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Sample records for neuromorphic bistable vlsi

  1. Robust working memory in an asynchronously spiking neural network realized in neuromorphic VLSI

    Directory of Open Access Journals (Sweden)

    Massimiliano eGiulioni

    2012-02-01

    Full Text Available We demonstrate bistable attractor dynamics in a spiking neural network implemented with neuromorphic VLSI hardware. The on-chip network consists of three interacting populations (two excitatory, one inhibitory of integrate-and-fire (LIF neurons. One excitatory population is distinguished by strong synaptic self-excitation, which sustains meta-stable states of ‘high’ and ‘low’-firing activity. Depending on the overall excitability, transitions to the ‘high’ state may be evoked by external stimulation, or may occur spontaneously due to random activity fluctuations. In the former case, the ‘high’ state retains a working memory of a stimulus until well after its release. In the latter case, ‘high’ states remain stable for seconds, three orders of magnitude longer than the largest time-scale implemented in the circuitry. Evoked and spontaneous transitions form a continuum and may exhibit a wide range of latencies, depending on the strength of external stimulation and of recurrent synaptic excitation. In addition, we investigated corrupted ‘high’ states comprising neurons of both excitatory populations. Within a basin of attraction, the network dynamics corrects such states and re-establishes the prototypical ‘high’ state. We conclude that, with effective theoretical guidance, full-fledged attractor dynamics can be realized with comparatively small populations of neuromorphic hardware neurons.

  2. Emergent auditory feature tuning in a real-time neuromorphic VLSI system

    Directory of Open Access Journals (Sweden)

    Sadique eSheik

    2012-02-01

    Full Text Available Many sounds of ecological importance, such as communication calls, are characterised by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamocortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP, which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectrotemporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step towards the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

  3. Liquid state machine with dendritically enhanced readout for low-power, neuromorphic VLSI implementations.

    Science.gov (United States)

    Roy, Subhrajit; Banerjee, Amitava; Basu, Arindam

    2014-10-01

    In this paper, we describe a new neuro-inspired, hardware-friendly readout stage for the liquid state machine (LSM), a popular model for reservoir computing. Compared to the parallel perceptron architecture trained by the p-delta algorithm, which is the state of the art in terms of performance of readout stages, our readout architecture and learning algorithm can attain better performance with significantly less synaptic resources making it attractive for VLSI implementation. Inspired by the nonlinear properties of dendrites in biological neurons, our readout stage incorporates neurons having multiple dendrites with a lumped nonlinearity (two compartment model). The number of synaptic connections on each branch is significantly lower than the total number of connections from the liquid neurons and the learning algorithm tries to find the best 'combination' of input connections on each branch to reduce the error. Hence, the learning involves network rewiring (NRW) of the readout network similar to structural plasticity observed in its biological counterparts. We show that compared to a single perceptron using analog weights, this architecture for the readout can attain, even by using the same number of binary valued synapses, up to 3.3 times less error for a two-class spike train classification problem and 2.4 times less error for an input rate approximation task. Even with 60 times larger synapses, a group of 60 parallel perceptrons cannot attain the performance of the proposed dendritically enhanced readout. An additional advantage of this method for hardware implementations is that the 'choice' of connectivity can be easily implemented exploiting address event representation (AER) protocols commonly used in current neuromorphic systems where the connection matrix is stored in memory. Also, due to the use of binary synapses, our proposed method is more robust against statistical variations.

  4. Emulated Muscle Spindle and Spiking Afferents Validates VLSI Neuromorphic Hardware as a Testbed for Sensorimotor Function and Disease

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    Chuanxin M. Niu

    2014-12-01

    Full Text Available The lack of multi-scale empirical measurements (e.g. recording simultaneously from neurons, muscles, whole body, etc. complicates understanding of sensorimotor function in humans. This is particularly true for the understanding of development during childhood, which requires evaluation of measurements over many years. We have developed a synthetic platform for emulating multi-scale activity of the vertebrate sensorimotor system. Our design benefits from Very Large Scale Integrated-circuit (VLSI technology to provide considerable scalability and high-speed, as much as 365x faster than real-time. An essential component of our design is the proprioceptive sensor, or muscle spindle. Here we demonstrate an accurate and extremely fast emulation of a muscle spindle and its spiking afferents, which are computationally expensive but fundamental for reflex functions. We implemented a well-known rate-based model of the spindle (Mileusnic et al., 2006 and a simplified spiking sensory neuron model using the Izhikevich approximation to the Hodgkin-Huxley model. The resulting behavior of our afferent sensory system is qualitatively compatible with classic cat soleus recording (Matthews, 1964; 1972; Crowe and Matthews, 1964b. Our results suggest that this simplified structure of the spindle and afferent neuron is sufficient to produce physiologically-realistic behavior. The VLSI technology allows us to accelerate this behavior beyond 365x real-time. Our goal is to use this testbed for predicting years of disease progression with only a few days of emulation. This is the first hardware emulation of the spindle afferent system, and it may have application not only for emulation of human health and disease, but also for the construction of compliant neuromorphic robotic systems.

  5. Emulated muscle spindle and spiking afferents validates VLSI neuromorphic hardware as a testbed for sensorimotor function and disease.

    Science.gov (United States)

    Niu, Chuanxin M; Nandyala, Sirish K; Sanger, Terence D

    2014-01-01

    The lack of multi-scale empirical measurements (e.g., recording simultaneously from neurons, muscles, whole body, etc.) complicates understanding of sensorimotor function in humans. This is particularly true for the understanding of development during childhood, which requires evaluation of measurements over many years. We have developed a synthetic platform for emulating multi-scale activity of the vertebrate sensorimotor system. Our design benefits from Very Large Scale Integrated-circuit (VLSI) technology to provide considerable scalability and high-speed, as much as 365× faster than real-time. An essential component of our design is the proprioceptive sensor, or muscle spindle. Here we demonstrate an accurate and extremely fast emulation of a muscle spindle and its spiking afferents, which are computationally expensive but fundamental for reflex functions. We implemented a well-known rate-based model of the spindle (Mileusnic et al., 2006) and a simplified spiking sensory neuron model using the Izhikevich approximation to the Hodgkin-Huxley model. The resulting behavior of our afferent sensory system is qualitatively compatible with classic cat soleus recording (Crowe and Matthews, 1964b; Matthews, 1964, 1972). Our results suggest that this simplified structure of the spindle and afferent neuron is sufficient to produce physiologically-realistic behavior. The VLSI technology allows us to accelerate this behavior beyond 365× real-time. Our goal is to use this testbed for predicting years of disease progression with only a few days of emulation. This is the first hardware emulation of the spindle afferent system, and it may have application not only for emulation of human health and disease, but also for the construction of compliant neuromorphic robotic systems.

  6. Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

    Science.gov (United States)

    Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; Del Giudice, Paolo

    2015-10-01

    Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.

  7. VLSI design

    CERN Document Server

    Einspruch, Norman G

    1986-01-01

    VLSI Electronics Microstructure Science, Volume 14: VLSI Design presents a comprehensive exposition and assessment of the developments and trends in VLSI (Very Large Scale Integration) electronics. This volume covers topics that range from microscopic aspects of materials behavior and device performance to the comprehension of VLSI in systems applications. Each article is prepared by a recognized authority. The subjects discussed in this book include VLSI processor design methodology; the RISC (Reduced Instruction Set Computer); the VLSI testing program; silicon compilers for VLSI; and special

  8. VLSI design

    CERN Document Server

    Basu, D K

    2014-01-01

    Very Large Scale Integrated Circuits (VLSI) design has moved from costly curiosity to an everyday necessity, especially with the proliferated applications of embedded computing devices in communications, entertainment and household gadgets. As a result, more and more knowledge on various aspects of VLSI design technologies is becoming a necessity for the engineering/technology students of various disciplines. With this goal in mind the course material of this book has been designed to cover the various fundamental aspects of VLSI design, like Categorization and comparison between various technologies used for VLSI design Basic fabrication processes involved in VLSI design Design of MOS, CMOS and Bi CMOS circuits used in VLSI Structured design of VLSI Introduction to VHDL for VLSI design Automated design for placement and routing of VLSI systems VLSI testing and testability The various topics of the book have been discussed lucidly with analysis, when required, examples, figures and adequate analytical and the...

  9. Neuromorphic Silicon Neuron Circuits

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Hamilton, Tara Julia; van Schaik, André; Etienne-Cummings, Ralph; Delbruck, Tobi; Liu, Shih-Chii; Dudek, Piotr; Häfliger, Philipp; Renaud, Sylvie; Schemmel, Johannes; Cauwenberghs, Gert; Arthur, John; Hynna, Kai; Folowosele, Fopefolu; Saighi, Sylvain; Serrano-Gotarredona, Teresa; Wijekoon, Jayawan; Wang, Yingxue; Boahen, Kwabena

    2011-01-01

    Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain–machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin–Huxley models to bi-dimensional generalized adaptive integrate and fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips. PMID:21747754

  10. Neuromorphic silicon neuron circuits

    Directory of Open Access Journals (Sweden)

    Giacomo eIndiveri

    2011-05-01

    Full Text Available Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance based Hodgkin-Huxley models to bi-dimensional generalized adaptive Integrate and Fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips.

  11. VLSI design

    CERN Document Server

    Chandrasetty, Vikram Arkalgud

    2011-01-01

    This book provides insight into the practical design of VLSI circuits. It is aimed at novice VLSI designers and other enthusiasts who would like to understand VLSI design flows. Coverage includes key concepts in CMOS digital design, design of DSP and communication blocks on FPGAs, ASIC front end and physical design, and analog and mixed signal design. The approach is designed to focus on practical implementation of key elements of the VLSI design process, in order to make the topic accessible to novices. The design concepts are demonstrated using software from Mathworks, Xilinx, Mentor Graphic

  12. VLSI metallization

    CERN Document Server

    Einspruch, Norman G; Gildenblat, Gennady Sh

    1987-01-01

    VLSI Electronics Microstructure Science, Volume 15: VLSI Metallization discusses the various issues and problems related to VLSI metallization. It details the available solutions and presents emerging trends.This volume is comprised of 10 chapters. The two introductory chapters, Chapter 1 and 2 serve as general references for the electrical and metallurgical properties of thin conducting films. Subsequent chapters review the various aspects of VLSI metallization. The order of presentation has been chosen to follow the common processing sequence. In Chapter 3, some relevant metal deposition tec

  13. Large-scale neuromorphic computing systems

    Science.gov (United States)

    Furber, Steve

    2016-10-01

    Neuromorphic computing covers a diverse range of approaches to information processing all of which demonstrate some degree of neurobiological inspiration that differentiates them from mainstream conventional computing systems. The philosophy behind neuromorphic computing has its origins in the seminal work carried out by Carver Mead at Caltech in the late 1980s. This early work influenced others to carry developments forward, and advances in VLSI technology supported steady growth in the scale and capability of neuromorphic devices. Recently, a number of large-scale neuromorphic projects have emerged, taking the approach to unprecedented scales and capabilities. These large-scale projects are associated with major new funding initiatives for brain-related research, creating a sense that the time and circumstances are right for progress in our understanding of information processing in the brain. In this review we present a brief history of neuromorphic engineering then focus on some of the principal current large-scale projects, their main features, how their approaches are complementary and distinct, their advantages and drawbacks, and highlight the sorts of capabilities that each can deliver to neural modellers.

  14. Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

    Science.gov (United States)

    Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

    2017-08-01

    Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a

  15. A Re-configurable On-line Learning Spiking Neuromorphic Processor comprising 256 neurons and 128K synapses

    Directory of Open Access Journals (Sweden)

    Ning eQiao

    2015-04-01

    Full Text Available Implementing compact, low-power artificial neural processing systems with real-time on-line learning abilities is still an open challenge. In this paper we present a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems. The proposed architecture allows the on-chip configuration of a wide range of network connectivities, including recurrent and deep networks with short-term and long-term plasticity. The device comprises 128 K analog synapse and 256 neuron circuits with biologically plausible dynamics and bi-stable spike-based plasticity mechanisms that endow it with on-line learning abilities. In addition to the analog circuits, the device comprises also asynchronous digital logic circuits for setting different synapse and neuron properties as well as different network configurations. This prototype device, fabricated using a 180 nm 1P6M CMOS process, occupies an area of 51.4 mm 2 , and consumes approximately 4 mW for typical experiments, for example involving attractor networks. Here we describe the details of the overall architecture and of the individual circuits and present experimental results that showcase its potential. By supporting a wide range of cortical-like computational modules comprising plasticity mechanisms, this device will enable the realization of intelligent autonomous systems with on-line learning capabilities.

  16. VLSI electronics microstructure science

    CERN Document Server

    1982-01-01

    VLSI Electronics: Microstructure Science, Volume 4 reviews trends for the future of very large scale integration (VLSI) electronics and the scientific base that supports its development.This book discusses the silicon-on-insulator for VLSI and VHSIC, X-ray lithography, and transient response of electron transport in GaAs using the Monte Carlo method. The technology and manufacturing of high-density magnetic-bubble memories, metallic superlattices, challenge of education for VLSI, and impact of VLSI on medical signal processing are also elaborated. This text likewise covers the impact of VLSI t

  17. VLSI in medicine

    CERN Document Server

    Einspruch, Norman G

    1989-01-01

    VLSI Electronics Microstructure Science, Volume 17: VLSI in Medicine deals with the more important applications of VLSI in medical devices and instruments.This volume is comprised of 11 chapters. It begins with an article about medical electronics. The following three chapters cover diagnostic imaging, focusing on such medical devices as magnetic resonance imaging, neurometric analyzer, and ultrasound. Chapters 5, 6, and 7 present the impact of VLSI in cardiology. The electrocardiograph, implantable cardiac pacemaker, and the use of VLSI in Holter monitoring are detailed in these chapters. The

  18. VLSI electronics microstructure science

    CERN Document Server

    1981-01-01

    VLSI Electronics: Microstructure Science, Volume 3 evaluates trends for the future of very large scale integration (VLSI) electronics and the scientific base that supports its development.This book discusses the impact of VLSI on computer architectures; VLSI design and design aid requirements; and design, fabrication, and performance of CCD imagers. The approaches, potential, and progress of ultra-high-speed GaAs VLSI; computer modeling of MOSFETs; and numerical physics of micron-length and submicron-length semiconductor devices are also elaborated. This text likewise covers the optical linewi

  19. Progress in neuromorphic photonics

    Science.gov (United States)

    Ferreira de Lima, Thomas; Shastri, Bhavin J.; Tait, Alexander N.; Nahmias, Mitchell A.; Prucnal, Paul R.

    2017-03-01

    As society's appetite for information continues to grow, so does our need to process this information with increasing speed and versatility. Many believe that the one-size-fits-all solution of digital electronics is becoming a limiting factor in certain areas such as data links, cognitive radio, and ultrafast control. Analog photonic devices have found relatively simple signal processing niches where electronics can no longer provide sufficient speed and reconfigurability. Recently, the landscape for commercially manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. By bridging the mathematical prowess of artificial neural networks to the underlying physics of optoelectronic devices, neuromorphic photonics could breach new domains of information processing demanding significant complexity, low cost, and unmatched speed. In this article, we review the progress in neuromorphic photonics, focusing on photonic integrated devices. The challenges and design rules for optoelectronic instantiation of artificial neurons are presented. The proposed photonic architecture revolves around the processing network node composed of two parts: a nonlinear element and a network interface. We then survey excitable lasers in the recent literature as candidates for the nonlinear node and microring-resonator weight banks as the network interface. Finally, we compare metrics between neuromorphic electronics and neuromorphic photonics and discuss potential applications.

  20. Dynamic Neural Fields as a Step Towards Cognitive Neuromorphic Architectures

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    Yulia eSandamirskaya

    2014-01-01

    Full Text Available Dynamic Field Theory (DFT is an established framework for modelling embodied cognition. In DFT, elementary cognitive functions such as memory formation, formation of grounded representations, attentional processes, decision making, adaptation, and learning emerge from neuronal dynamics. The basic computational element of this framework is a Dynamic Neural Field (DNF. Under constraints on the time-scale of the dynamics, the DNF is computationally equivalent to a soft winner-take-all (WTA network, which is considered one of the basic computational units in neuronal processing. Recently, it has been shown how a WTA network may be implemented in neuromorphic hardware, such as analogue Very Large Scale Integration (VLSI device. This paper leverages the relationship between DFT and soft WTA networks to systematically revise and integrate established DFT mechanisms that have previously been spread among different architectures. In addition, I also identify some novel computational and architectural mechanisms of DFT which may be implemented in neuromorphic VLSI devices using WTA networks as an intermediate computational layer. These specific mechanisms include the stabilization of working memory, the coupling of sensory systems to motor dynamics, intentionality, and autonomous learning. I further demonstrate how all these elements may be integrated into a unified architecture to generate behavior and autonomous learning.

  1. Plasma processing for VLSI

    CERN Document Server

    Einspruch, Norman G

    1984-01-01

    VLSI Electronics: Microstructure Science, Volume 8: Plasma Processing for VLSI (Very Large Scale Integration) discusses the utilization of plasmas for general semiconductor processing. It also includes expositions on advanced deposition of materials for metallization, lithographic methods that use plasmas as exposure sources and for multiple resist patterning, and device structures made possible by anisotropic etching.This volume is divided into four sections. It begins with the history of plasma processing, a discussion of some of the early developments and trends for VLSI. The second section

  2. Foldable neuromorphic memristive electronics

    KAUST Repository

    Ghoneim, Mohamed T.

    2014-07-01

    Neuromorphic computer will need folded architectural form factor to match brain cortex\\'s folded pattern for ultra-compact design. In this work, we show a state-of-the-art CMOS compatible pragmatic fabrication approach of building structurally foldable and densely integrated neuromorphic devices for non-volatile memory applications. We report the first ever memristive devices with the size of a motor neuron on bulk mono-crystalline silicon (100) and then with trench-protect-release-recycle process transform the silicon wafer with devices into a flexible and semi-transparent silicon fabric while recycling the remaining wafer for further use. This process unconditionally offers the ultra-large-scale-integration opportunity-increasingly critical for ultra-compact memory.

  3. A Review of Current Neuromorphic Approaches for Vision, Auditory, and Olfactory Sensors.

    Science.gov (United States)

    Vanarse, Anup; Osseiran, Adam; Rassau, Alexander

    2016-01-01

    Conventional vision, auditory, and olfactory sensors generate large volumes of redundant data and as a result tend to consume excessive power. To address these shortcomings, neuromorphic sensors have been developed. These sensors mimic the neuro-biological architecture of sensory organs using aVLSI (analog Very Large Scale Integration) and generate asynchronous spiking output that represents sensing information in ways that are similar to neural signals. This allows for much lower power consumption due to an ability to extract useful sensory information from sparse captured data. The foundation for research in neuromorphic sensors was laid more than two decades ago, but recent developments in understanding of biological sensing and advanced electronics, have stimulated research on sophisticated neuromorphic sensors that provide numerous advantages over conventional sensors. In this paper, we review the current state-of-the-art in neuromorphic implementation of vision, auditory, and olfactory sensors and identify key contributions across these fields. Bringing together these key contributions we suggest a future research direction for further development of the neuromorphic sensing field.

  4. Neuromorphic Computing for Cognitive Cybersecurity

    Science.gov (United States)

    2017-03-20

    neuromorphic computing using threshold gate networks. Keywords: Neuromorphic computing; Neural networks; cybersecurity Introduction Traditional CMOS scaling...for neural nets is a combined multiply-accumulate operation, evaluated by using a threshold . Neurons of this type implement threshold gate...there is much work to be done in the following areas: • One shot learning, unsupervised learning, concept drift; • Data reduction techniques

  5. Lithography for VLSI

    CERN Document Server

    Einspruch, Norman G

    1987-01-01

    VLSI Electronics Microstructure Science, Volume 16: Lithography for VLSI treats special topics from each branch of lithography, and also contains general discussion of some lithographic methods.This volume contains 8 chapters that discuss the various aspects of lithography. Chapters 1 and 2 are devoted to optical lithography. Chapter 3 covers electron lithography in general, and Chapter 4 discusses electron resist exposure modeling. Chapter 5 presents the fundamentals of ion-beam lithography. Mask/wafer alignment for x-ray proximity printing and for optical lithography is tackled in Chapter 6.

  6. Neuromorphic atomic switch networks.

    Directory of Open Access Journals (Sweden)

    Audrius V Avizienis

    Full Text Available Efforts to emulate the formidable information processing capabilities of the brain through neuromorphic engineering have been bolstered by recent progress in the fabrication of nonlinear, nanoscale circuit elements that exhibit synapse-like operational characteristics. However, conventional fabrication techniques are unable to efficiently generate structures with the highly complex interconnectivity found in biological neuronal networks. Here we demonstrate the physical realization of a self-assembled neuromorphic device which implements basic concepts of systems neuroscience through a hardware-based platform comprised of over a billion interconnected atomic-switch inorganic synapses embedded in a complex network of silver nanowires. Observations of network activation and passive harmonic generation demonstrate a collective response to input stimulus in agreement with recent theoretical predictions. Further, emergent behaviors unique to the complex network of atomic switches and akin to brain function are observed, namely spatially distributed memory, recurrent dynamics and the activation of feedforward subnetworks. These devices display the functional characteristics required for implementing unconventional, biologically and neurally inspired computational methodologies in a synthetic experimental system.

  7. Transformational VLSI Design

    DEFF Research Database (Denmark)

    Rasmussen, Ole Steen

    This thesis introduces a formal approach to deriving VLSI circuits by the use of correctness-preserving transformations. Both the specification and the implementation are descibed by the relation based language Ruby. In order to prove the transformation rules a proof tool called RubyZF has been...

  8. Neuromorphic UAS Collision Avoidance Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Using biologically-inspired neuromorphic optic flow algorithms is a novel approach in collision avoidance for UAS. Traditional computer vision algorithms rely on...

  9. Neuromorphic meets neuromechanics, part I: the methodology and implementation

    Science.gov (United States)

    Niu, Chuanxin M.; Jalaleddini, Kian; Sohn, Won Joon; Rocamora, John; Sanger, Terence D.; Valero-Cuevas, Francisco J.

    2017-04-01

    Objective: One goal of neuromorphic engineering is to create ‘realistic’ robotic systems that interact with the physical world by adopting neuromechanical principles from biology. Critical to this is the methodology to implement the spinal circuitry responsible for the behavior of afferented muscles. At its core, muscle afferentation is the closed-loop behavior arising from the interactions among populations of muscle spindle afferents, alpha and gamma motoneurons, and muscle fibers to enable useful behaviors. Approach. We used programmable very- large-scale-circuit (VLSI) hardware to implement simple models of spiking neurons, skeletal muscles, muscle spindle proprioceptors, alpha-motoneuron recruitment, gamma motoneuron control of spindle sensitivity, and the monosynaptic circuitry connecting them. This multi-scale system of populations of spiking neurons emulated the physiological properties of a pair of antagonistic afferented mammalian muscles (each simulated by 1024 alpha- and gamma-motoneurones) acting on a joint via long tendons. Main results. This integrated system was able to maintain a joint angle, and reproduced stretch reflex responses even when driving the nonlinear biomechanics of an actual cadaveric finger. Moreover, this system allowed us to explore numerous values and combinations of gamma-static and gamma-dynamic gains when driving a robotic finger, some of which replicated some human pathological conditions. Lastly, we explored the behavioral consequences of adopting three alternative models of isometric muscle force production. We found that the dynamic responses to rate-coded spike trains produce force ramps that can be very sensitive to tendon elasticity, especially at high force output. Significance. Our methodology produced, to our knowledge, the first example of an autonomous, multi-scale, neuromorphic, neuromechanical system capable of creating realistic reflex behavior in cadaveric fingers. This research platform allows us to explore

  10. The VLSI handbook

    CERN Document Server

    Chen, Wai-Kai

    2007-01-01

    Written by a stellar international panel of expert contributors, this handbook remains the most up-to-date, reliable, and comprehensive source for real answers to practical problems. In addition to updated information in most chapters, this edition features several heavily revised and completely rewritten chapters, new chapters on such topics as CMOS fabrication and high-speed circuit design, heavily revised sections on testing of digital systems and design languages, and two entirely new sections on low-power electronics and VLSI signal processing. An updated compendium of references and othe

  11. UW VLSI chip tester

    Science.gov (United States)

    McKenzie, Neil

    1989-12-01

    We present a design for a low-cost, functional VLSI chip tester. It is based on the Apple MacIntosh II personal computer. It tests chips that have up to 128 pins. All pin drivers of the tester are bidirectional; each pin is programmed independently as an input or an output. The tester can test both static and dynamic chips. Rudimentary speed testing is provided. Chips are tested by executing C programs written by the user. A software library is provided for program development. Tests run under both the Mac Operating System and A/UX. The design is implemented using Xilinx Logic Cell Arrays. Price/performance tradeoffs are discussed.

  12. VLSI signal processing technology

    CERN Document Server

    Swartzlander, Earl

    1994-01-01

    This book is the first in a set of forthcoming books focussed on state-of-the-art development in the VLSI Signal Processing area. It is a response to the tremendous research activities taking place in that field. These activities have been driven by two factors: the dramatic increase in demand for high speed signal processing, especially in consumer elec­ tronics, and the evolving microelectronic technologies. The available technology has always been one of the main factors in determining al­ gorithms, architectures, and design strategies to be followed. With every new technology, signal processing systems go through many changes in concepts, design methods, and implementation. The goal of this book is to introduce the reader to the main features of VLSI Signal Processing and the ongoing developments in this area. The focus of this book is on: • Current developments in Digital Signal Processing (DSP) pro­ cessors and architectures - several examples and case studies of existing DSP chips are discussed in...

  13. VLSI implementations for image communications

    CERN Document Server

    Pirsch, P

    1993-01-01

    The past few years have seen a rapid growth in image processing and image communication technologies. New video services and multimedia applications are continuously being designed. Essential for all these applications are image and video compression techniques. The purpose of this book is to report on recent advances in VLSI architectures and their implementation for video signal processing applications with emphasis on video coding for bit rate reduction. Efficient VLSI implementation for video signal processing spans a broad range of disciplines involving algorithms, architectures, circuits

  14. Closed-loop neuromorphic benchmarks

    CSIR Research Space (South Africa)

    Stewart, TC

    2015-11-01

    Full Text Available the study was exempt from ethical approval procedures.) Did the study presented in the manuscript involve human or animal subjects: No I v i w 1Closed-loop Neuromorphic Benchmarks Terrence C. Stewart 1,∗, Travis DeWolf 1, Ashley Kleinhans 2 and Chris..._link335 program from ev3dev-c (https://github.com/in4lio/ev3dev-c). This allows the EV3 to336 listen for UDP commands that tell it to set motor values and read sensor values. Communication with337 a PC was over a USB link (although the system also...

  15. Declarative Descriptions for VLSI Generators

    Science.gov (United States)

    1986-06-01

    will review languages in each category. Sheeran [ Sheeran 83] proposes a structured hierarchical design language, IL, FP (a variation of the...IEEE, 1982. [ Sheeran 83] Mary Sheeran . p& FP -An Algebraic VLSI Design Language. PhD thesis, Oxford University Computing Laboratory, November, 1983

  16. VLSI mixed signal processing system

    Science.gov (United States)

    Alvarez, A.; Premkumar, A. B.

    1993-01-01

    An economical and efficient VLSI implementation of a mixed signal processing system (MSP) is presented in this paper. The MSP concept is investigated and the functional blocks of the proposed MSP are described. The requirements of each of the blocks are discussed in detail. A sample application using active acoustic cancellation technique is described to demonstrate the power of the MSP approach.

  17. Fundamentals of Microelectronics Processing (VLSI).

    Science.gov (United States)

    Takoudis, Christos G.

    1987-01-01

    Describes a 15-week course in the fundamentals of microelectronics processing in chemical engineering, which emphasizes the use of very large scale integration (VLSI). Provides a listing of the topics covered in the course outline, along with a sample of some of the final projects done by students. (TW)

  18. Bistable microelectromechanical actuator

    Science.gov (United States)

    Fleming, J.G.

    1999-02-02

    A bistable microelectromechanical (MEM) actuator is formed on a substrate and includes a stressed membrane of generally rectangular shape that upon release assumes a curvilinear cross-sectional shape due to attachment at a midpoint to a resilient member and at opposing edges to a pair of elongate supports. The stressed membrane can be electrostatically switched between a pair of mechanical states having mirror-image symmetry, with the MEM actuator remaining in a quiescent state after a programming voltage is removed. The bistable MEM actuator according to various embodiments of the present invention can be used to form a nonvolatile memory element, an optical modulator (with a pair of mirrors supported above the membrane and moving in synchronism as the membrane is switched), a switchable mirror (with a single mirror supported above the membrane at the midpoint thereof) and a latching relay (with a pair of contacts that open and close as the membrane is switched). Arrays of bistable MEM actuators can be formed for applications including nonvolatile memories, optical displays and optical computing. 49 figs.

  19. A Coherent VLSI Design Environment.

    Science.gov (United States)

    1985-03-31

    We would like to acknowledge the contributions by Flavio Rose of MIT when we first studied this problem. The three of us originally produced a O(1V13...Rinehart and Winston, New York, 1976. 18] Charles E. Leiserson, Flavio M. Rose, and James B. Saxe, "Optimizing synchronous circuitry by retiming... Flavio M. Rose, Models for VLSI CircuiLs, Masters Thesis, Department of Electrical En- gineering and Computer Science, Massachusetts Institute of

  20. Reversibly Bistable Flexible Electronics

    KAUST Repository

    Alfaraj, Nasir

    2015-05-01

    Introducing the notion of transformational silicon electronics has paved the way for integrating various applications with silicon-based, modern, high-performance electronic circuits that are mechanically flexible and optically semitransparent. While maintaining large-scale production and prototyping rapidity, this flexible and translucent scheme demonstrates the potential to transform conventionally stiff electronic devices into thin and foldable ones without compromising long-term performance and reliability. In this work, we report on the fabrication and characterization of reversibly bistable flexible electronic switches that utilize flexible n-channel metal-oxide-semiconductor field-effect transistors. The transistors are fabricated initially on rigid (100) silicon substrates before they are peeled off. They can be used to control flexible batches of light-emitting diodes, demonstrating both the relative ease of scaling at minimum cost and maximum reliability and the feasibility of integration. The peeled-off silicon fabric is about 25 µm thick. The fabricated devices are transferred to a reversibly bistable flexible platform through which, for example, a flexible smartphone can be wrapped around a user’s wrist and can also be set back to its original mechanical position. Buckling and cyclic bending of such host platforms brings a completely new dimension to the development of flexible electronics, especially rollable displays.

  1. Radiative Bistability and Thermal Memory

    Science.gov (United States)

    Kubytskyi, Viacheslav; Biehs, Svend-Age; Ben-Abdallah, Philippe

    2014-08-01

    We predict the existence of a thermal bistability in many-body systems out of thermal equilibrium which exchange heat by thermal radiation using insulator-metal transition materials. We propose a writing-reading procedure and demonstrate the possibility to exploit the thermal bistability to make a volatile thermal memory. We show that this thermal memory can be used to store heat and thermal information (via an encoding temperature) for arbitrary long times. The radiative thermal bistability could find broad applications in the domains of thermal management, information processing, and energy storage.

  2. Parallel Evolutionary Optimization for Neuromorphic Network Training

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Disney, Adam [University of Tennessee (UT); Singh, Susheela [North Carolina State University (NCSU), Raleigh; Bruer, Grant [University of Tennessee (UT); Mitchell, John Parker [University of Tennessee (UT); Klibisz, Aleksander [University of Tennessee (UT); Plank, James [University of Tennessee (UT)

    2016-01-01

    One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impact the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.

  3. Surface and interface effects in VLSI

    CERN Document Server

    Einspruch, Norman G

    1985-01-01

    VLSI Electronics Microstructure Science, Volume 10: Surface and Interface Effects in VLSI provides the advances made in the science of semiconductor surface and interface as they relate to electronics. This volume aims to provide a better understanding and control of surface and interface related properties. The book begins with an introductory chapter on the intimate link between interfaces and devices. The book is then divided into two parts. The first part covers the chemical and geometric structures of prototypical VLSI interfaces. Subjects detailed include, the technologically most import

  4. Serendipitous offline learning in a neuromorphic robot

    CSIR Research Space (South Africa)

    Stewart, TC

    2016-02-01

    Full Text Available We demonstrate a hybrid neuromorphic learning paradigm that learns complex senso-rimotor mappings based on a small set of hard-coded reflex behaviors. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviors. All sensor...

  5. VLSI Technology for Cognitive Radio

    Science.gov (United States)

    VIJAYALAKSHMI, B.; SIDDAIAH, P.

    2017-08-01

    One of the most challenging tasks of cognitive radio is the efficiency in the spectrum sensing scheme to overcome the spectrum scarcity problem. The popular and widely used spectrum sensing technique is the energy detection scheme as it is very simple and doesn’t require any previous information related to the signal. We propose one such approach which is an optimised spectrum sensing scheme with reduced filter structure. The optimisation is done in terms of area and power performance of the spectrum. The simulations of the VLSI structure of the optimised flexible spectrum is done using verilog coding by using the XILINX ISE software. Our method produces performance with 13% reduction in area and 66% reduction in power consumption in comparison to the flexible spectrum sensing scheme. All the results are tabulated and comparisons are made. A new scheme for optimised and effective spectrum sensing opens up with our model.

  6. Optical bistability controlling light with light

    CERN Document Server

    Gibbs, Hyatt

    1985-01-01

    Optical Bistability: Controlling Light with Light focuses on optical bistability in nonlinear optical systems. Emphasis is on passive (non-laser) systems that exhibit reversible bistability with input intensity as the hysteresis variable, along with the physics and the potential applications of such systems for nonlinear optical signal processing. This book consists of seven chapters and begins with a historical overview of optical bistability in lasers and passive systems. The next chapter describes steady-state theories of optical bistability, including the Bonifacio-Lugiato model, as we

  7. Full custom VLSI - A technology for high performance computing

    Science.gov (United States)

    Maki, Gary K.; Whitaker, Sterling R.

    1990-01-01

    Full custom VLSI is presented as a viable technology for addressing the need for the computing capabilities required for the real-time health monitoring of spacecraft systems. This technology presents solutions that cannot be realized with stored program computers or semicustom VLSI; also, it is not dependent on current IC processes. It is argued that, while design time is longer, full custom VLSI produces the fastest and densest VLSI solution and that high density normally also yields low manufacturing costs.

  8. Toward exascale computing through neuromorphic approaches.

    Energy Technology Data Exchange (ETDEWEB)

    James, Conrad D.

    2010-09-01

    While individual neurons function at relatively low firing rates, naturally-occurring nervous systems not only surpass manmade systems in computing power, but accomplish this feat using relatively little energy. It is asserted that the next major breakthrough in computing power will be achieved through application of neuromorphic approaches that mimic the mechanisms by which neural systems integrate and store massive quantities of data for real-time decision making. The proposed LDRD provides a conceptual foundation for SNL to make unique advances toward exascale computing. First, a team consisting of experts from the HPC, MESA, cognitive and biological sciences and nanotechnology domains will be coordinated to conduct an exercise with the outcome being a concept for applying neuromorphic computing to achieve exascale computing. It is anticipated that this concept will involve innovative extension and integration of SNL capabilities in MicroFab, material sciences, high-performance computing, and modeling and simulation of neural processes/systems.

  9. Flexible Bistable Cholesteric Reflective Displays

    Science.gov (United States)

    Yang, Deng-Ke

    2006-03-01

    Cholesteric liquid crystals (ChLCs) exhibit two stable states at zero field condition-the reflecting planar state and the nonreflecting focal conic state. ChLCs are an excellent candidate for inexpensive and rugged electronic books and papers. This paper will review the display cell structure,materials and drive schemes for flexible bistable cholesteric (Ch) reflective displays.

  10. Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2015-01-01

    Dynamic Adaptive Neural Network Array (DANNA) is a neuromorphic hardware implementation. It differs from most other neuromorphic projects in that it allows for programmability of structure, and it is trained or designed using evolutionary optimization. This paper describes the DANNA structure, how DANNA is trained using evolutionary optimization, and an application of DANNA to a very simple classification task.

  11. A coherent VLSI design environment

    Science.gov (United States)

    Penfield, Paul, Jr.

    1988-05-01

    The CAD effort is centered on timing analysis and circuit simulation. Advances have been made in tightening the bounds of timing analysis. The superiority of the Gauss-Jacobi technique for matrix solution, over the Gauss-Seidel method, has been proven when the algorithms are implemented on massively parallel machines. In the circuits area, one result of importance is a new technique for calculating the highest frequency of operation of transistors with parasitic elements present. Work on a synthesis technique is under way. In the architecture area, many new results have been derived for parallel algorithms and complexity. One of the most astonishing is that a hypercube with a large number of faulty nodes can be used, with high probability, as another perfectly functioning hypercube of half the size, by using reconfiguration algorithms that are simple, fast, and require only local information. Also, the design of the message-driven processor is continuing, with several advances in architecture, software, communications, and ALU design. Many of these are being implemented in VLSI circuits. The theory work has as a central theme that the cost of communication should be included in complexity analyses. This has led to advances in models for computation, including volume-universal networks, routing, network flow, fault avoidance, queue management, and network simulation.

  12. Neuromorphic cognitive systems a learning and memory centered approach

    CERN Document Server

    Yu, Qiang; Hu, Jun; Tan Chen, Kay

    2017-01-01

    This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromo...

  13. VLSI-distributed architectures for smart cameras

    Science.gov (United States)

    Wolf, Wayne H.

    2001-03-01

    Smart cameras use video/image processing algorithms to capture images as objects, not as pixels. This paper describes architectures for smart cameras that take advantage of VLSI to improve the capabilities and performance of smart camera systems. Advances in VLSI technology aid in the development of smart cameras in two ways. First, VLSI allows us to integrate large amounts of processing power and memory along with image sensors. CMOS sensors are rapidly improving in performance, allowing us to integrate sensors, logic, and memory on the same chip. As we become able to build chips with hundreds of millions of transistors, we will be able to include powerful multiprocessors on the same chip as the image sensors. We call these image sensor/multiprocessor systems image processors. Second, VLSI allows us to put a large number of these powerful sensor/processor systems on a single scene. VLSI factories will produce large quantities of these image processors, making it cost-effective to use a large number of them in a single location. Image processors will be networked into distributed cameras that use many sensors as well as the full computational resources of all the available multiprocessors. Multiple cameras make a number of image recognition tasks easier: we can select the best view of an object, eliminate occlusions, and use 3D information to improve the accuracy of object recognition. This paper outlines approaches to distributed camera design: architectures for image processors and distributed cameras; algorithms to run on distributed smart cameras, and applications of which VLSI distributed camera systems.

  14. Compact MOSFET models for VLSI design

    CERN Document Server

    Bhattacharyya, A B

    2009-01-01

    Practicing designers, students, and educators in the semiconductor field face an ever expanding portfolio of MOSFET models. In Compact MOSFET Models for VLSI Design , A.B. Bhattacharyya presents a unified perspective on the topic, allowing the practitioner to view and interpret device phenomena concurrently using different modeling strategies. Readers will learn to link device physics with model parameters, helping to close the gap between device understanding and its use for optimal circuit performance. Bhattacharyya also lays bare the core physical concepts that will drive the future of VLSI.

  15. Associative Pattern Recognition In Analog VLSI Circuits

    Science.gov (United States)

    Tawel, Raoul

    1995-01-01

    Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

  16. Use of polyimides in VLSI fabrication

    Science.gov (United States)

    Wilson, A. M.

    The functional requirements of overcoats and multilevel insulators for very large scale integrated circuits (VLSI) are outlined. The moisture barrier properties of polyimide films are reviewed. Polyimide performance vs plasma enhanced chemically vapor deposited (CVD) silicon nitride overcoats are compared. The topological and via forming advantages of polyimides vs plasma enhanced CVD silicon oxide as a multilevel insulator are cited. The temperature and voltage field induced electronic charge transport and trapping at oxide interfaces is cited as the most serious limitation to the use of polyimides as multilevel insulators on VLSI chips.

  17. Functionally rigid bistable [2]rotaxanes

    DEFF Research Database (Denmark)

    Nygaard, Sune; Leung, Ken C-F; Aprahamian, Ivan

    2007-01-01

    component resides, to all intents and purposes, predominantly on the MPTTF unit in the ground state. As a consequence of these two effects, the assignment of NMR and UV-vis data is more simplified as compared to previous donor-acceptor bistable [2]rotaxanes. This development has not only allowed for much......Two-station [2]rotaxanes in the shape of a degenerate naphthalene (NP) shuttle and a nondegenerate monopyrrolotetrathiafulvalene (MPTTF)/NP redox-controllable switch have been synthesized and characterized in solution. Their dumbbell-shaped components are composed of polyether chains interrupted......-free bistable [2]rotaxane. Utilization of MPTTF removes the cis/trans isomerization that characterizes the tetrathiafulvalene (TTF) parent core structure. Furthermore, only one translational isomer is observed (> 95

  18. An Application Development Platform for Neuromorphic Computing

    Energy Technology Data Exchange (ETDEWEB)

    Dean, Mark [University of Tennessee (UT); Chan, Jason [University of Tennessee (UT); Daffron, Christopher [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT); Rose, Garrett [University of Tennessee (UT); Plank, James [University of Tennessee (UT); Birdwell, John Douglas [University of Tennessee (UT); Schuman, Catherine D [ORNL

    2016-01-01

    Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic computing systems developed as a hardware based approach to the implementation of neural networks. They feature highly adaptive and programmable structural elements, which model arti cial neural networks with spiking behavior. We design them to solve problems using evolutionary optimization. In this paper, we highlight the current hardware and software implementations of DANNA, including their features, functionalities and performance. We then describe the development of an Application Development Platform (ADP) to support efficient application implementation and testing of DANNA based solutions. We conclude with future directions.

  19. An Evolutionary Optimization Framework for Neural Networks and Neuromorphic Architectures

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Plank, James [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2016-01-01

    As new neural network and neuromorphic architectures are being developed, new training methods that operate within the constraints of the new architectures are required. Evolutionary optimization (EO) is a convenient training method for new architectures. In this work, we review a spiking neural network architecture and a neuromorphic architecture, and we describe an EO training framework for these architectures. We present the results of this training framework on four classification data sets and compare those results to other neural network and neuromorphic implementations. We also discuss how this EO framework may be extended to other architectures.

  20. Neuromorphic computing applications for network intrusion detection systems

    Science.gov (United States)

    Garcia, Raymond C.; Pino, Robinson E.

    2014-05-01

    What is presented here is a sequence of evolving concepts for network intrusion detection. These concepts start with neuromorphic structures for XOR-based signature matching and conclude with computationally based network intrusion detection system with an autonomous structuring algorithm. There is evidence that neuromorphic computation for network intrusion detection is fractal in nature under certain conditions. Specifically, the neural structure can take fractal form when simple neural structuring is autonomous. A neural structure is fractal by definition when its fractal dimension exceeds the synaptic matrix dimension. The authors introduce the use of fractal dimension of the neuromorphic structure as a factor in the autonomous restructuring feedback loop.

  1. Exploring neuronal bistability at the depolarization block.

    Directory of Open Access Journals (Sweden)

    Andrey Dovzhenok

    Full Text Available Many neurons display bistability--coexistence of two firing modes such as bursting and tonic spiking or tonic spiking and silence. Bistability has been proposed to endow neurons with richer forms of information processing in general and to be involved in short-term memory in particular by allowing a brief signal to elicit long-lasting changes in firing. In this paper, we focus on bistability that allows for a choice between tonic spiking and depolarization block in a wide range of the depolarization levels. We consider the spike-producing currents in two neurons, models of which differ by the parameter values. Our dopaminergic neuron model displays bistability in a wide range of applied currents at the depolarization block. The Hodgkin-Huxley model of the squid giant axon shows no bistability. We varied parameter values for the model to analyze transitions between the two parameter sets. We show that bistability primarily characterizes the inactivation of the Na(+ current. Our study suggests a connection between the amount of the Na(+ window current and the length of the bistability range. For the dopaminergic neuron we hypothesize that bistability can be linked to a prolonged action of antipsychotic drugs.

  2. Serendipitous Offline Learning in a Neuromorphic Robot.

    Science.gov (United States)

    Stewart, Terrence C; Kleinhans, Ashley; Mundy, Andrew; Conradt, Jörg

    2016-01-01

    We demonstrate a hybrid neuromorphic learning paradigm that learns complex sensorimotor mappings based on a small set of hard-coded reflex behaviors. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviors. All sensor data is provided via a spike-based silicon retina camera (eDVS), and all control is implemented via spiking neurons simulated on neuromorphic hardware (SpiNNaker). Given this control system, the robot is capable of simple obstacle avoidance and random exploration. To train the robot to perform more complex tasks, we observe the robot and find instances where the robot accidentally performs the desired action. Data recorded from the robot during these times is then used to update the neural control system, increasing the likelihood of the robot performing that task in the future, given a similar sensor state. As an example application of this general-purpose method of training, we demonstrate the robot learning to respond to novel sensory stimuli (a mirror) by turning right if it is present at an intersection, and otherwise turning left. In general, this system can learn arbitrary relations between sensory input and motor behavior.

  3. NUMERICAL SIMULATION OF DIGITAL VLSI TOTAL DOSE FUNCTIONAL FAILURES

    Directory of Open Access Journals (Sweden)

    O. A. Kalashnikov

    2016-10-01

    Full Text Available The technique for numerical simulation of digital VLSI total dose failures is presented, based on fuzzy logic sets theory. It assumes transfer from boolean logic model of a VLSI with values {0,1} to fuzzy model with continuous interval [0,1], and from boolean logic functions to continuous minimax functions. The technique is realized as a calculation system and allows effective estimating of digital VLSI radiation behavior without experimental investigation.

  4. VLSI 'smart' I/O module development

    Science.gov (United States)

    Kirk, Dan

    The developmental history, design, and operation of the MIL-STD-1553A/B discrete and serial module (DSM) for the U.S. Navy AN/AYK-14(V) avionics computer are described and illustrated with diagrams. The ongoing preplanned product improvement for the AN/AYK-14(V) includes five dual-redundant MIL-STD-1553 channels based on DSMs. The DSM is a front-end processor for transferring data to and from a common memory, sharing memory with a host processor to provide improved 'smart' input/output performance. Each DSM comprises three hardware sections: three VLSI-6000 semicustomized CMOS arrays, memory units to support the arrays, and buffers and resynchronization circuits. The DSM hardware module design, VLSI-6000 design tools, controlware and test software, and checkout procedures (using a hardware simulator) are characterized in detail.

  5. TECHNOLOGY MAPPING TOOL FOR VLSI CAD

    Directory of Open Access Journals (Sweden)

    D. I. Cheremisinov

    2017-01-01

    Full Text Available Technology mapping program implements a sequential circuit using the gates of a particular technology library. It is an integral component of any automated VLSI circuit design flow. The structure of the program for solving the technology mapping problem and formats of the source and result data are presented. Models of intermediate representations of the sequential circuit and their conversions are described. Technology mapping is a stage of logic synthesis and it is viewed as the transformation of a functional (i.e., algebraic circuit specification into a gate (i.e., netlist specification. The program is included as project operations in the VLSI CAD system for energy-saving logical synthesis developed in the United Institute of Informatics Problems of NAS of Belarus.

  6. Harnessing VLSI System Design with EDA Tools

    CERN Document Server

    Kamat, Rajanish K; Gaikwad, Pawan K; Guhilot, Hansraj

    2012-01-01

    This book explores various dimensions of EDA technologies for achieving different goals in VLSI system design. Although the scope of EDA is very broad and comprises diversified hardware and software tools to accomplish different phases of VLSI system design, such as design, layout, simulation, testability, prototyping and implementation, this book focuses only on demystifying the code, a.k.a. firmware development and its implementation with FPGAs. Since there are a variety of languages for system design, this book covers various issues related to VHDL, Verilog and System C synergized with EDA tools, using a variety of case studies such as testability, verification and power consumption. * Covers aspects of VHDL, Verilog and Handel C in one text; * Enables designers to judge the appropriateness of each EDA tool for relevant applications; * Omits discussion of design platforms and focuses on design case studies; * Uses design case studies from diversified application domains such as network on chip, hospital on...

  7. VLSI Microsystem for Rapid Bioinformatic Pattern Recognition

    Science.gov (United States)

    Fang, Wai-Chi; Lue, Jaw-Chyng

    2009-01-01

    A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).

  8. VLSI Architectures For Syntactic Image Analysis

    Science.gov (United States)

    Chiang, Y. P.; Fu, K. S.

    1984-01-01

    Earley's algorithm has been commonly used for the parsing of general context-free languages and error-correcting parsing in syntactic pattern recognition. The time complexity for parsing is 0(n3). In this paper we present a parallel Earley's recognition algorithm in terms of "x*" operation. By restricting the input context-free grammar to be X-free, we are able to implement this parallel algorithm on a triangular shape VLSI array. This system has an efficient way of moving data to the right place at the right time. Simulation results show that this system can recognize a string with length n in 2n+1 system time. We also present an error-correcting recognition algorithm. The parallel error-correcting recognition algorithm has also been im-plemented on a triangular VLSI array. This array recognizes an erroneous string length n in time 2n+1 and gives the correct error count. Applications of the proposed VLSI architectures to image analysis are illus-trated by examples.

  9. A Notation for Describing Multiple Views of VLSI Circuits

    Science.gov (United States)

    1988-06-01

    leaf In the functional programming language pFP cells or abstract objects) and a set of relations among [ Sheeran 83] the behavior specification implies a...A raduate VLSI design class has employed the notation in the design of modules com- [ Sheeran 83] M. Sheeran , "jvFP - An Algebraic VLSI prising a

  10. Trends and challenges in VLSI technology scaling towards 100 nm

    NARCIS (Netherlands)

    Rusu, S.; Sachdev, M.; Svensson, C.; Nauta, Bram

    Summary form only given. Moore's Law drives VLSI technology to continuous increases in transistor densities and higher clock frequencies. This tutorial will review the trends in VLSI technology scaling in the last few years and discuss the challenges facing process and circuit engineers in the 100nm

  11. Parallel optimization algorithms and their implementation in VLSI design

    Science.gov (United States)

    Lee, G.; Feeley, J. J.

    1991-01-01

    Two new parallel optimization algorithms based on the simplex method are described. They may be executed by a SIMD parallel processor architecture and be implemented in VLSI design. Several VLSI design implementations are introduced. An application example is reported to demonstrate that the algorithms are effective.

  12. Neuromorphic Artificial Touch for Categorization of Naturalistic Textures.

    Science.gov (United States)

    Rongala, Udaya Bhaskar; Mazzoni, Alberto; Oddo, Calogero Maria

    2017-04-01

    We implemented neuromorphic artificial touch and emulated the firing behavior of mechanoreceptors by injecting the raw outputs of a biomimetic tactile sensor into an Izhikevich neuronal model. Naturalistic textures were evaluated with a passive touch protocol. The resulting neuromorphic spike trains were able to classify ten naturalistic textures ranging from textiles to glass to BioSkin, with accuracy as high as 97%. Remarkably, rather than on firing rate features calculated over the stimulation window, the highest achieved decoding performance was based on the precise spike timing of the neuromorphic output as captured by Victor Purpura distance. We also systematically varied the sliding velocity and the contact force to investigate the role of sensing conditions in categorizing the stimuli via the artificial sensory system. We found that the decoding performance based on the timing of neuromorphic spike events was robust for a broad range of sensing conditions. Being able to categorize naturalistic textures in different sensing conditions, these neurorobotic results pave the way to the use of neuromorphic tactile sensors in future real-life neuroprosthetic applications.

  13. Artwork Analysis Tools for VLSI Circuits.

    Science.gov (United States)

    1980-06-01

    derived frcm the art- work.i~nFo :.- Is zr Code DI t pecal Sculnfv CLA a uPICAT OP T0416 PA*6WM Dine Bftee AMA& -’M Artwork Analysis Tools for VLSI Circuits... code of the program and in pre-generated bit tables. The design rules thcmselves are not input directly into the checker. The rules were interpreted...circuit simulation is swich -level sintulation. In this type, transistors are modeled as switches that are either on or off. Fixed delays are a%.ociated

  14. Superconducting Optoelectronic Circuits for Neuromorphic Computing

    Science.gov (United States)

    Shainline, Jeffrey M.; Buckley, Sonia M.; Mirin, Richard P.; Nam, Sae Woo

    2017-03-01

    Neural networks have proven effective for solving many difficult computational problems, yet implementing complex neural networks in software is computationally expensive. To explore the limits of information processing, it is necessary to implement new hardware platforms with large numbers of neurons, each with a large number of connections to other neurons. Here we propose a hybrid semiconductor-superconductor hardware platform for the implementation of neural networks and large-scale neuromorphic computing. The platform combines semiconducting few-photon light-emitting diodes with superconducting-nanowire single-photon detectors to behave as spiking neurons. These processing units are connected via a network of optical waveguides, and variable weights of connection can be implemented using several approaches. The use of light as a signaling mechanism overcomes fanout and parasitic constraints on electrical signals while simultaneously introducing physical degrees of freedom which can be employed for computation. The use of supercurrents achieves the low power density (1 mW /cm2 at 20-MHz firing rate) necessary to scale to systems with enormous entropy. Estimates comparing the proposed hardware platform to a human brain show that with the same number of neurons (1 011) and 700 independent connections per neuron, the hardware presented here may achieve an order of magnitude improvement in synaptic events per second per watt.

  15. Neuromorphic Configurable Architecture for Robust Motion Estimation

    Directory of Open Access Journals (Sweden)

    Guillermo Botella

    2008-01-01

    Full Text Available The robustness of the human visual system recovering motion estimation in almost any visual situation is enviable, performing enormous calculation tasks continuously, robustly, efficiently, and effortlessly. There is obviously a great deal we can learn from our own visual system. Currently, there are several optical flow algorithms, although none of them deals efficiently with noise, illumination changes, second-order motion, occlusions, and so on. The main contribution of this work is the efficient implementation of a biologically inspired motion algorithm that borrows nature templates as inspiration in the design of architectures and makes use of a specific model of human visual motion perception: Multichannel Gradient Model (McGM. This novel customizable architecture of a neuromorphic robust optical flow can be constructed with FPGA or ASIC device using properties of the cortical motion pathway, constituting a useful framework for building future complex bioinspired systems running in real time with high computational complexity. This work includes the resource usage and performance data, and the comparison with actual systems. This hardware has many application fields like object recognition, navigation, or tracking in difficult environments due to its bioinspired and robustness properties.

  16. Neuromorphic implementations of neurobiological learning algorithms for spiking neural networks.

    Science.gov (United States)

    Walter, Florian; Röhrbein, Florian; Knoll, Alois

    2015-12-01

    The application of biologically inspired methods in design and control has a long tradition in robotics. Unlike previous approaches in this direction, the emerging field of neurorobotics not only mimics biological mechanisms at a relatively high level of abstraction but employs highly realistic simulations of actual biological nervous systems. Even today, carrying out these simulations efficiently at appropriate timescales is challenging. Neuromorphic chip designs specially tailored to this task therefore offer an interesting perspective for neurorobotics. Unlike Von Neumann CPUs, these chips cannot be simply programmed with a standard programming language. Like real brains, their functionality is determined by the structure of neural connectivity and synaptic efficacies. Enabling higher cognitive functions for neurorobotics consequently requires the application of neurobiological learning algorithms to adjust synaptic weights in a biologically plausible way. In this paper, we therefore investigate how to program neuromorphic chips by means of learning. First, we provide an overview over selected neuromorphic chip designs and analyze them in terms of neural computation, communication systems and software infrastructure. On the theoretical side, we review neurobiological learning techniques. Based on this overview, we then examine on-die implementations of these learning algorithms on the considered neuromorphic chips. A final discussion puts the findings of this work into context and highlights how neuromorphic hardware can potentially advance the field of autonomous robot systems. The paper thus gives an in-depth overview of neuromorphic implementations of basic mechanisms of synaptic plasticity which are required to realize advanced cognitive capabilities with spiking neural networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Fast neuromorphic sound localization for binaural hearing aids.

    Science.gov (United States)

    Park, Paul K J; Ryu, Hyunsurk; Lee, Jun Haeng; Shin, Chang-Woo; Lee, Kyoo Bin; Woo, Jooyeon; Kim, Jun-Seok; Kang, Byung Chang; Liu, Shih-Chii; Delbruck, Tobi

    2013-01-01

    We report on the neuromorphic sound localization circuit which can enhance the perceptual sensation in a hearing aid system. All elements are simple leaky integrate-and-fire neuron circuits with different parameters optimized to suppress the impacts of synaptic circuit noises. The detection range and resolution of the proposed neuromorphic circuit are 500 us and 5 us, respectively. Our results show that, the proposed technique can localize a sound pulse with extremely narrow duration (∼ 1 ms) resulting in real-time response.

  18. Technology computer aided design simulation for VLSI MOSFET

    CERN Document Server

    Sarkar, Chandan Kumar

    2013-01-01

    Responding to recent developments and a growing VLSI circuit manufacturing market, Technology Computer Aided Design: Simulation for VLSI MOSFET examines advanced MOSFET processes and devices through TCAD numerical simulations. The book provides a balanced summary of TCAD and MOSFET basic concepts, equations, physics, and new technologies related to TCAD and MOSFET. A firm grasp of these concepts allows for the design of better models, thus streamlining the design process, saving time and money. This book places emphasis on the importance of modeling and simulations of VLSI MOS transistors and

  19. Hybrid optoelectronic device with multiple bistable outputs

    Science.gov (United States)

    Costazo-Caso, Pablo A.; Jin, Yiye; Gelh, Michael; Granieri, Sergio; Siahmakoun, Azad

    2011-01-01

    Optoelectronic circuits which exhibit optical and electrical bistability with hysteresis behavior are proposed and experimentally demonstrated. The systems are based on semiconductor optical amplifiers (SOA), bipolar junction transistors (BJT), PIN photodiodes (PD) and laser diodes externally modulated with integrated electro-absorption modulators (LD-EAM). The device operates based on two independent phenomena leading to both electrical bistability and optical bistability. The electrical bistability is due to the series connection of two p-i-n structures (SOA, BJT, PD or LD) in reverse bias. The optical bistability is consequence of the quantum confined Stark effect (QCSE) in the multi-quantum well (MQW) structure in the intrinsic region of the device. This effect produces the optical modulation of the transmitted light through the SOA (or reflected from the PD). Finally, because the optical transmission of the SOA (in reverse bias) and the reflected light from the PD are so small, a LD-EAM modulated by the voltage across these devices are employed to obtain a higher output optical power. Experiments show that the maximum switching frequency is in MHz range and the rise/fall times lower than 1 us. The temporal response is mainly limited by the electrical capacitance of the devices and the parasitic inductances of the connecting wires. The effects of these components can be reduced in current integration technologies.

  20. Bistable soliton states and switching in doubly inhomogeneously ...

    Indian Academy of Sciences (India)

    there has been a considerable interest in bistable solitons in glass fibers (with non-Kerr properties), in connection with optical bistability and other possible applications leading to switching and logic-gate devices. In literature one distinguishes between two kinds of bistable solitons: one for which the nonlinear propagation ...

  1. A neuromorphic model of spatial lookahead planning.

    Science.gov (United States)

    Ivey, Richard; Bullock, Daniel; Grossberg, Stephen

    2011-04-01

    In order to create spatial plans in a complex and changing world, organisms need to rapidly adapt to novel configurations of obstacles that impede simple routes to goal acquisition. Some animals can mentally create successful multistep spatial plans in new visuo-spatial layouts that preclude direct, one-segment routes to goal acquisition. Lookahead multistep plans can, moreover, be fully developed before an animal executes any step in the plan. What neural computations suffice to yield preparatory multistep lookahead plans during spatial cognition of an obstructed two-dimensional scene? To address this question, we introduce a novel neuromorphic system for spatial lookahead planning in which a feasible sequence of actions is prepared before movement begins. The proposed system combines neurobiologically plausible mechanisms of recurrent shunting competitive networks, visuo-spatial diffusion, and inhibition-of-return. These processes iteratively prepare a multistep trajectory to the desired goal state in the presence of obstacles. The planned trajectory can be stored using a primacy gradient in a sequential working memory and enacted by a competitive queuing process. The proposed planning system is compared with prior planning models. Simulation results demonstrate system robustness to environmental variations. Notably, the model copes with many configurations of obstacles that lead other visuo-spatial planning models into selecting undesirable or infeasible routes. Our proposal is inspired by mechanisms of spatial attention and planning in primates. Accordingly, our simulation results are compared with neurophysiological and behavioral findings from relevant studies of spatial lookahead behavior. Copyright © 2010 Elsevier Ltd. All rights reserved.

  2. A Neuromorphic System for Video Object Recognition

    Directory of Open Access Journals (Sweden)

    Deepak eKhosla

    2014-11-01

    Full Text Available Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS, is inspired by recent findings in computational neuroscience on feed-forward object detection and classification pipelines for processing and extracting relevant information from visual data. The NEOVUS architecture is inspired by the ventral (what and dorsal (where streams of the mammalian visual pathway and combines retinal processing, form-based and motion-based object detection, and convolutional neural nets based object classification. Our system was evaluated by the Defense Advanced Research Projects Agency (DARPA under the NEOVISION2 program on a variety of urban area video datasets collected from both stationary and moving platforms. The datasets are challenging as they include a large number of targets in cluttered scenes with varying illumination and occlusion conditions. The NEOVUS system was also mapped to commercially available off-the-shelf hardware. The dynamic power requirement for the system that includes a 5.6Mpixel retinal camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W, for an effective energy consumption of 5.4 nanoJoules (nJ per bit of incoming video. In a systematic evaluation of five different teams by DARPA on three aerial datasets, the NEOVUS demonstrated the best performance with the highest recognition accuracy and at least three orders of magnitude lower energy consumption than two independent state of the art computer vision systems. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition towards enabling practical low-power and mobile video processing applications.

  3. Neuromechanistic Model of Auditory Bistability.

    Directory of Open Access Journals (Sweden)

    James Rankin

    2015-11-01

    Full Text Available Sequences of higher frequency A and lower frequency B tones repeating in an ABA- triplet pattern are widely used to study auditory streaming. One may experience either an integrated percept, a single ABA-ABA- stream, or a segregated percept, separate but simultaneous streams A-A-A-A- and -B---B--. During minutes-long presentations, subjects may report irregular alternations between these interpretations. We combine neuromechanistic modeling and psychoacoustic experiments to study these persistent alternations and to characterize the effects of manipulating stimulus parameters. Unlike many phenomenological models with abstract, percept-specific competition and fixed inputs, our network model comprises neuronal units with sensory feature dependent inputs that mimic the pulsatile-like A1 responses to tones in the ABA- triplets. It embodies a neuronal computation for percept competition thought to occur beyond primary auditory cortex (A1. Mutual inhibition, adaptation and noise are implemented. We include slow NDMA recurrent excitation for local temporal memory that enables linkage across sound gaps from one triplet to the next. Percepts in our model are identified in the firing patterns of the neuronal units. We predict with the model that manipulations of the frequency difference between tones A and B should affect the dominance durations of the stronger percept, the one dominant a larger fraction of time, more than those of the weaker percept-a property that has been previously established and generalized across several visual bistable paradigms. We confirm the qualitative prediction with our psychoacoustic experiments and use the behavioral data to further constrain and improve the model, achieving quantitative agreement between experimental and modeling results. Our work and model provide a platform that can be extended to consider other stimulus conditions, including the effects of context and volition.

  4. Bistable Topological Insulator with Exciton-Polaritons

    Science.gov (United States)

    Kartashov, Yaroslav V.; Skryabin, Dmitry V.

    2017-12-01

    The functionality of many nonlinear and quantum optical devices relies on the effect of optical bistability. Using microcavity exciton-polaritons in a honeycomb arrangement of microcavity pillars, we report the resonance response and bistability of topological edge states. A balance between the pump, loss, and nonlinearity ensures a broad range of dynamical stability and controls the distribution of power between counterpropagating states on the opposite edges of the honeycomb lattice stripe. Tuning energy and polarization of the pump photons, while keeping their momentum constant, we demonstrate control of the propagation direction of the dominant edge state. Our results facilitate the development of practical applications of topological photonics.

  5. Benchmarking Neuromorphic Vision: Lessons Learnt from Computer Vision

    Directory of Open Access Journals (Sweden)

    Cheston eTan

    2015-10-01

    Full Text Available Neuromorphic Vision sensors have improved greatly since the first silicon retina was presented almost three decades ago. They have recently matured to the point where they are commercially available and can be operated by laymen. However, despite improved availability of sensors, there remains a lack of good datasets, and algorithms for processing spike-based visual data are still in their infancy. On the other hand, frame-based computer vision algorithms are far more mature, thanks in part to widely accepted datasets which allow direct comparison between algorithms and encourage competition. We are presented with a unique opportunity to shape the development of Neuromorphic Vision benchmarks and challenges by leveraging what has been learnt from the use of datasets in frame-based computer vision. Taking advantage of this opportunity, in this paper we review the role that benchmarks and challenges have played in the advancement of frame-based computer vision, and suggest guidelines for the creation of Neuromorphic Vision benchmarks and challenges. We also discuss the unique challenges faced when benchmarking Neuromorphic Vision algorithms, particularly when attempting to provide direct comparison with frame-based computer vision.

  6. Recent Advances on Neuromorphic Systems Using Phase-Change Materials

    Science.gov (United States)

    Wang, Lei; Lu, Shu-Ren; Wen, Jing

    2017-05-01

    Realization of brain-like computer has always been human's ultimate dream. Today, the possibility of having this dream come true has been significantly boosted due to the advent of several emerging non-volatile memory devices. Within these innovative technologies, phase-change memory device has been commonly regarded as the most promising candidate to imitate the biological brain, owing to its excellent scalability, fast switching speed, and low energy consumption. In this context, a detailed review concerning the physical principles of the neuromorphic circuit using phase-change materials as well as a comprehensive introduction of the currently available phase-change neuromorphic prototypes becomes imperative for scientists to continuously progress the technology of artificial neural networks. In this paper, we first present the biological mechanism of human brain, followed by a brief discussion about physical properties of phase-change materials that recently receive a widespread application on non-volatile memory field. We then survey recent research on different types of neuromorphic circuits using phase-change materials in terms of their respective geometrical architecture and physical schemes to reproduce the biological events of human brain, in particular for spike-time-dependent plasticity. The relevant virtues and limitations of these devices are also evaluated. Finally, the future prospect of the neuromorphic circuit based on phase-change technologies is envisioned.

  7. Thermal Expansion and Aging Effects in Neuromorphic Signal Processor

    NARCIS (Netherlands)

    Zjajo, A.; van Leuken, T.G.R.M.

    2016-01-01

    In this paper, we propose an efficient methodology based on a real-time estimator and predictor-corrector scheme for accurate thermal expansion profile and aging evaluation of a neuromorphic signal processor circuit components. As the experimental results indicate, for comparable mesh size, the

  8. Benchmarking neuromorphic vision: lessons learnt from computer vision.

    Science.gov (United States)

    Tan, Cheston; Lallee, Stephane; Orchard, Garrick

    2015-01-01

    Neuromorphic Vision sensors have improved greatly since the first silicon retina was presented almost three decades ago. They have recently matured to the point where they are commercially available and can be operated by laymen. However, despite improved availability of sensors, there remains a lack of good datasets, while algorithms for processing spike-based visual data are still in their infancy. On the other hand, frame-based computer vision algorithms are far more mature, thanks in part to widely accepted datasets which allow direct comparison between algorithms and encourage competition. We are presented with a unique opportunity to shape the development of Neuromorphic Vision benchmarks and challenges by leveraging what has been learnt from the use of datasets in frame-based computer vision. Taking advantage of this opportunity, in this paper we review the role that benchmarks and challenges have played in the advancement of frame-based computer vision, and suggest guidelines for the creation of Neuromorphic Vision benchmarks and challenges. We also discuss the unique challenges faced when benchmarking Neuromorphic Vision algorithms, particularly when attempting to provide direct comparison with frame-based computer vision.

  9. ORGANIZATION OF GRAPHIC INFORMATION FOR VIEWING THE MULTILAYER VLSI TOPOLOGY

    Directory of Open Access Journals (Sweden)

    V. I. Romanov

    2016-01-01

    Full Text Available One of the possible ways to reorganize of graphical information describing the set of topology layers of modern VLSI. The method is directed on the use in the conditions of the bounded size of video card memory. An additional effect, providing high performance of forming multi- image layout a multi-layer topology of modern VLSI, is achieved by preloading the required texture by means of auxiliary background process.

  10. Memory Based Machine Intelligence Techniques in VLSI hardware

    OpenAIRE

    James, Alex Pappachen

    2012-01-01

    We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...

  11. Delay dynamics of neuromorphic optoelectronic nanoscale resonators: Perspectives and applications

    Science.gov (United States)

    Romeira, Bruno; Figueiredo, José M. L.; Javaloyes, Julien

    2017-11-01

    With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the implementation of AI systems using computer algorithms of neural networks is emerging rapidly, scientists are just taking the very first steps in the development of the hardware elements of an artificial brain, specifically neuromorphic microchips. In this review article, we present the current state of the art of neuromorphic photonic circuits based on solid-state optoelectronic oscillators formed by nanoscale double barrier quantum well resonant tunneling diodes. We address, both experimentally and theoretically, the key dynamic properties of recently developed artificial solid-state neuron microchips with delayed perturbations and describe their role in the study of neural activity and regenerative memory. This review covers our recent research work on excitable and delay dynamic characteristics of both single and autaptic (delayed) artificial neurons including all-or-none response, spike-based data encoding, storage, signal regeneration and signal healing. Furthermore, the neural responses of these neuromorphic microchips display all the signatures of extended spatio-temporal localized structures (LSs) of light, which are reviewed here in detail. By taking advantage of the dissipative nature of LSs, we demonstrate potential applications in optical data reconfiguration and clock and timing at high-speeds and with short transients. The results reviewed in this article are a key enabler for the development of high-performance optoelectronic devices in future high-speed brain-inspired optical memories and neuromorphic computing.

  12. Multi-net optimization of VLSI interconnect

    CERN Document Server

    Moiseev, Konstantin; Wimer, Shmuel

    2015-01-01

    This book covers layout design and layout migration methodologies for optimizing multi-net wire structures in advanced VLSI interconnects. Scaling-dependent models for interconnect power, interconnect delay and crosstalk noise are covered in depth, and several design optimization problems are addressed, such as minimization of interconnect power under delay constraints, or design for minimal delay in wire bundles within a given routing area. A handy reference or a guide for design methodologies and layout automation techniques, this book provides a foundation for physical design challenges of interconnect in advanced integrated circuits.  • Describes the evolution of interconnect scaling and provides new techniques for layout migration and optimization, focusing on multi-net optimization; • Presents research results that provide a level of design optimization which does not exist in commercially-available design automation software tools; • Includes mathematical properties and conditions for optimal...

  13. VLSI Design of Trusted Virtual Sensors

    Directory of Open Access Journals (Sweden)

    Macarena C. Martínez-Rodríguez

    2018-01-01

    Full Text Available This work presents a Very Large Scale Integration (VLSI design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption. The sensed variable is estimated by a virtual sensor based on a configurable and programmable PieceWise-Affine hyper-Rectangular (PWAR model. An algorithm is presented to find the best values of the programmable parameters given a set of (empirical or simulated input-output data. The VLSI design of the trusted virtual sensor uses the fast authenticated encryption algorithm, AEGIS, to ensure the integrity of the provided virtual measurement and to encrypt it, and a Physical Unclonable Function (PUF based on a Static Random Access Memory (SRAM to ensure the integrity of the sensor itself. Implementation results of a prototype designed in a 90-nm Complementary Metal Oxide Semiconductor (CMOS technology show that the active silicon area of the trusted virtual sensor is 0.86 mm 2 and its power consumption when trusted sensing at 50 MHz is 7.12 mW. The maximum operation frequency is 85 MHz, which allows response times lower than 0.25 μ s. As application example, the designed prototype was programmed to estimate the yaw rate in a vehicle, obtaining root mean square errors lower than 1.1%. Experimental results of the employed PUF show the robustness of the trusted sensing against aging and variations of the operation conditions, namely, temperature and power supply voltage (final value as well as ramp-up time.

  14. Organic bistable light-emitting devices

    Science.gov (United States)

    Ma, Liping; Liu, Jie; Pyo, Seungmoon; Yang, Yang

    2002-01-01

    An organic bistable device, with a unique trilayer structure consisting of organic/metal/organic sandwiched between two outmost metal electrodes, has been invented. [Y. Yang, L. P. Ma, and J. Liu, U.S. Patent Pending, U.S. 01/17206 (2001)]. When the device is biased with voltages beyond a critical value (for example 3 V), the device suddenly switches from a high-impedance state to a low-impedance state, with a difference in injection current of more than 6 orders of magnitude. When the device is switched to the low-impedance state, it remains in that state even when the power is off. (This is called "nonvolatile" phenomenon in memory devices.) The high-impedance state can be recovered by applying a reverse bias; therefore, this bistable device is ideal for memory applications. In order to increase the data read-out rate of this type of memory device, a regular polymer light-emitting diode has been integrated with the organic bistable device, such that it can be read out optically. These features make the organic bistable light-emitting device a promising candidate for several applications, such as digital memories, opto-electronic books, and recordable papers.

  15. Lattice stretching bistability and dynamic heterogeneity

    DEFF Research Database (Denmark)

    Christiansen, Peter Leth; Savin, A. V.; Zolotaryuk, A. V.

    2012-01-01

    between the bistable ground states. However, the key point of the model is the appearance of a heterogenous structure, when the second-neighbor coupling is sufficiently weak. In this case, a part of the chain has short bonds with a single-well potential, whereas the complementary part admits strongly...

  16. Neuromorphic elements and systems as the basis for the physical implementation of artificial intelligence technologies

    Science.gov (United States)

    Demin, V. A.; Emelyanov, A. V.; Lapkin, D. A.; Erokhin, V. V.; Kashkarov, P. K.; Kovalchuk, M. V.

    2016-11-01

    The instrumental realization of neuromorphic systems may form the basis of a radically new social and economic setup, redistributing roles between humans and complex technical aggregates. The basic elements of any neuromorphic system are neurons and synapses. New memristive elements based on both organic (polymer) and inorganic materials have been formed, and the possibilities of instrumental implementation of very simple neuromorphic systems with different architectures on the basis of these elements have been demonstrated.

  17. Six Networks on a Universal Neuromorphic Computing Substrate

    Science.gov (United States)

    Pfeil, Thomas; Grübl, Andreas; Jeltsch, Sebastian; Müller, Eric; Müller, Paul; Petrovici, Mihai A.; Schmuker, Michael; Brüderle, Daniel; Schemmel, Johannes; Meier, Karlheinz

    2013-01-01

    In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality. PMID:23423583

  18. Towards neuromorphic electronics: Memristors on foldable silicon fabric

    KAUST Repository

    Ghoneim, Mohamed T.

    2014-11-01

    The advantages associated with neuromorphic computation are rich areas of complex research. We address the fabrication challenge of building neuromorphic devices on structurally foldable platform with high integration density. We present a CMOS compatible fabrication process to demonstrate for the first time memristive devices fabricated on bulk monocrystalline silicon (100) which is next transformed into a flexible thin sheet of silicon fabric with all the pre-fabricated devices. This process preserves the ultra-high integration density advantage unachievable on other flexible substrates. In addition, the memristive devices are of the size of a motor neuron and the flexible/folded architectural form factor is critical to match brain cortex\\'s folded pattern for ultra-compact design.

  19. Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware

    Directory of Open Access Journals (Sweden)

    Andreas Stöckel

    2017-08-01

    Full Text Available Large-scale neuromorphic hardware platforms, specialized computer systems for energy efficient simulation of spiking neural networks, are being developed around the world, for example as part of the European Human Brain Project (HBP. Due to conceptual differences, a universal performance analysis of these systems in terms of runtime, accuracy and energy efficiency is non-trivial, yet indispensable for further hard- and software development. In this paper we describe a scalable benchmark based on a spiking neural network implementation of the binary neural associative memory. We treat neuromorphic hardware and software simulators as black-boxes and execute exactly the same network description across all devices. Experiments on the HBP platforms under varying configurations of the associative memory show that the presented method allows to test the quality of the neuron model implementation, and to explain significant deviations from the expected reference output.

  20. Qualitative Functional Decomposition Analysis of Evolved Neuromorphic Flight Controllers

    Directory of Open Access Journals (Sweden)

    Sanjay K. Boddhu

    2012-01-01

    Full Text Available In the previous work, it was demonstrated that one can effectively employ CTRNN-EH (a neuromorphic variant of EH method methodology to evolve neuromorphic flight controllers for a flapping wing robot. This paper describes a novel frequency grouping-based analysis technique, developed to qualitatively decompose the evolved controllers into explainable functional control blocks. A summary of the previous work related to evolving flight controllers for two categories of the controller types, called autonomous and nonautonomous controllers, is provided, and the applicability of the newly developed decomposition analysis for both controller categories is demonstrated. Further, the paper concludes with appropriate discussion of ongoing work and implications for possible future work related to employing the CTRNN-EH methodology and the decomposition analysis techniques presented in this paper.

  1. Thermal memristor and neuromorphic networks for manipulating heat flow

    Science.gov (United States)

    Ben-Abdallah, Philippe

    2017-06-01

    A memristor is one of four fundamental two-terminal solid elements in electronics. In addition with the resistor, the capacitor and the inductor, this passive element relates the electric charges to current in solid state elements. Here we report the existence of a thermal analog for this element made with metal-insulator transition materials. We demonstrate that these memristive systems can be used to create thermal neurons opening so the way to neuromorphic networks for smart thermal management and information treatment.

  2. A CAD System for Exploring Neuromorphic Computing with Emerging Technologies

    Science.gov (United States)

    2017-03-01

    Our continued research agenda includes richer applications, including aircraft control and speech recognition , improved evolutionary optimization...phoneme recognition on audio feeds. 
 • A general classification application to make classification decisions on data sets by using pre...Zarella, “TrueHappiness: Neuromorphic Emotion Recognition on TrueNorth,” arXiv:1601- .04183, 2016. 
 9. S. K. Esser et al, “Convolutional Networks for

  3. An improved cortex-like neuromorphic system for target recognitions

    Science.gov (United States)

    Tsitiridis, Aristeidis; Yuen, Peter; Hong, Kan; Chen, Tong; Ibrahim, Izzati; Jackman, James; James, David; Richardson, Mark

    2010-10-01

    This paper reports on the enhancement of biologically-inspired machine vision through a rotation invariance mechanism. Research over the years has suggested that rotation invariance is one of the fundamental generic elements of object constancy, a known generic visual ability of the human brain. Cortex-like vision unlike conventional pixel based machine vision is achieved by mimicking neuromorphic mechanisms of the primates' brain. In this preliminary study, rotation invariance is implemented through histograms from Gabor features of an object. The performance of rotation invariance in the neuromorphic algorithm is assessed by the classification accuracies of a test data set which consists of image objects in five different orientations. It is found that a much more consistent classification result over these five different oriented data sets has been achieved by the integrated rotation invariance neuromorphic algorithm compared to the one without. In addition, the issue of varying aspect ratios of input images to these models is also addressed, in an attempt to create a robust algorithm against a wider variability of input data. The extension of the present achievement is to improve the recognition accuracies while incorporating it to a series of different real-world scenarios which would challenge the approach accordingly.

  4. A neuromorphic system for object detection and classification

    Science.gov (United States)

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam; Cheng, Shinko Y.; Honda, Alexander L.; Zhang, Lei

    2013-05-01

    Unattended object detection, recognition and tracking on unmanned reconnaissance platforms in battlefields and urban spaces are topics of emerging importance. In this paper, we present an unattended object recognition system that automatically detects objects of interest in videos and classifies them into various categories (e.g., person, car, truck, etc.). Our system is inspired by recent findings in visual neuroscience on feed-forward object detection and recognition pipeline and mirrors that via two main neuromorphic modules (1) A front-end detection module that combines form and motion based visual attention to search for and detect "integrated" object percepts as is hypothesized to occur in the human visual pathways; (2) A back-end recognition module that processes only the detected object percepts through a neuromorphic object classification algorithm based on multi-scale convolutional neural networks, which can be efficiently implemented in COTS hardware. Our neuromorphic system was evaluated using a variety of urban area video data collected from both stationary and moving platforms. The data are quite challenging as it includes targets at long ranges, occurring under variable conditions of illuminations and occlusion with high clutter. The experimental results of our system showed excellent detection and classification performance. In addition, the proposed bio-inspired approach is good for hardware implementation due to its low complexity and mapping to off-the-shelf conventional hardware.

  5. Demonstrating Hybrid Learning in a Flexible Neuromorphic Hardware System.

    Science.gov (United States)

    Friedmann, Simon; Schemmel, Johannes; Grubl, Andreas; Hartel, Andreas; Hock, Matthias; Meier, Karlheinz

    2017-02-01

    We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high efficiency associated with neuromorphic implementations, we combine a general-purpose processor with full-custom analog elements. This processor is operating in parallel with a fully parallel neuromorphic system consisting of an array of synapses connected to analog, continuous time neuron circuits. Novel analog correlation sensor circuits process spike events for each synapse in parallel and in real-time. The processor uses this pre-processing to compute new weights possibly using additional information following its program. Therefore, to a certain extent, learning rules can be defined in software giving a large degree of flexibility. Synapses realize correlation detection geared towards Spike-Timing Dependent Plasticity (STDP) as central computational primitive in the analog domain. Operating at a speed-up factor of 1000 compared to biological time-scale, we measure time-constants from tens to hundreds of micro-seconds. We analyze variability across multiple chips and demonstrate learning using a multiplicative STDP rule. We conclude that the presented approach will enable flexible and efficient learning as a platform for neuroscientific research and technological applications.

  6. VLSI digital demodulator co-processor

    Science.gov (United States)

    Stephen, Karen J.; Buznitsky, Mitchell A.; Lindsey, Mark J.

    A demodulation coprocessor that incorporates into a single VLSI package a number of important arithmetic functions commonly encountered in demodulation processing is developed. The LD17 demodulator is designed for use in a digital modem as a companion to any of the commercially available digital signal processing (DSP) microprocessors. The LD17 includes an 8-b complex multiplier-accumulator (MAC), a programmable tone generator, a preintegrator, a dedicated noncoherent differential phase-shift keying (DPSK) calculator, and a program/data sequencer. By using a simple generic interface and small but powerful instruction set, the LD17 has the capability to operate in several architectural schemes with a minimum of glue logic. Speed, size, and power constraints will dictate which of these schemes is best for a particular application. The LD17 will be implemented in a 1.5-micron DLM CMOS gate array and packaged in an 84-pin JLCC. With the LD17 and its memory, the real-time processing compatibility of a typical DSP microprocessor can be extended to sampling rates from hundreds to thousands of kilosamples per second.

  7. Multilevel VLSI interconnection—an optimum approach?

    Science.gov (United States)

    Srikrishnan, K. V.; Totta, P. A.

    1986-04-01

    The wirability of circuit elements is a key ingredient in the success of the very large scale integration technology. Multilevel wiring eliminates the need to use extensive areas of the silicon surface simply for wiring channels. Increasing the number of wiring planes significantly improves the possibility of achieving the goals of the VLSI, i.e. the interconnection of the maximum number of devices in the smallest possible area. Extensive modeling has shown the need to optimize the wiring pitch, number of wiring planes and electrical properties of the materials used (e.g-low resistivity for conductors and low dielectric constant for insulators). The choice of the interconnection technology is also influenced by other factors. Some of these areas: cost and reliability objectives; in house expertise and practice; new process/equipment availability and a desire to maintain process commonality. The selected strategy is sometimes an optimum approach for an individual situation which is not universally optimum. In IBM, for example, two different but successful multilevel wiring technologies are being used extensively. The first is used for bipolar circuits; it is a three-level metallization design, with sputtered SiO2 as the insulator. The second, for FET devices, has two-levels of metal and polyimide as the insulator. Both technologies use area array input/output terminal connections and lift off line definition. The process/material set of each is reviewed to emphasize the mechanics of reaching an ``optimum'' solution for the individual applications.

  8. Dynamo efficiency controlled by hydrodynamic bistability.

    Science.gov (United States)

    Miralles, Sophie; Herault, Johann; Herault, Johann; Fauve, Stephan; Gissinger, Christophe; Pétrélis, François; Daviaud, François; Dubrulle, Bérengère; Boisson, Jean; Bourgoin, Mickaël; Verhille, Gautier; Odier, Philippe; Pinton, Jean-François; Plihon, Nicolas

    2014-06-01

    Hydrodynamic and magnetic behaviors in a modified experimental setup of the von Kármán sodium flow-where one disk has been replaced by a propeller-are investigated. When the rotation frequencies of the disk and the propeller are different, we show that the fully turbulent hydrodynamic flow undergoes a global bifurcation between two configurations. The bistability of these flow configurations is associated with the dynamics of the central shear layer. The bistable flows are shown to have different dynamo efficiencies; thus for a given rotation rate of the soft-iron disk, two distinct magnetic behaviors are observed depending on the flow configuration. The hydrodynamic transition controls the magnetic field behavior, and bifurcations between high and low magnetic field branches are investigated.

  9. Statistical Performance Analysis and Modeling Techniques for Nanometer VLSI Designs

    CERN Document Server

    Shen, Ruijing; Yu, Hao

    2012-01-01

    Since process variation and chip performance uncertainties have become more pronounced as technologies scale down into the nanometer regime, accurate and efficient modeling or characterization of variations from the device to the architecture level have  become imperative for the successful design of VLSI chips. This book provides readers with tools for variation-aware design methodologies and computer-aided design (CAD) of VLSI systems, in the presence of process variations at the nanometer scale. It presents the latest developments for modeling and analysis, with a focus on statistical interconnect modeling, statistical parasitic extractions, statistical full-chip leakage and dynamic power analysis considering spatial correlations, statistical analysis and modeling for large global interconnects and analog/mixed-signal circuits.  Provides readers with timely, systematic and comprehensive treatments of statistical modeling and analysis of VLSI systems with a focus on interconnects, on-chip power grids and ...

  10. Bistability driven by dichotomous noise: A comment

    Energy Technology Data Exchange (ETDEWEB)

    Porra, J.M.; Masoliver, J. (Departament de Fisica Fonamental, Universitat de Barcelona, Diagonal 647, 08028 Barcelona (Spain)); Lindenberg, K. (Department of Chemistry 0340, University of California, San Diego, La Jolla, California 92093 (United States) Institute for Nonlinear Science 0402, University of California, San Diego, La Jolla, California 92093 (United States)); L' Heureux, I. (Department of Physics, University of Ottawa, Ottawa, Ontario, K1N6N5 (Canada)); Kapral, R. (Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario, M5S1A1 (Canada))

    1992-04-15

    Two recently reported treatments (J. M. Porra {ital et} {ital al}., Phys. Rev. A 44, 4866 (1991) and I. L'Heureux and R. Kapral, J. Chem. Phys. 88, 7468 (1988)) of the problem of bistability driven by dichotomous colored noise with a small correlation time are brought into agreement with each other and with the exact numerical results of L'Heureux and Kapral (J. Chem. Phys. 90, 2453 (1989)).

  11. Collective Motion: Bistability and Trajectory Tracking

    OpenAIRE

    Paley, Derek; Leonard, Naomi; Sepulchre, Rodolphe

    2004-01-01

    This paper presents analysis and application of steering control laws for a network of self-propelled, planar particles. We explore together the two stably controlled group motions, parallel motion and circular motion, for modeling and design purposes. We show that a previously considered control law simultaneously stabilizes both parallel and circular group motion, leading to bistability and hysteresis. We also present behavior primitives that enable piecewise-linear ...

  12. The delicate bistability of CaMKII.

    Science.gov (United States)

    Michalski, P J

    2013-08-06

    Calcium/calmodulin-dependent protein kinase II (CaMKII) is a synaptic, autophosphorylating kinase that is essential for learning and memory. Previous models have suggested that CaMKII functions as a bistable switch that could be the molecular correlate of long-term memory, but experiments have failed to validate these predictions. These models involved significant approximations to overcome the combinatorial complexity inherent in a multisubunit, multistate system. Here, we develop a stochastic particle-based model of CaMKII activation and dynamics that overcomes combinatorial complexity without significant approximations. We report four major findings. First, the CaMKII model system is never bistable at resting calcium concentrations, which suggests that CaMKII activity does not function as the biochemical switch underlying long-term memory. Second, the steady-state activation curves are either laserlike or steplike. Both are characterized by a well-defined threshold for activation, which suggests that thresholding is a robust feature of this system. Third, transiently activated CaMKII can maintain its activity over the time course of many experiments, and such slow deactivation may account for the few reports of bistability in the literature. And fourth, under in vivo conditions, increases in phosphatase activity can increase CaMKII activity. This is a surprising and counterintuitive effect, as dephosphorylation is generally associated with CaMKII deactivation. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  13. AN ALGORITHM FOR ASSEMBLING A COMMON IMAGE OF VLSI LAYOUT

    Directory of Open Access Journals (Sweden)

    Y. Y. Lankevich

    2015-01-01

    Full Text Available We consider problem of assembling a common image of VLSI layout. Common image is composedof frames obtained by electron microscope photographing. Many frames require a lot of computation for positioning each frame inside the common image. Employing graphics processing units enables acceleration of computations. We realize algorithms and programs for assembling a common image of VLSI layout. Specificity of this work is to use abilities of CUDA to reduce computation time. Experimental results show efficiency of the proposed programs.

  14. Handbook of VLSI chip design and expert systems

    CERN Document Server

    Schwarz, A F

    1993-01-01

    Handbook of VLSI Chip Design and Expert Systems provides information pertinent to the fundamental aspects of expert systems, which provides a knowledge-based approach to problem solving. This book discusses the use of expert systems in every possible subtask of VLSI chip design as well as in the interrelations between the subtasks.Organized into nine chapters, this book begins with an overview of design automation, which can be identified as Computer-Aided Design of Circuits and Systems (CADCAS). This text then presents the progress in artificial intelligence, with emphasis on expert systems.

  15. VLSI micro- and nanophotonics science, technology, and applications

    CERN Document Server

    Lee, El-Hang; Razeghi, Manijeh; Jagadish, Chennupati

    2011-01-01

    Addressing the growing demand for larger capacity in information technology, VLSI Micro- and Nanophotonics: Science, Technology, and Applications explores issues of science and technology of micro/nano-scale photonics and integration for broad-scale and chip-scale Very Large Scale Integration photonics. This book is a game-changer in the sense that it is quite possibly the first to focus on ""VLSI Photonics"". Very little effort has been made to develop integration technologies for micro/nanoscale photonic devices and applications, so this reference is an important and necessary early-stage pe

  16. Multistability in Bistable Ferroelectric Materials toward Adaptive Applications

    NARCIS (Netherlands)

    Ghosh, Anirban; Koster, Gertjan; Rijnders, Augustinus J.H.M.

    2016-01-01

    Traditionally thermodynamically bistable ferroic materials are used for nonvolatile operations based on logic gates (e.g., in the form of field effect transistors). But, this inherent bistability in these class of materials limits their applicability for adaptive operations. Emulating biological

  17. Bubbling and bistability in two parameter discrete systems

    Indian Academy of Sciences (India)

    We present a graphical analysis of the mechanisms underlying the occurrences of bubbling sequences and bistability regions in the bifurcation scenario of a special class of one dimensional two parameter maps. The main result of the analysis is that whether it is bubbling or bistability is decided by the sign of the third ...

  18. Formal Hierarchical Multilevel Verification of Synchronous MOS VLSI Designs,

    Science.gov (United States)

    1987-11-01

    description of digital systems appear in Johnson [Johnson] (though in a much less accessible form). Other researchers, [ Sheeran , Johnson], use the same...Snepscheut, "Hot-Clock nMOS," Proc of the 1985 Chapel Hil Conference on VLSI. Henry Fuchs, Editor. Computer Science Press 1985 [ Sheeran ] Mary Sheeran

  19. Artificial immune system algorithm in VLSI circuit configuration

    Science.gov (United States)

    Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd

    2017-08-01

    In artificial intelligence, the artificial immune system is a robust bio-inspired heuristic method, extensively used in solving many constraint optimization problems, anomaly detection, and pattern recognition. This paper discusses the implementation and performance of artificial immune system (AIS) algorithm integrated with Hopfield neural networks for VLSI circuit configuration based on 3-Satisfiability problems. Specifically, we emphasized on the clonal selection technique in our binary artificial immune system algorithm. We restrict our logic construction to 3-Satisfiability (3-SAT) clauses in order to outfit with the transistor configuration in VLSI circuit. The core impetus of this research is to find an ideal hybrid model to assist in the VLSI circuit configuration. In this paper, we compared the artificial immune system (AIS) algorithm (HNN-3SATAIS) with the brute force algorithm incorporated with Hopfield neural network (HNN-3SATBF). Microsoft Visual C++ 2013 was used as a platform for training, simulating and validating the performances of the proposed network. The results depict that the HNN-3SATAIS outperformed HNN-3SATBF in terms of circuit accuracy and CPU time. Thus, HNN-3SATAIS can be used to detect an early error in the VLSI circuit design.

  20. VLSI implementation of a fairness ATM buffer system

    DEFF Research Database (Denmark)

    Nielsen, J.V.; Dittmann, Lars; Madsen, Jens Kargaard

    1996-01-01

    This paper presents a VLSI implementation of a resource allocation scheme, based on the concept of weighted fair queueing. The design can be used in asynchronous transfer mode (ATM) networks to ensure fairness and robustness. Weighted fair queueing is a scheduling and buffer management scheme...

  1. Bistability: requirements on cell-volume, protein diffusion, and thermodynamics.

    Directory of Open Access Journals (Sweden)

    Robert G Endres

    Full Text Available Bistability is considered wide-spread among bacteria and eukaryotic cells, useful, e.g., for enzyme induction, bet hedging, and epigenetic switching. However, this phenomenon has mostly been described with deterministic dynamic or well-mixed stochastic models. Here, we map known biological bistable systems onto the well-characterized biochemical Schlögl model, using analytical calculations and stochastic spatiotemporal simulations. In addition to network architecture and strong thermodynamic driving away from equilibrium, we show that bistability requires fine-tuning towards small cell volumes (or compartments and fast protein diffusion (well mixing. Bistability is thus fragile and hence may be restricted to small bacteria and eukaryotic nuclei, with switching triggered by volume changes during the cell cycle. For large volumes, single cells generally loose their ability for bistable switching and instead undergo a first-order phase transition.

  2. Bistability: requirements on cell-volume, protein diffusion, and thermodynamics.

    Science.gov (United States)

    Endres, Robert G

    2015-01-01

    Bistability is considered wide-spread among bacteria and eukaryotic cells, useful, e.g., for enzyme induction, bet hedging, and epigenetic switching. However, this phenomenon has mostly been described with deterministic dynamic or well-mixed stochastic models. Here, we map known biological bistable systems onto the well-characterized biochemical Schlögl model, using analytical calculations and stochastic spatiotemporal simulations. In addition to network architecture and strong thermodynamic driving away from equilibrium, we show that bistability requires fine-tuning towards small cell volumes (or compartments) and fast protein diffusion (well mixing). Bistability is thus fragile and hence may be restricted to small bacteria and eukaryotic nuclei, with switching triggered by volume changes during the cell cycle. For large volumes, single cells generally loose their ability for bistable switching and instead undergo a first-order phase transition.

  3. Neuromorphic Computing – From Materials Research to Systems Architecture Roundtable

    Energy Technology Data Exchange (ETDEWEB)

    Schuller, Ivan K. [Univ. of California, San Diego, CA (United States); Stevens, Rick [Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Chicago, IL (United States); Pino, Robinson [Dept. of Energy (DOE) Office of Science, Washington, DC (United States); Pechan, Michael [Dept. of Energy (DOE) Office of Science, Washington, DC (United States)

    2015-10-29

    Computation in its many forms is the engine that fuels our modern civilization. Modern computation—based on the von Neumann architecture—has allowed, until now, the development of continuous improvements, as predicted by Moore’s law. However, computation using current architectures and materials will inevitably—within the next 10 years—reach a limit because of fundamental scientific reasons. DOE convened a roundtable of experts in neuromorphic computing systems, materials science, and computer science in Washington on October 29-30, 2015 to address the following basic questions: Can brain-like (“neuromorphic”) computing devices based on new material concepts and systems be developed to dramatically outperform conventional CMOS based technology? If so, what are the basic research challenges for materials sicence and computing? The overarching answer that emerged was: The development of novel functional materials and devices incorporated into unique architectures will allow a revolutionary technological leap toward the implementation of a fully “neuromorphic” computer. To address this challenge, the following issues were considered: The main differences between neuromorphic and conventional computing as related to: signaling models, timing/clock, non-volatile memory, architecture, fault tolerance, integrated memory and compute, noise tolerance, analog vs. digital, and in situ learning New neuromorphic architectures needed to: produce lower energy consumption, potential novel nanostructured materials, and enhanced computation Device and materials properties needed to implement functions such as: hysteresis, stability, and fault tolerance Comparisons of different implementations: spin torque, memristors, resistive switching, phase change, and optical schemes for enhanced breakthroughs in performance, cost, fault tolerance, and/or manufacturability.

  4. A hierarchical stochastic model for bistable perception.

    Directory of Open Access Journals (Sweden)

    Stefan Albert

    2017-11-01

    Full Text Available Viewing of ambiguous stimuli can lead to bistable perception alternating between the possible percepts. During continuous presentation of ambiguous stimuli, percept changes occur as single events, whereas during intermittent presentation of ambiguous stimuli, percept changes occur at more or less regular intervals either as single events or bursts. Response patterns can be highly variable and have been reported to show systematic differences between patients with schizophrenia and healthy controls. Existing models of bistable perception often use detailed assumptions and large parameter sets which make parameter estimation challenging. Here we propose a parsimonious stochastic model that provides a link between empirical data analysis of the observed response patterns and detailed models of underlying neuronal processes. Firstly, we use a Hidden Markov Model (HMM for the times between percept changes, which assumes one single state in continuous presentation and a stable and an unstable state in intermittent presentation. The HMM captures the observed differences between patients with schizophrenia and healthy controls, but remains descriptive. Therefore, we secondly propose a hierarchical Brownian model (HBM, which produces similar response patterns but also provides a relation to potential underlying mechanisms. The main idea is that neuronal activity is described as an activity difference between two competing neuronal populations reflected in Brownian motions with drift. This differential activity generates switching between the two conflicting percepts and between stable and unstable states with similar mechanisms on different neuronal levels. With only a small number of parameters, the HBM can be fitted closely to a high variety of response patterns and captures group differences between healthy controls and patients with schizophrenia. At the same time, it provides a link to mechanistic models of bistable perception, linking the group

  5. Bistability in Coupled Oscillators Exhibiting Synchronized Dynamics

    Science.gov (United States)

    Olusola, O. I.; Vincent, U. E.; Njah, A. N.; Olowofela, J. A.

    2010-05-01

    We report some new results associated with the synchronization behavior of two coupled double-well Duffing oscillators (DDOs). Some sufficient algebraic criteria for global chaos synchronization of the drive and response DDOs via linear state error feedback control are obtained by means of Lyapunov stability theory. The synchronization is achieved through a bistable state in which a periodic attractor co-exists with a chaotic attractor. Using the linear perturbation analysis, the prevalence of attractors in parameter space and the associated bifurcations are examined. Subcritical and supercritical Hopf bifurcations and abundance of Arnold tongues — a signature of mode locking phenomenon are found.

  6. Bistability in mushroom-type metamaterials

    Science.gov (United States)

    Fernandes, David E.; Silveirinha, Mário G.

    2017-07-01

    Here, we study the electromagnetic response of asymmetric mushroom-type metamaterials loaded with nonlinear elements. It is shown that near a Fano resonance, these structures may have a strong tunable, bistable, and switchable response and enable giant nonlinear effects. By using an effective medium theory and full wave simulations, it is proven that the nonlinear elements may allow the reflection and transmission coefficients to follow hysteresis loops, and to switch the metamaterial between "go" and "no-go" states similar to an ideal electromagnetic switch.

  7. Thermal memristor and neuromorphic networks for manipulating heat flow

    Directory of Open Access Journals (Sweden)

    Philippe Ben-Abdallah

    2017-06-01

    Full Text Available A memristor is one of four fundamental two-terminal solid elements in electronics. In addition with the resistor, the capacitor and the inductor, this passive element relates the electric charges to current in solid state elements. Here we report the existence of a thermal analog for this element made with metal-insulator transition materials. We demonstrate that these memristive systems can be used to create thermal neurons opening so the way to neuromorphic networks for smart thermal management and information treatment.

  8. Computational intelligence and neuromorphic computing potential for cybersecurity applications

    Science.gov (United States)

    Pino, Robinson E.; Shevenell, Michael J.; Cam, Hasan; Mouallem, Pierre; Shumaker, Justin L.; Edwards, Arthur H.

    2013-05-01

    In today's highly mobile, networked, and interconnected internet world, the flow and volume of information is overwhelming and continuously increasing. Therefore, it is believed that the next frontier in technological evolution and development will rely in our ability to develop intelligent systems that can help us process, analyze, and make-sense of information autonomously just as a well-trained and educated human expert. In computational intelligence, neuromorphic computing promises to allow for the development of computing systems able to imitate natural neurobiological processes and form the foundation for intelligent system architectures.

  9. Annealing study of a bistable cluster defect

    Energy Technology Data Exchange (ETDEWEB)

    Junkes, Alexandra, E-mail: alexandra.junkes@desy.d [Institute for Experimental Physics, University of Hamburg, 22761 Hamburg (Germany); Eckstein, Doris [Institute for Experimental Physics, University of Hamburg, 22761 Hamburg (Germany); Pintilie, Ioana [Institute for Experimental Physics, University of Hamburg, 22761 Hamburg (Germany); NIMP Bucharest-Margurele (Romania); Makarenko, Leonid F. [Belarusian State University, Minsk (Belarus); Fretwurst, Eckhart [Institute for Experimental Physics, University of Hamburg, 22761 Hamburg (Germany)

    2010-01-11

    This work deals with the influence of neutron and proton induced cluster related defects on the properties of n-type silicon detectors. Defect concentrations were obtained by means of Deep Level Transient Spectroscopy (DLTS) and Thermally Stimulated Current (TSC) technique, while the full depletion voltage and the reverse current were extracted from capacitance-voltage (C-V) and current-voltage (I-V) characteristics. The annealing behaviour of the reverse current can be correlated with the annealing of the cluster related defect levels labeled E4a and E4b by making use of their bistability. This bistability was characterised by isochronal and isothermal annealing studies and it was found that the development with increasing annealing temperature is similar to that of divacancies. This supports the assumption that E4a and E4b are vacancy related defects. In addition we observe an influence of the disordered regions on the shape and height of the DLTS or TSC signals corresponding to point defects like the vacancy-oxygen complex.

  10. Domain wall dynamics of magnetically bistable microwires

    Directory of Open Access Journals (Sweden)

    Ipatov M.

    2012-06-01

    Full Text Available We studied domain wall propagation of magnetically-bistable Fe- Co-rich microwires paying attention on effect of applied and internal stresses. We measured hysteresis loops and domain wall propagation in various magnetic Fe- Co-rich amorphous microwires with metallic nucleus diameters (from 12 □m till 22 □m using Sixtus Tonks-like experiments. Application of tensile stresses results in decreasing of domain wall velocity. We discussed magnetoelastic contribution in dynamics of domain wall propagation. We observed, that microwires with different geometries exhibit v(H dependences with different slopes. Application of stresses resulted in decrease of DW velocity, v, and DW mobility S. Quite fast DW propagation (v till 2500 m/s at H about 30 A/m has been observed in low magnetostrictive magnetically bistable Co56Fe8Ni10Si110B16 microwires. Consequently, we can assume that generally magnetoelastic energy affects DW dynamics: decreasing magnetoelastic energy, Kme, DW velocity increases.

  11. Nonlinear dynamics of bistable lattices with defects

    Science.gov (United States)

    Hwang, Myungwon; Arrieta, Andres F.

    2017-04-01

    Heterogeneity in a lattice system has gained continued attention from researchers due to its ability to support interesting localized dynamics and engineering applications. Most studies on the influence of the defects have been done in a one-dimensional monoatomic chain with both linear and nonlinear interactions. However, analysis of defect dynamics in a lattice under on-site potential is still a rare finding. Recently, extreme wave propagation has been demonstrated theoretically and experimentally on a bi-stable lattice with magnetic inter-site force, featuring quartic on-site potential. In this work, the nonlinear dynamics of introducing engineered defects in the form of mass impurities and inter-site forcing disparities on lattices of bi-stable elements are studied. We investigate the effect of the defect presence on the local wave propagation speed and identify the critical conditions that governs the stable propagation of transition waves. With the control of damping, we further observe a special satellite region, where stable transition of wave with intermediate jumps between the stable states of the local unit cell occurs.

  12. Memristor: A New Concept in Synchronization of Coupled Neuromorphic Circuits

    Directory of Open Access Journals (Sweden)

    Ch. K. Volos

    2014-10-01

    Full Text Available The existence of the memristor, as a fourth fundamental circuit element, by researchers at Hewlett Packard (HP labs in 2008, has attracted much interest since then. This occurs because the memristor opens up new functionalities in electronics and it has led to the interpretation of phenomena not only in electronic devices but also in biological systems. Furthermore, many research teams work on projects, which use memristors in neuromorphic devices to simulate learning, adaptive and spontaneous behavior while other teams on systems, which attempt to simulate the behavior of biological synapses. In this paper, the latest achievements and applications of this newly development circuit element are presented. Also, the basic features of neuromorphic circuits, in which the memristor can be used as an electrical synapse, are studied. In this direction, a flux-controlled memristor model is adopted for using as a coupling element between coupled electronic circuits, which simulate the behavior of neuron-cells. For this reason, the circuits which are chosen realize the systems of differential equations that simulate the well-known Hindmarsh-Rose and FitzHugh-Nagumo neuron models. Finally, the simulation results of the use of a memristor as an electric synapse present the effectiveness of the proposed method and many interesting dynamic phenomena concerning the behavior of coupled neuron-cells.

  13. Integration of nanoscale memristor synapses in neuromorphic computing architectures.

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Legenstein, Robert; Deligeorgis, George; Prodromakis, Themistoklis

    2013-09-27

    Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing systems, such as their extremely low-power consumption features or their ability to carry out robust and efficient computation using massively parallel arrays of limited precision, highly variable, and unreliable components. Recent developments in nano-technologies are making available extremely compact and low power, but also variable and unreliable solid-state devices that can potentially extend the offerings of availing CMOS technologies. In particular, memristors are regarded as a promising solution for modeling key features of biological synapses due to their nanoscale dimensions, their capacity to store multiple bits of information per element and the low energy required to write distinct states. In this paper, we first review the neuro- and neuromorphic computing approaches that can best exploit the properties of memristor and scale devices, and then propose a novel hybrid memristor-CMOS neuromorphic circuit which represents a radical departure from conventional neuro-computing approaches, as it uses memristors to directly emulate the biophysics and temporal dynamics of real synapses. We point out the differences between the use of memristors in conventional neuro-computing architectures and the hybrid memristor-CMOS circuit proposed, and argue how this circuit represents an ideal building block for implementing brain-inspired probabilistic computing paradigms that are robust to variability and fault tolerant by design.

  14. Generalized Reconfigurable Memristive Dynamical System (MDS for Neuromorphic Applications

    Directory of Open Access Journals (Sweden)

    Mohammad eBavandpour

    2015-11-01

    Full Text Available This study firstly presents (i a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n^2 memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS. Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN, Adaptive Exponential (AdEx integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.

  15. Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications.

    Science.gov (United States)

    Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O

    2015-01-01

    This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n (2) memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.

  16. Noise-exploitation and adaptation in neuromorphic sensors

    Science.gov (United States)

    Hindo, Thamira; Chakrabartty, Shantanu

    2012-04-01

    Even though current micro-nano fabrication technology has reached integration levels where ultra-sensitive sensors can be fabricated, the sensing performance (resolution per joule) of synthetic systems are still orders of magnitude inferior to those observed in neurobiology. For example, the filiform hairs in crickets operate at fundamental limits of noise; auditory sensors in a parasitoid fly can overcome fundamental limitations to precisely localize ultra-faint acoustic signatures. Even though many of these biological marvels have served as inspiration for different types of neuromorphic sensors, the main focus these designs have been to faithfully replicate the biological functionalities, without considering the constructive role of "noise". In man-made sensors device and sensor noise are typically considered as a nuisance, where as in neurobiology "noise" has been shown to be a computational aid that enables biology to sense and operate at fundamental limits of energy efficiency and performance. In this paper, we describe some of the important noise-exploitation and adaptation principles observed in neurobiology and how they can be systematically used for designing neuromorphic sensors. Our focus will be on two types of noise-exploitation principles, namely, (a) stochastic resonance; and (b) noise-shaping, which are unified within our previously reported framework called Σ▵ learning. As a case-study, we describe the application of Σ▵ learning for the design of a miniature acoustic source localizer whose performance matches that of its biological counterpart(Ormia Ochracea).

  17. Integration of nanoscale memristor synapses in neuromorphic computing architectures

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Legenstein, Robert; Deligeorgis, George; Prodromakis, Themistoklis

    2013-09-01

    Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing systems, such as their extremely low-power consumption features or their ability to carry out robust and efficient computation using massively parallel arrays of limited precision, highly variable, and unreliable components. Recent developments in nano-technologies are making available extremely compact and low power, but also variable and unreliable solid-state devices that can potentially extend the offerings of availing CMOS technologies. In particular, memristors are regarded as a promising solution for modeling key features of biological synapses due to their nanoscale dimensions, their capacity to store multiple bits of information per element and the low energy required to write distinct states. In this paper, we first review the neuro- and neuromorphic computing approaches that can best exploit the properties of memristor and scale devices, and then propose a novel hybrid memristor-CMOS neuromorphic circuit which represents a radical departure from conventional neuro-computing approaches, as it uses memristors to directly emulate the biophysics and temporal dynamics of real synapses. We point out the differences between the use of memristors in conventional neuro-computing architectures and the hybrid memristor-CMOS circuit proposed, and argue how this circuit represents an ideal building block for implementing brain-inspired probabilistic computing paradigms that are robust to variability and fault tolerant by design.

  18. Neuromorphic device architectures with global connectivity through electrolyte gating

    Science.gov (United States)

    Gkoupidenis, Paschalis; Koutsouras, Dimitrios A.; Malliaras, George G.

    2017-05-01

    Information processing in the brain takes place in a network of neurons that are connected with each other by an immense number of synapses. At the same time, neurons are immersed in a common electrochemical environment, and global parameters such as concentrations of various hormones regulate the overall network function. This computational paradigm of global regulation, also known as homeoplasticity, has important implications in the overall behaviour of large neural ensembles and is barely addressed in neuromorphic device architectures. Here, we demonstrate the global control of an array of organic devices based on poly(3,4ethylenedioxythiophene):poly(styrene sulf) that are immersed in an electrolyte, a behaviour that resembles homeoplasticity phenomena of the neural environment. We use this effect to produce behaviour that is reminiscent of the coupling between local activity and global oscillations in the biological neural networks. We further show that the electrolyte establishes complex connections between individual devices, and leverage these connections to implement coincidence detection. These results demonstrate that electrolyte gating offers significant advantages for the realization of networks of neuromorphic devices of higher complexity and with minimal hardwired connectivity.

  19. Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems

    Directory of Open Access Journals (Sweden)

    Emre eNeftci

    2014-01-01

    Full Text Available Restricted Boltzmann Machines (RBMs and Deep Belief Networks have been demonstrated to perform efficiently in variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The reverberating activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP carries out the weight updates in an online, asynchronous fashion.We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

  20. Stability and morphing characteristics of bistable composite laminates

    Science.gov (United States)

    Tawfik, Samer A.

    The focus of the current research is to investigate the potential of using bistable unsymmetric cross-ply laminated composites as a means for achieving structures with morphed characteristics. To this end, an investigation of the design space for laminated composites exhibiting bistable behavior is undertaken and the key parameters controlling their behavior are identified. For this purpose a nonlinear Finite Element methodology using ABAQUS(TM) code is developed to predict both the cured shapes and the stability characteristics of unsymmetric cross-ply laminates. In addition, an experimental program is developed to validate the analytically predicted results through comparison with test data. A new method is proposed for attaching piezoelectric actuators to a bistable panel in order to preserve its favorable stability characteristics as well as optimizing the actuators performance. The developed nonlinear FE methodology is extended to predict the actuation requirements of bistable panels. Actuator requirements, predicted using the nonlinear FE analysis, are found to be in agreement with the test results. The current research also explores the potential for implementing bistable panels for Uninhabited Aerial Vehicle (UAV) wing configuration. To this end, a set of bistable panels is manufactured by combining symmetric and unsymmetric balanced and unbalanced stacking sequence and their stability characteristics are predicted. A preliminary analysis of the aerodynamic characteristics of the manufactured panels is carried out and the aerodynamic benefits of manufactured bistable panel are noted.

  1. Noise-margin limitations on gallium-arsenide VLSI

    Science.gov (United States)

    Long, Stephen I.; Sundaram, Mani

    1988-01-01

    Two factors which limit the complexity of GaAs MESFET VLSI circuits are considered. Power dissipation sets an upper complexity limit for a given logic circuit implementation and thermal design. Uniformity of device characteristics and the circuit configuration determines the electrical functional yield. Projection of VLSI complexity based on these factors indicates that logic chips of 15,000 gates are feasible with the most promising static circuits if a maximum power dissipation of 5 W per chip is assumed. While lower power per gate and therefore more gates per chip can be obtained by using a popular E/D FET circuit, yields are shown to be small when practical device parameter tolerances are applied. Further improvements in materials, devices, and circuits wil be needed to extend circuit complexity to the range currently dominated by silicon.

  2. Embedded Processor Based Automatic Temperature Control of VLSI Chips

    Directory of Open Access Journals (Sweden)

    Narasimha Murthy Yayavaram

    2009-01-01

    Full Text Available This paper presents embedded processor based automatic temperature control of VLSI chips, using temperature sensor LM35 and ARM processor LPC2378. Due to the very high packing density, VLSI chips get heated very soon and if not cooled properly, the performance is very much affected. In the present work, the sensor which is kept very near proximity to the IC will sense the temperature and the speed of the fan arranged near to the IC is controlled based on the PWM signal generated by the ARM processor. A buzzer is also provided with the hardware, to indicate either the failure of the fan or overheating of the IC. The entire process is achieved by developing a suitable embedded C program.

  3. VLSI architectures for the new (T,L) algorithm

    Science.gov (United States)

    Bengough, P. A.; Simmons, S. J.

    Trellis coding techniques have seen much use in error correction codes for space and satellite applications. When long sequences of data are encoded, the number of possible paths through the trellis becomes great and a trellis search algorithm must be used to determine the path that best matches the received data sequence. The (T,L) algorithm is a new reduced complexity trellis search algorithm, applicable to data sequence estimation in digital communications, that adapts to changing channel conditions. Its simplicity and inherent parallelism suits it well for very large scale integration (VLSI) implementation. A number of alternative VLSI architectures are presented which can be used to realize this algorithm. While one uses a simple nonsorting structure, two other sorting designs based on parallel insertion and weavesorting algorithms are proposed. The area-time performance of the various architectures is compared.

  4. Trace-based post-silicon validation for VLSI circuits

    CERN Document Server

    Liu, Xiao

    2014-01-01

    This book first provides a comprehensive coverage of state-of-the-art validation solutions based on real-time signal tracing to guarantee the correctness of VLSI circuits.  The authors discuss several key challenges in post-silicon validation and provide automated solutions that are systematic and cost-effective.  A series of automatic tracing solutions and innovative design for debug (DfD) techniques are described, including techniques for trace signal selection for enhancing visibility of functional errors, a multiplexed signal tracing strategy for improving functional error detection, a tracing solution for debugging electrical errors, an interconnection fabric for increasing data bandwidth and supporting multi-core debug, an interconnection fabric design and optimization technique to increase transfer flexibility and a DfD design and associated tracing solution for improving debug efficiency and expanding tracing window. The solutions presented in this book improve the validation quality of VLSI circuit...

  5. Advanced symbolic analysis for VLSI systems methods and applications

    CERN Document Server

    Shi, Guoyong; Tlelo Cuautle, Esteban

    2014-01-01

    This book provides comprehensive coverage of the recent advances in symbolic analysis techniques for design automation of nanometer VLSI systems. The presentation is organized in parts of fundamentals, basic implementation methods and applications for VLSI design. Topics emphasized include  statistical timing and crosstalk analysis, statistical and parallel analysis, performance bound analysis and behavioral modeling for analog integrated circuits . Among the recent advances, the Binary Decision Diagram (BDD) based approaches are studied in depth. The BDD-based hierarchical symbolic analysis approaches, have essentially broken the analog circuit size barrier. In particular, this book   • Provides an overview of classical symbolic analysis methods and a comprehensive presentation on the modern  BDD-based symbolic analysis techniques; • Describes detailed implementation strategies for BDD-based algorithms, including the principles of zero-suppression, variable ordering and canonical reduction; • Int...

  6. UW/NW (University of Washington/Northwest) VLSI Consortium

    Science.gov (United States)

    1986-12-10

    structure of the described circuits. One such language is ^ FP (a variation of the Functional Programming language FP) [ Sheeran 83] that describes...86] [Lipton 82] [ Sheeran 83] [Suzuki 85] [UW/NW 84] Bamji, C, Hauck, C. and Allen, J. A Design by Example Regular Structure Generator. In 22nd...Automation Conference, pages 467-474. IEEE, 1982. Mary Sheeran . \\i.FP - An Algebraic VLSI Design Language. PhD thesis, Oxford University Computing La

  7. Using Software Technology to Specify Abstract Interfaces in VLSI Design.

    Science.gov (United States)

    1985-01-01

    and Smoliar [Fran7g], Rowson [Rows80, Gordon [Gord8lJ, Cardelli and Plotkin [Card8l1, Hafer and Parker (Hafe83I, and Sheeran [Shee84] have all suggested...Software 1, 4 (October 1984), pp. 10-26. •.’ Y .. , ;,, ..- , .. r ,- ’..-.... -. -.. ,.:.%.. -. 149 ISbeeS4I. Sheeran , M., "mFP, a Language for VLSI

  8. Design of a VLSI Decoder for Partially Structured LDPC Codes

    Directory of Open Access Journals (Sweden)

    Fabrizio Vacca

    2008-01-01

    of their parity matrix can be partitioned into two disjoint sets, namely, the structured and the random ones. For the proposed class of codes a constructive design method is provided. To assess the value of this method the constructed codes performance are presented. From these results, a novel decoding method called split decoding is introduced. Finally, to prove the effectiveness of the proposed approach a whole VLSI decoder is designed and characterized.

  9. Model for EOS caused EF screening in CMOS VLSI

    Energy Technology Data Exchange (ETDEWEB)

    Lisenker, B. [Tower Semiconductor Ltd., Migdal Haemek (Israel); Nevo, Y. [National Semiconductor Ltd., Herzlia B` (Israel)

    1995-12-31

    This paper introduced a Fault Model, capable to elucidate the sensitivity to Electrical Overstress (EOS) and Early Fault (EF) rising nature in CMOS VLSI circuit. The Model based on the general Percolation Theory applied to the CMOS technology. Early Failures screening technique employing this Model, shows strong correlation between rejected devices, EOS faults and EF rate. This technique is recommenced both as an EF screening test and a process reliability monitor.

  10. A bistable electromagnetically actuated rotary gate microvalve

    Science.gov (United States)

    Luharuka, Rajesh; Hesketh, Peter J.

    2008-03-01

    Two types of rotary gate microvalves are developed for flow modulation in microfluidic systems. These microvalves have been tested for an open flow rate of up to 100 sccm and operate under a differential pressure of 6 psig with flow modulation of up to 100. The microvalve consists of a suspended gate that rotates in the plane of the chip to regulate flow through the orifice. The gate is suspended by a novel fully compliant in-plane rotary bistable micromechanism (IPRBM) that advantageously constrains the gate in all degrees of freedom except for in-plane rotational motion. Multiple inlet/outlet orifices provide flexibility of operating the microvalve in three different flow configurations. The rotary gate microvalve is switched with an external electromagnetic actuator. The suspended gate is made of a soft magnetic material and its electromagnetic actuation is based on the operating principle of a variable-reluctance stepper motor.

  11. Engineering optical soliton bistability in colloidal media

    CERN Document Server

    Matuszewski, Michal

    2010-01-01

    We consider a mixture consisting of two species of spherical nanoparticles dispersed in a liquid medium. We show that with an appropriate choice of refractive indices and particle diameters, it is possible to observe the phenomenon of optical soliton bistability in two spatial dimensions in a broad beam power range. Previously, this possibility was ruled out in the case of a single-species colloid. As a particular example, we consider the system of hydrophilic silica particles and gas bubbles generated in the process of electrolysis in water. The interaction of two soliton beams can lead to switching of the lower branch solitons to the upper branch, and the interaction of solitons from different branches is phase independent and always repulsive.

  12. On the Selection of Bistability in Genetic Regulatory Circuits

    Science.gov (United States)

    Ghim, Cheol-Min; Almaas, Eivind

    2008-03-01

    Bistability is a defining character of switching and memory devices. Many regulatory circuits observed in cellular reaction networks contain ``bistability motifs'' that endow a cell with efficient and reliable switching between different physiological modes of operation. One of the best characterized system, the lac operon in E. coli, has been shown to display a saddle-node bifurcation when induced by nonmetabolizable lactose analogue inducers, such as isopropylthio-β-D-galactoside (IPTG) and thio-methyl-galactoside (TMG). Motivated by the absence of bifurcation in the same system with its natural inducer, lactose, we studied the conditions for bistability and rationalized its fitness effects in the light of evolution. Stochastic simulations as well as mean-field approach confirm that history-dependent behavior as well as nongenetic inheritance, being realized by bistability motifs, may be beneficial in fluctuating environments.

  13. Bistable emission of a black-body radiator

    Science.gov (United States)

    Redmond, S. M.; Rand, S. C.; Oliveira, S. L.

    2004-12-01

    Bistable black-body emission is reported from resonantly excited Er3+,Yb3+:Y2O3 nanopowders. A simple model based on thermo-optic nonlinear response in the strongly scattering random medium explains the observed behavior.

  14. Bistability, Epigenetics, and Bet-Hedging in Bacteria

    NARCIS (Netherlands)

    Veening, Jan-Willem; Smits, Wiep Klaas; Kuipers, Oscar P.

    2008-01-01

    Clonal populations of microbial cells often show a high degree of phenotypic variability under homogeneous conditions. Stochastic fluctuations in the cellular components that determine cellular states can cause two distinct subpopulations, a property called bistability Phenotypic heterogeneity can

  15. An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems

    Directory of Open Access Journals (Sweden)

    Anup Vanarse

    2017-11-01

    Full Text Available The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses.

  16. Large-Scale Analysis of Network Bistability for Human Cancers

    OpenAIRE

    Tetsuya Shiraishi; Shinako Matsuyama; Hiroaki Kitano

    2010-01-01

    Author Summary Since most disease states exhibit a certain level of resilience against therapeutic interventions, each disease state can be considered to be homeostatic to some extent. There must be one or more mechanisms that cause the gene-regulatory network to maintain a certain state, and one such mechanism is a bistable switch. In this work, bistable switch networks were constructed and their ON(upregulated)/OFF(downregulated) states were compared between human cancers and healthy contro...

  17. vPELS: An E-Learning Social Environment for VLSI Design with Content Security Using DRM

    Science.gov (United States)

    Dewan, Jahangir; Chowdhury, Morshed; Batten, Lynn

    2014-01-01

    This article provides a proposal for personal e-learning system (vPELS [where "v" stands for VLSI: very large scale integrated circuit])) architecture in the context of social network environment for VLSI Design. The main objective of vPELS is to develop individual skills on a specific subject--say, VLSI--and share resources with peers.…

  18. Advances in neuromorphic hardware exploiting emerging nanoscale devices

    CERN Document Server

    2017-01-01

    This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.

  19. Stochastic Learning in Oxide Binary Synaptic Device for Neuromorphic Computing

    Directory of Open Access Journals (Sweden)

    Shimeng eYu

    2013-10-01

    Full Text Available Hardware implementation of neuromorphic computing is attractive as a computing paradigm beyond the conventional digital computing. In this work, we show that the SET (off-to-on transition of metal oxide resistance switching memory becomes probabilistic under a weak programming condition. The switching variability of the binary synaptic device implements a stochastic learning rule. Such stochastic SET transition was statistically measured and modeled for a simulation of a winner-take-all network for competitive learning. The simulation illustrates that with such stochastic learning, the orientation classification function of input patterns can be effectively realized. The system performance metrics were compared between the conventional approach using the analog synapse and the approach in this work that employs the binary synapse utilizing the stochastic learning. The feasibility of using binary synapse in the neurormorphic computing may relax the constraints to engineer continuous multilevel intermediate states and widens the material choice for the synaptic device design.

  20. Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing

    Science.gov (United States)

    Wang, Zhongrui; Joshi, Saumil; Savel'Ev, Sergey E.; Jiang, Hao; Midya, Rivu; Lin, Peng; Hu, Miao; Ge, Ning; Strachan, John Paul; Li, Zhiyong; Wu, Qing; Barnell, Mark; Li, Geng-Lin; Xin, Huolin L.; Williams, R. Stanley; Xia, Qiangfei; Yang, J. Joshua

    2017-01-01

    The accumulation and extrusion of Ca2+ in the pre- and postsynaptic compartments play a critical role in initiating plastic changes in biological synapses. To emulate this fundamental process in electronic devices, we developed diffusive Ag-in-oxide memristors with a temporal response during and after stimulation similar to that of the synaptic Ca2+ dynamics. In situ high-resolution transmission electron microscopy and nanoparticle dynamics simulations both demonstrate that Ag atoms disperse under electrical bias and regroup spontaneously under zero bias because of interfacial energy minimization, closely resembling synaptic influx and extrusion of Ca2+, respectively. The diffusive memristor and its dynamics enable a direct emulation of both short- and long-term plasticity of biological synapses, representing an advance in hardware implementation of neuromorphic functionalities.

  1. Microfluidic Neurons, a New Way in Neuromorphic Engineering?

    Directory of Open Access Journals (Sweden)

    Timothée Levi

    2016-08-01

    Full Text Available This article describes a new way to explore neuromorphic engineering, the biomimetic artificial neuron using microfluidic techniques. This new device could replace silicon neurons and solve the issues of biocompatibility and power consumption. The biological neuron transmits electrical signals based on ion flow through their plasma membrane. Action potentials are propagated along axons and represent the fundamental electrical signals by which information are transmitted from one place to another in the nervous system. Based on this physiological behavior, we propose a microfluidic structure composed of chambers representing the intra and extracellular environments, connected by channels actuated by Quake valves. These channels are equipped with selective ion permeable membranes to mimic the exchange of chemical species found in the biological neuron. A thick polydimethylsiloxane (PDMS membrane is used to create the Quake valve membrane. Integrated electrodes are used to measure the potential difference between the intracellular and extracellular environments: the membrane potential.

  2. Las Vegas is better than determinism in VLSI and distributed computing

    DEFF Research Database (Denmark)

    Mehlhorn, Kurt; Schmidt, Erik Meineche

    1982-01-01

    In this paper we describe a new method for proving lower bounds on the complexity of VLSI - computations and more generally distributed computations. Lipton and Sedgewick observed that the crossing sequence arguments used to prove lower bounds in VLSI (or TM or distributed computing) apply to (ac...

  3. Crystal growth and evaluation of silicon for VLSI and ULSI

    CERN Document Server

    Eranna, Golla

    2014-01-01

    PrefaceAbout the AuthorIntroductionSilicon: The SemiconductorWhy Single CrystalsRevolution in Integrated Circuit Fabrication Technology and the Art of Device MiniaturizationUse of Silicon as a SemiconductorSilicon Devices for Boolean ApplicationsIntegration of Silicon Devices and the Art of Circuit MiniaturizationMOS and CMOS Devices for Digital ApplicationsLSI, VLSI, and ULSI Circuits and ApplicationsSilicon for MEMS ApplicationsSummaryReferencesSilicon: The Key Material for Integrated Circuit Fabrication TechnologyIntroductionPreparation of Raw Silicon MaterialMetallurgical-Grade SiliconPuri

  4. Formal verification an essential toolkit for modern VLSI design

    CERN Document Server

    Seligman, Erik; Kumar, M V Achutha Kiran

    2015-01-01

    Formal Verification: An Essential Toolkit for Modern VLSI Design presents practical approaches for design and validation, with hands-on advice for working engineers integrating these techniques into their work. Building on a basic knowledge of System Verilog, this book demystifies FV and presents the practical applications that are bringing it into mainstream design and validation processes at Intel and other companies. The text prepares readers to effectively introduce FV in their organization and deploy FV techniques to increase design and validation productivity. Presents formal verific

  5. VLSI architectures for modern error-correcting codes

    CERN Document Server

    Zhang, Xinmiao

    2015-01-01

    Error-correcting codes are ubiquitous. They are adopted in almost every modern digital communication and storage system, such as wireless communications, optical communications, Flash memories, computer hard drives, sensor networks, and deep-space probing. New-generation and emerging applications demand codes with better error-correcting capability. On the other hand, the design and implementation of those high-gain error-correcting codes pose many challenges. They usually involve complex mathematical computations, and mapping them directly to hardware often leads to very high complexity. VLSI

  6. Bistability behavior of thermally actuated micro-bridge

    Science.gov (United States)

    Michael, Aron; Yu, Kevin; Kwok, Chee Yee

    2005-02-01

    A multi-layered micro-bridge buckles due to residual stresses in the layers of the beam when it is released during fabrication, and the axial load due to this stress exceeds the Euler load. This residual stress renders intrinsic bi-stability behavior to the bridge. In this paper, the effect of axial, rotational stiffness, and residual moment on the buckled shape, snapping, and bi-stability of multi-layered bridge when it is thermally actuated is studied both theoretically, and experimentally. Theoretical analysis, and ANSYS finite element simulation have been carried out to investigate these effects. Deflection versus temperature plots for different axial, rotational stiffness, and residual moment are obtained. The theoretical investigations are applied to bi-morph micro-bridges of 1000um length, and 40um wide made of PECVD silicon dioxide, and epi-taxial silicon, and a tri-layer structure of Poly/SiO2/epi-silicon. The bi-layer structure is fabricated, and its buckled shape is obtained from SEM. Results show that axial, rotational stiffness, and residual moment strongly affect the buckled shape, and bi-stability of the micro-bridge. It is also shown that for thermally actuated micro-bridge, better bi-stability, and snapping characteristics can be obtained when both rotational and axial stiffnesses are reduced, and the residual moment must not exceed a certain threshold value if bi-stability is to be preserved.

  7. Bistability of mangrove forests and competition with freshwater plants

    Science.gov (United States)

    Jiang, Jiang; Fuller, Douglas O; Teh, Su Yean; Zhai, Lu; Koh, Hock Lye; DeAngelis, Donald L.; Sternberg, L.D.S.L.

    2015-01-01

    Halophytic communities such as mangrove forests and buttonwood hammocks tend to border freshwater plant communities as sharp ecotones. Most studies attribute this purely to underlying physical templates, such as groundwater salinity gradients caused by tidal flux and topography. However, a few recent studies hypothesize that self-reinforcing feedback between vegetation and vadose zone salinity are also involved and create a bistable situation in which either halophytic dominated habitat or freshwater plant communities may dominate as alternative stable states. Here, we revisit the bistability hypothesis and demonstrate the mechanisms that result in bistability. We demonstrate with remote sensing imagery the sharp boundaries between freshwater hardwood hammock communities in southern Florida and halophytic communities such as buttonwood hammocks and mangroves. We further document from the literature how transpiration of mangroves and freshwater plants respond differently to vadose zone salinity, thus altering the salinity through feedback. Using mathematical models, we show how the self-reinforcing feedback, together with physical template, controls the ecotones between halophytic and freshwater communities. Regions of bistability along environmental gradients of salinity have the potential for large-scale vegetation shifts following pulse disturbances such as hurricane tidal surges in Florida, or tsunamis in other regions. The size of the region of bistability can be large for low-lying coastal habitat due to the saline water table, which extends inland due to salinity intrusion. We suggest coupling ecological and hydrologic processes as a framework for future studies.

  8. Oscillations in the bistable regime of neuronal networks

    Science.gov (United States)

    Roxin, Alex; Compte, Albert

    2016-07-01

    Bistability between attracting fixed points in neuronal networks has been hypothesized to underlie persistent activity observed in several cortical areas during working memory tasks. In network models this kind of bistability arises due to strong recurrent excitation, sufficient to generate a state of high activity created in a saddle-node (SN) bifurcation. On the other hand, canonical network models of excitatory and inhibitory neurons (E-I networks) robustly produce oscillatory states via a Hopf (H) bifurcation due to the E-I loop. This mechanism for generating oscillations has been invoked to explain the emergence of brain rhythms in the β to γ bands. Although both bistability and oscillatory activity have been intensively studied in network models, there has not been much focus on the coincidence of the two. Here we show that when oscillations emerge in E-I networks in the bistable regime, their phenomenology can be explained to a large extent by considering coincident SN and H bifurcations, known as a codimension two Takens-Bogdanov bifurcation. In particular, we find that such oscillations are not composed of a stable limit cycle, but rather are due to noise-driven oscillatory fluctuations. Furthermore, oscillations in the bistable regime can, in principle, have arbitrarily low frequency.

  9. Numerical and experimental study of bistable plates for morphing structures

    Science.gov (United States)

    Nicassio, F.; Scarselli, G.; Avanzini, G.; Del Core, G.

    2017-04-01

    This study is concerned with the activation energy threshold of bistable composite plates in order to tailor a bistable system for specific aeronautical applications. The aim is to explore potential configurations of the bistable plates and their dynamic behavior for designing novel morphing structure suitable for aerodynamic surfaces and, as a possible further application, for power harvesters. Bistable laminates have two stable mechanical shapes that can withstand aerodynamic loads without additional constraint forces or locking mechanisms. This kind of structures, when properly loaded, snap-through from one stable configuration to another, causing large strains that can also be used for power harvesting scopes. The transition between the stable states of the composite laminate can be triggered, in principle, simply by aerodynamic loads (pilot, disturbance or passive inputs) without the need of servo-activated control systems. Both numerical simulations based on Finite Element models and experimental testing based on different activating forcing spectra are used to validate this concept. The results show that dynamic activation of bistable plates depend on different parameters that need to be carefully managed for their use as aircraft passive wing flaps.

  10. Cavity enhanced nonlinear optics for few photon optical bistability.

    Science.gov (United States)

    Fryett, Taylor K; Dodson, Christopher M; Majumdar, Arka

    2015-06-15

    Weak material nonlinearity at optical frequencies poses a serious hurdle to realizing optical bistability at low optical powers, which is a critical component for digital optical computing. In this paper, we explore the cavity enhancement of the second-order optical nonlinearity in order to determine the feasibility of few photon optical bistability. Starting from a quantum optical formalism of a doubly resonant cavity (required to meet the condition of phase matching), we derive a dynamic classical model of a cavity that is bistable at the fundamental mode. We analyze the optical energy and the switching speed as a function of the cavity quality factors and mode volumes and identify the regime where only ten's of photons are required to perform the switching. An unusual trend in the switching speed is also observed, where the speed monotonically decreases as the cavity linewidth increases. This is ascribed to the increase in the switching gain with increasing cavity linewidth.

  11. Charge-induced optical bistability in thermal Rydberg vapor

    CERN Document Server

    Weller, Daniel; Rico, Andy; Löw, Robert; Kübler, Harald

    2016-01-01

    We investigate the phenomenon of optical bistability in a driven ensemble of Rydberg atoms. By performing two experiments with thermal vapors of rubidium and cesium, we are able to shed light onto the underlying interaction mechanisms causing such a non-linear behavior. Due to the different properties of these two atomic species, we conclude that the large polarizability of Rydberg states in combination with electric fields of spontaneously ionized Rydberg atoms is the relevant interaction mechanism. In the case of rubidium, we directly measure the electric field in a bistable situation via two-species spectroscopy. In cesium, we make use of the different sign of the polarizability for different l-states and the possibility of applying electric fields. Both these experiments allow us to rule out dipole-dipole interactions, and support our hypothesis of a charge-induced bistability.

  12. Amazonian forest-savanna bistability and human impact

    Science.gov (United States)

    Wuyts, Bert; Champneys, Alan R.; House, Joanna I.

    2017-05-01

    A bimodal distribution of tropical tree cover at intermediate precipitation levels has been presented as evidence of fire-induced bistability. Here we subdivide satellite vegetation data into those from human-unaffected areas and those from regions close to human-cultivated zones. Bimodality is found to be almost absent in the unaffected regions, whereas it is significantly enhanced close to cultivated zones. Assuming higher logging rates closer to cultivated zones and spatial diffusion of fire, our spatiotemporal mathematical model reproduces these patterns. Given a gradient of climatic and edaphic factors, rather than bistability there is a predictable spatial boundary, a Maxwell point, that separates regions where forest and savanna states are naturally selected. While bimodality can hence be explained by anthropogenic edge effects and natural spatial heterogeneity, a narrow range of bimodality remaining in the human-unaffected data indicates that there is still bistability, although on smaller scales than claimed previously.

  13. Opto-VLSI-based reconfigurable free-space optical interconnects architecture

    DEFF Research Database (Denmark)

    Aljada, Muhsen; Alameh, Kamal; Chung, Il-Sug

    2007-01-01

    is the Opto-VLSI processor which can be driven by digital phase steering and multicasting holograms that reconfigure the optical interconnects between the input and output ports. The optical interconnects architecture is experimentally demonstrated at 2.5 Gbps using high-speed 1×3 VCSEL array and 1......×3 photoreceiver array in conjunction with two 1×4096 pixel Opto-VLSI processors. The minimisation of the crosstalk between the output ports is achieved by appropriately aligning the VCSEL and PD elements with respect to the Opto-VLSI processors and driving the latter with optimal steering phase holograms....

  14. A VLSI design concept for parallel iterative algorithms

    Directory of Open Access Journals (Sweden)

    C. C. Sun

    2009-05-01

    Full Text Available Modern VLSI manufacturing technology has kept shrinking down to the nanoscale level with a very fast trend. Integration with the advanced nano-technology now makes it possible to realize advanced parallel iterative algorithms directly which was almost impossible 10 years ago. In this paper, we want to discuss the influences of evolving VLSI technologies for iterative algorithms and present design strategies from an algorithmic and architectural point of view. Implementing an iterative algorithm on a multiprocessor array, there is a trade-off between the performance/complexity of processors and the load/throughput of interconnects. This is due to the behavior of iterative algorithms. For example, we could simplify the parallel implementation of the iterative algorithm (i.e., processor elements of the multiprocessor array in any way as long as the convergence is guaranteed. However, the modification of the algorithm (processors usually increases the number of required iterations which also means that the switch activity of interconnects is increasing. As an example we show that a 25×25 full Jacobi EVD array could be realized into one single FPGA device with the simplified μ-rotation CORDIC architecture.

  15. A programmable analog VLSI neural network processor for communication receivers.

    Science.gov (United States)

    Choi, J; Bang, S H; Sheu, B J

    1993-01-01

    An analog VLSI neural network processor was designed and fabricated for communication receiver applications. It does not require prior estimation of the channel characteristics. A powerful channel equalizer was implemented with this processor chip configured as a four-layered perceptron network. The compact synapse cell is realized with an enhanced wide-range Gilbert multiplier circuit. The output neuron consists of a linear current-to-voltage converter and a sigmoid function generator with a controllable voltage gain. Network training is performed by the modified Kalman neuro-filtering algorithm to speed up the convergence process for intersymbol interference and white Gaussian noise communication channels. The learning process is done in the companion DSP board which also keeps the synapse weight for later use of the chip. The VLSI neural network processor chip occupies a silicon area of 4.6 mmx6.8 mm and was fabricated in a 2-mum double-polysilicon CMOS technology. System analysis and experimental results are presented.

  16. VLSI design for reliability. Final report, September-November 1989

    Energy Technology Data Exchange (ETDEWEB)

    Hajj, I.N.; Najm, F.N.; Yang, P.

    1990-05-01

    This report contains the results of supplementary work done related to the reliability analysis of Application Specific Very Large Scale Integrated (ASIC VLSI) CMOS circuits. The major work is currently being carried out under Task N-9-5716. The main goal of both tasks is to determine the electromigration susceptibility of VLSI circuits. Electromigration is a major reliability problem caused by the transport of atoms in a metal line due to the electron flow. Under persistent current stress, electromigration can cause deformations of the metal lines which may result in shorts or open circuits. The failure rate due to electromigration depends on the current density in the metal lines and is usually expressed as a median-time-to-failure (MTF). This work focuses on the electromigration problem in the power and ground busses. To estimate the bust MTF, an estimate of the current waveform in each branch of the bus is required. In general, the MTF is dependent on the shape of the current waveform, and not simply on its time-average. However, a very large number of such waveform shapes are possible, depending on what inputs are applied to the circuit. This is especially true for complementary metal oxide semiconductors circuits, which draw current only during switching.

  17. Hierarchical Chunking of Sequential Memory on Neuromorphic Architecture with Reduced Synaptic Plasticity.

    Science.gov (United States)

    Li, Guoqi; Deng, Lei; Wang, Dong; Wang, Wei; Zeng, Fei; Zhang, Ziyang; Li, Huanglong; Song, Sen; Pei, Jing; Shi, Luping

    2016-01-01

    Chunking refers to a phenomenon whereby individuals group items together when performing a memory task to improve the performance of sequential memory. In this work, we build a bio-plausible hierarchical chunking of sequential memory (HCSM) model to explain why such improvement happens. We address this issue by linking hierarchical chunking with synaptic plasticity and neuromorphic engineering. We uncover that a chunking mechanism reduces the requirements of synaptic plasticity since it allows applying synapses with narrow dynamic range and low precision to perform a memory task. We validate a hardware version of the model through simulation, based on measured memristor behavior with narrow dynamic range in neuromorphic circuits, which reveals how chunking works and what role it plays in encoding sequential memory. Our work deepens the understanding of sequential memory and enables incorporating it for the investigation of the brain-inspired computing on neuromorphic architecture.

  18. Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system

    Directory of Open Access Journals (Sweden)

    Daniel Brüderle

    2009-06-01

    Full Text Available Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated.

  19. Establishing a Novel Modeling Tool: A Python-Based Interface for a Neuromorphic Hardware System

    Science.gov (United States)

    Brüderle, Daniel; Müller, Eric; Davison, Andrew; Muller, Eilif; Schemmel, Johannes; Meier, Karlheinz

    2008-01-01

    Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated. PMID:19562085

  20. Polymer-electrolyte-gated nanowire synaptic transistors for neuromorphic applications

    Science.gov (United States)

    Zou, Can; Sun, Jia; Gou, Guangyang; Kong, Ling-An; Qian, Chuan; Dai, Guozhang; Yang, Junliang; Guo, Guang-hua

    2017-09-01

    Polymer-electrolytes are formed by dissolving a salt in polymer instead of water, the conducting mechanism involves the segmental motion-assisted diffusion of ion in the polymer matrix. Here, we report on the fabrication of tin oxide (SnO2) nanowire synaptic transistors using polymer-electrolyte gating. A thin layer of poly(ethylene oxide) and lithium perchlorate (PEO/LiClO4) was deposited on top of the devices, which was used to boost device performances. A voltage spike applied on the in-plane gate attracts ions toward the polymer-electrolyte/SnO2 nanowire interface and the ions are gradually returned after the pulse is removed, which can induce a dynamic excitatory postsynaptic current in the nanowire channel. The SnO2 synaptic transistors exhibit the behavior of short-term plasticity like the paired-pulse facilitation and self-adaptation, which is related to the electric double-effect regulation. In addition, the synaptic logic functions and the logical function transformation are also discussed. Such single SnO2 nanowire-based synaptic transistors are of great importance for future neuromorphic devices.

  1. The geodynamo as a bistable oscillator

    Science.gov (United States)

    Hoyng, P.; Ossendrijver, M. A. J. H.; Schmitt, D.

    2001-07-01

    Our intent is to provide a simple and quantitative understanding of the variability of the axial dipole component of the geomagnetic field on both short and long time scales. To this end we study the statistical properties of a prototype nonlinear mean field model. An azimuthal average is employed, so that (1) we address only the axisymmetric component of the field, and (2) the dynamo parameters have a random component that fluctuates on the (fast) eddy turnover time scale. Numerical solutions with a rapidly fluctuating alpha reproduce several features of the geomagnetic field: (1) a variable, dominantly dipolar field with additional fine structure due to excited overtones, and sudden reversals during which the field becomes almost quadrupolar, (2) aborted reversals and excursions, (3) intervals between reversals having a Poisson distribution. These properties are robust, and appear regardless of the type of nonlinearity and the model parameters. A technique is presented for analysing the statistical properties of dynamo models of this type. The Fokker-Planck equation for the amplitude a of the fundamental dipole mode shows that a behaves as the position of a heavily damped particle in a bistable potential ~(1-a^2)^2, subject to random forcing. The dipole amplitude oscillates near the bottom of one well and makes occasional jumps to the other. These reversals are induced solely by the overtones. Theoretical expressions are derived for the statistical distribution of the dipole amplitude, the variance of the dipole amplitude between reversals, and the mean reversal rate. The model explains why the reversal rate increases with increasing secular variation, as observed. Moreover, the present reversal rate of the geodynamo, once per (2-3)x10^5years, is shown to imply a secular variation of the dipole moment of ~15% (about the current value). The theoretical dipole amplitude distribution agrees well with the Sint-800 data.

  2. THE DENSITY DISTRIBUTION IN TURBULENT BISTABLE FLOWS

    Energy Technology Data Exchange (ETDEWEB)

    Gazol, Adriana [Centro de Radioastronomia y Astrofisica, UNAM, A. P. 3-72, c.p. 58089 Morelia, Michoacan (Mexico); Kim, Jongsoo, E-mail: a.gazol@crya.unam.mx, E-mail: jskim@kasi.re.kr [Korea Astronomy and Space Science Institute, 61-1, Hwaam-Dong, Yuseong-Ku, Daejeon 305-348 (Korea, Republic of)

    2013-03-01

    We numerically study the volume density probability distribution function (n-PDF) and the column density probability distribution function ({Sigma}-PDF) resulting from thermally bistable turbulent flows. We analyze three-dimensional hydrodynamic models in periodic boxes of 100 pc by side, where turbulence is driven in the Fourier space at a wavenumber corresponding to 50 pc. At low densities (n {approx}< 0.6 cm{sup -3}), the n-PDF is well described by a lognormal distribution for an average local Mach number ranging from {approx}0.2 to {approx}5.5. As a consequence of the nonlinear development of thermal instability (TI), the logarithmic variance of the distribution of the diffuse gas increases with M faster than in the well-known isothermal case. The average local Mach number for the dense gas (n {approx}> 7.1 cm{sup -3}) goes from {approx}1.1 to {approx}16.9 and the shape of the high-density zone of the n-PDF changes from a power law at low Mach numbers to a lognormal at high M values. In the latter case, the width of the distribution is smaller than in the isothermal case and grows slower with M. At high column densities, the {Sigma}-PDF is well described by a lognormal for all of the Mach numbers we consider and, due to the presence of TI, the width of the distribution is systematically larger than in the isothermal case but follows a qualitatively similar behavior as M increases. Although a relationship between the width of the distribution and M can be found for each one of the cases mentioned above, these relations are different from those of the isothermal case.

  3. Optical bistability in nonlinear composites with coated ellipsoidal nanoparticles

    CERN Document Server

    Pinchuk, A

    2003-01-01

    Nonlinear composite structures show great promise for use in optical switching, signal processing, etc. We derive an effective nonlinear dielectric permittivity of composite structures where coated ellipsoidal nonlinear particles are imbedded in a linear host medium. The derived expression for the effective dielectric permittivity tensor follows the Clasius-Mossotti approximation. We observe conditions for the existence of the optical bistability effect in a coated ellipsoidal particle with a nonlinear core and a metallic shell. Our numerical results show stronger bistability effects in more dense suspensions of nonlinear heterogeneous ellipsoids.

  4. Bistable flow spectral analysis. Repercussions on jet pumps

    Energy Technology Data Exchange (ETDEWEB)

    Gavilan Moreno, C.J., E-mail: cgavilan@iies.es [Cofrentes NPP, Engineering Dept., Iberdrola (Spain)

    2011-07-15

    Highlights: > The most important thing in this paper, is the spectral characterization of the bistable flow in a Nuclear Power Plant. > This paper goes deeper in the effect of the bistable flow over the jet pump and the induced vibrations. > The jet pump frequencies are very close to natural jet pump frequencies, in the 3rd and 6th mode. - Abstract: There have been many attempts at characterizing and predicting bistable flow in boiling water reactors (BWRs). Nevertheless, in most cases the results have only managed to develop models that analytically reproduce the phenomenon (). Modeling has been forensic in all cases, while the capacity of the model focus on determining the exclusion areas on the recirculation flow map. The bistability process is known by its effects given there is no clear definition of its causal process. In the 1980s, Hitachi technicians () managed to reproduce bistable flow in the laboratory by means of pipe geometry, similar to that which is found in recirculation loops. The result was that the low flow pattern is formed by the appearance of a quasi stationary, helicoidal vortex in the recirculation collector's branches. This vortex creates greater frictional losses than regions without vortices, at the same discharge pressure. Neither the behavior nor the dynamics of these vortices were characterized in this paper. The aim of this paper is to characterize these vortices in such a way as to enable them to provide their own frequencies and their later effect on the jet pumps. The methodology used in this study is similar to the one used previously when analyzing the bistable flow in tube arrays with cross flow (). The method employed makes use of the power spectral density function. What differs is the field of application. We will analyze a Loop B with a bistable flow and compare the high and low flow situations. The same analysis will also be carried out on the loop that has not developed the bistable flow (Loop A) at the same moments

  5. Microfluidic very large scale integration (VLSI) modeling, simulation, testing, compilation and physical synthesis

    CERN Document Server

    Pop, Paul; Madsen, Jan

    2016-01-01

    This book presents the state-of-the-art techniques for the modeling, simulation, testing, compilation and physical synthesis of mVLSI biochips. The authors describe a top-down modeling and synthesis methodology for the mVLSI biochips, inspired by microelectronics VLSI methodologies. They introduce a modeling framework for the components and the biochip architecture, and a high-level microfluidic protocol language. Coverage includes a topology graph-based model for the biochip architecture, and a sequencing graph to model for biochemical application, showing how the application model can be obtained from the protocol language. The techniques described facilitate programmability and automation, enabling developers in the emerging, large biochip market. · Presents the current models used for the research on compilation and synthesis techniques of mVLSI biochips in a tutorial fashion; · Includes a set of "benchmarks", that are presented in great detail and includes the source code of several of the techniques p...

  6. Summary of workshop on the application of VLSI for robotic sensing

    Science.gov (United States)

    Brooks, T.; Wilcox, B.

    1984-01-01

    It was one of the objectives of the considered workshop to identify near, mid, and far-term applications of VLSI for robotic sensing and sensor data preprocessing. The workshop was also to indicate areas in which VLSI technology can provide immediate and future payoffs. A third objective is related to the promotion of dialog and collaborative efforts between research communities, industry, and government. The workshop was held on March 24-25, 1983. Conclusions and recommendations are discussed. Attention is given to the need for a pixel correction chip, an image sensor with 10,000 dynamic range, VLSI enhanced architectures, the need for a high-density serpentine memory, an LSI-tactile sensing program, an analog-signal preprocessor chip, a smart strain gage, a protective proximity envelope, a VLSI-proximity sensor program, a robot-net chip, and aspects of silicon micromechanics.

  7. Application of evolutionary algorithms for multi-objective optimization in VLSI and embedded systems

    CERN Document Server

    2015-01-01

    This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO, and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing, and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation, and operators like crossover, mutation, etc. can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field ...

  8. Confirmation of bistable stellar differential rotation profiles

    Science.gov (United States)

    Käpylä, P. J.; Käpylä, M. J.; Brandenburg, A.

    2014-10-01

    Context. Solar-like differential rotation is characterized by a rapidly rotating equator and slower poles. However, theoretical models and numerical simulations can also result in a slower equator and faster poles when the overall rotation is slow. Aims: We study the critical rotational influence under which differential rotation flips from solar-like (fast equator, slow poles) to an anti-solar one (slow equator, fast poles). We also estimate the non-diffusive (Λ effect) and diffusive (turbulent viscosity) contributions to the Reynolds stress. Methods: We present the results of three-dimensional numerical simulations of mildly turbulent convection in spherical wedge geometry. Here we apply a fully compressible setup which would suffer from a prohibitive time step constraint if the real solar luminosity was used. To avoid this problem while still representing the same rotational influence on the flow as in the Sun, we increase the luminosity by a factor of roughly 106 and the rotation rate by a factor of 102. We regulate the convective velocities by varying the amount of heat transported by thermal conduction, turbulent diffusion, and resolved convection. Results: Increasing the efficiency of resolved convection leads to a reduction of the rotational influence on the flow and a sharp transition from solar-like to anti-solar differential rotation for Coriolis numbers around 1.3. We confirm the recent finding of a large-scale flow bistability: contrasted with running the models from an initial condition with unprescribed differential rotation, the initialization of the model with certain kind of rotation profile sustains the solution over a wider parameter range. The anti-solar profiles are found to be more stable against perturbations in the level of convective turbulent velocity than the solar-type solutions. Conclusions: Our results may have implications for real stars that start their lives as rapid rotators implying solar-like rotation in the early main

  9. Beyond bistability: biophysics and temporal dynamics of working memory.

    Science.gov (United States)

    Durstewitz, D; Seamans, J K

    2006-04-28

    Working memory has often been modeled and conceptualized as a kind of binary (bistable) memory switch, where stimuli turn on plateau-like persistent activity in subsets of cells, in line with many in vivo electrophysiological reports. A potentially related form of bistability, termed up- and down-states, has been studied with regard to its synaptic and ionic basis in vivo and in reduced cortical preparations. Also single cell mechanisms for producing bistability have been proposed and investigated in brain slices and computationally. Recently, however, it has been emphasized that clear plateau-like bistable activity is rather rare during working memory tasks, and that neurons exhibit a multitude of different temporally unfolding activity profiles and temporal structure within their spiking dynamics. Hence, working memory seems to be a highly dynamical neural process with yet unknown mappings from dynamical to computational properties. Empirical findings on ramping activity profiles and temporal structure will be reviewed, as well as neural models that attempt to account for it and its computational significance. Furthermore, recent in vivo, neural culture, and in vitro preparations will be discussed that offer new possibilities for studying the biophysical mechanisms underlying computational processes during working memory. These preparations have revealed additional evidence for temporal structure and spatio-temporally organized attractor states in cortical networks, as well as for specific computational properties that may characterize synaptic processing during high-activity states as during working memory. Together such findings may lay the foundations for highly dynamical theories of working memory based on biophysical principles.

  10. Optical bistability in a nonlinear photonic crystal waveguide notch filter

    NARCIS (Netherlands)

    Stoffer, Remco; Kivshar, Yu. S.; Leijtens, X.J.M.; Besten, J.H.

    2000-01-01

    Optical bistability occurs when the effects of nonlinear behaviour of materials cause hysteresis in the transmission and reflection of a device. A possible mechanism for this is a strong dependence of the optical intensity on the index of refraction, e.g. in a cavity near resonance. In a 2-

  11. Dynamics of a bistable Miura-origami structure

    Science.gov (United States)

    Fang, Hongbin; Li, Suyi; Ji, Huimin; Wang, K. W.

    2017-05-01

    Origami-inspired structures and materials have shown extraordinary properties and performances originating from the intricate geometries of folding. However, current state of the art studies have mostly focused on static and quasistatic characteristics. This research performs a comprehensive experimental and analytical study on the dynamics of origami folding through investigating a stacked Miura-Ori (SMO) structure with intrinsic bistability. We fabricate and experimentally investigated a bistable SMO prototype with rigid facets and flexible crease lines. Under harmonic base excitation, the SMO exhibits both intrawell and interwell oscillations. Spectrum analyses reveal that the dominant nonlinearities of SMO are quadratic and cubic, which generate rich dynamics including subharmonic and chaotic oscillations. The identified nonlinearities indicate that a third-order polynomial can be employed to approximate the measured force-displacement relationship. Such an approximation is validated via numerical study by qualitatively reproducing the phenomena observed in the experiments. The dynamic characteristics of the bistable SMO resemble those of a Helmholtz-Duffing oscillator (HDO); this suggests the possibility of applying the established tools and insights of HDO to predict origami dynamics. We also show that the bistability of SMO can be programmed within a large design space via tailoring the crease stiffness and initial stress-free configurations. The results of this research offer a wealth of fundamental insights into the dynamics of origami folding, and provide a solid foundation for developing foldable and deployable structures and materials with embedded dynamic functionalities.

  12. Bistable soliton states and switching in doubly inhomogeneously ...

    Indian Academy of Sciences (India)

    ... Lecture Workshops · Refresher Courses · Symposia. Home; Journals; Pramana – Journal of Physics; Volume 57; Issue 5-6. Bistable soliton states and switching in doubly inhomogeneously doped fiber couplers. Ajit Kumar. Theoretical aspects of optical solitons Volume 57 Issue 5-6 November-December 2001 pp 969-979 ...

  13. Bubbling and bistability in two parameter discrete systems

    Indian Academy of Sciences (India)

    there are other interesting phenomena like bubble structures and bistability that have in- ... i.e., the underlying basic features that make them support bubbles in their bifurcation sce- nario. The above mentioned ..... SNV thanks the UGC, New Delhi for financial assistance through a junior research fellow- ship and GA ...

  14. Skimming Digits: Neuromorphic Classification of Spike-Encoded Images

    Directory of Open Access Journals (Sweden)

    Gregory Kevin Cohen

    2016-04-01

    Full Text Available The growing demands placed upon the field of computer vision has renewed the focus on alternative visual scene representations and processing paradigms. Silicon retinea provide an alternative means of imaging the visual environment, and produce frame-free spatio-temporal data. This paper presents an investigation into event-based digit classification using N-MNIST,a neuromorphic dataset created with a silicon retina, and the Synaptic Kernel Inverse Method (SKIM, a learning method based on principles of dendritic computation. As this work represents the first large-scale and multi-class classification task performed using the SKIM network, it explores different training patterns and output determination methods necessary to extend the original SKIM method to support multi-class problems. Making use of SKIM networks applied to real-world datasets, implementing the largest hidden layer sizes and simultaneously training the largest number of output neurons, the classification system achieved a best-case accuracy of 92.87% for a network containing 10,000 hidden layer neurons. These results represent the highest accuracies achieved against the dataset to date and serves to validate the application of the SKIM method to event-based visual classification tasks. Additionally, the study found that using a square pulse as the supervisory training signal produced the highest accuracy for most output determination methods, but the results also demonstrate that an exponential pattern is better suited to hardware implementations as it makes use of the simplest output determination method based on the maximum value.

  15. Piecewise Linear Approach for Timing Simulation of VLSI (Very-Large-Scale-Integrated) Circuits on Serial and Parallel Computers.

    Science.gov (United States)

    1987-12-01

    328 S % 33880E ° PIECEWISE LINEAR APPROACH FOR TIMING SIMULATION OF VLSI CIRCUITS ON SERIAL AND PARALLEL COMPUTERS Ongky Tejayadi UNIVE,’RSITY OF ILL...APPROACH FOR TIMING SIMULATION OF VLSI CIRCUITS ON SERIAL AND PARALLEL COMPUTERS 12. PERSONAL AUTHOR(S) Tejayadi, Ongky 13a. TYPE OF REPO~Z J,..-13b...PIECE’WISE LINEAR APPROACH FOR TIMING SIMULATION OF VLSI CIRCUITS ON SERIAL AND PARALLEL COMPUTERS BY ONGKY TEJAYADI B.S., University of Illinois

  16. Cascaded VLSI Chips Help Neural Network To Learn

    Science.gov (United States)

    Duong, Tuan A.; Daud, Taher; Thakoor, Anilkumar P.

    1993-01-01

    Cascading provides 12-bit resolution needed for learning. Using conventional silicon chip fabrication technology of VLSI, fully connected architecture consisting of 32 wide-range, variable gain, sigmoidal neurons along one diagonal and 7-bit resolution, electrically programmable, synaptic 32 x 31 weight matrix implemented on neuron-synapse chip. To increase weight nominally from 7 to 13 bits, synapses on chip individually cascaded with respective synapses on another 32 x 32 matrix chip with 7-bit resolution synapses only (without neurons). Cascade correlation algorithm varies number of layers effectively connected into network; adds hidden layers one at a time during learning process in such way as to optimize overall number of neurons and complexity and configuration of network.

  17. Analog VLSI implementation of resonate-and-fire neuron.

    Science.gov (United States)

    Nakada, Kazuki; Asai, Tetsuya; Hayashi, Hatsuo

    2006-12-01

    We propose an analog integrated circuit that implements a resonate-and-fire neuron (RFN) model based on the Lotka-Volterra (LV) system. The RFN model is a spiking neuron model that has second-order membrane dynamics, and thus exhibits fast damped subthreshold oscillation, resulting in the coincidence detection, frequency preference, and post-inhibitory rebound. The RFN circuit has been derived from the LV system to mimic such dynamical behavior of the RFN model. Through circuit simulations, we demonstrate that the RFN circuit can act as a coincidence detector and a band-pass filter at circuit level even in the presence of additive white noise and background random activity. These results show that our circuit is expected to be useful for very large-scale integration (VLSI) implementation of functional spiking neural networks.

  18. Efficient VLSI Architecture for Training Radial Basis Function Networks

    Science.gov (United States)

    Fan, Zhe-Cheng; Hwang, Wen-Jyi

    2013-01-01

    This paper presents a novel VLSI architecture for the training of radial basis function (RBF) networks. The architecture contains the circuits for fuzzy C-means (FCM) and the recursive Least Mean Square (LMS) operations. The FCM circuit is designed for the training of centers in the hidden layer of the RBF network. The recursive LMS circuit is adopted for the training of connecting weights in the output layer. The architecture is implemented by the field programmable gate array (FPGA). It is used as a hardware accelerator in a system on programmable chip (SOPC) for real-time training and classification. Experimental results reveal that the proposed RBF architecture is an effective alternative for applications where fast and efficient RBF training is desired. PMID:23519346

  19. Carbon nanotube based VLSI interconnects analysis and design

    CERN Document Server

    Kaushik, Brajesh Kumar

    2015-01-01

    The brief primarily focuses on the performance analysis of CNT based interconnects in current research scenario. Different CNT structures are modeled on the basis of transmission line theory. Performance comparison for different CNT structures illustrates that CNTs are more promising than Cu or other materials used in global VLSI interconnects. The brief is organized into five chapters which mainly discuss: (1) an overview of current research scenario and basics of interconnects; (2) unique crystal structures and the basics of physical properties of CNTs, and the production, purification and applications of CNTs; (3) a brief technical review, the geometry and equivalent RLC parameters for different single and bundled CNT structures; (4) a comparative analysis of crosstalk and delay for different single and bundled CNT structures; and (5) various unique mixed CNT bundle structures and their equivalent electrical models.

  20. Spike-driven synaptic plasticity: theory, simulation, VLSI implementation.

    Science.gov (United States)

    Fusi, S; Annunziato, M; Badoni, D; Salamon, A; Amit, D J

    2000-10-01

    We present a model for spike-driven dynamics of a plastic synapse, suited for aVLSI implementation. The synaptic device behaves as a capacitor on short timescales and preserves the memory of two stable states (efficacies) on long timescales. The transitions (LTP/LTD) are stochastic because both the number and the distribution of neural spikes in any finite (stimulation) interval fluctuate, even at fixed pre- and postsynaptic spike rates. The dynamics of the single synapse is studied analytically by extending the solution to a classic problem in queuing theory (Takacs process). The model of the synapse is implemented in aVLSI and consists of only 18 transistors. It is also directly simulated. The simulations indicate that LTP/LTD probabilities versus rates are robust to fluctuations of the electronic parameters in a wide range of rates. The solutions for these probabilities are in very good agreement with both the simulations and measurements. Moreover, the probabilities are readily manipulable by variations of the chip's parameters, even in ranges where they are very small. The tests of the electronic device cover the range from spontaneous activity (3-4 Hz) to stimulus-driven rates (50 Hz). Low transition probabilities can be maintained in all ranges, even though the intrinsic time constants of the device are short (approximately 100 ms). Synaptic transitions are triggered by elevated presynaptic rates: for low presynaptic rates, there are essentially no transitions. The synaptic device can preserve its memory for years in the absence of stimulation. Stochasticity of learning is a result of the variability of interspike intervals; noise is a feature of the distributed dynamics of the network. The fact that the synapse is binary on long timescales solves the stability problem of synaptic efficacies in the absence of stimulation. Yet stochastic learning theory ensures that it does not affect the collective behavior of the network, if the transition probabilities are

  1. An Energy Efficient Neuromorphic Computing System Using Real Time Sensing Method

    DEFF Research Database (Denmark)

    Farkhani, Hooman; Tohidi, Mohammad; Farkhani, Sadaf

    In spintronic-based neuromorphic computing systems (NCS), the switching of magnetic moment in a magnetic tunnel junction (MTJ) is used to mimic neuron firing. However, the stochastic switching behavior of the MTJ and process variations effect leads to extra stimulation time. This leads to extra e...

  2. Neuromorphic Computing: A Post-Moore's Law Complementary Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Birdwell, John Douglas [University of Tennessee (UT); Dean, Mark [University of Tennessee (UT); Plank, James [University of Tennessee (UT); Rose, Garrett [University of Tennessee (UT)

    2016-01-01

    We describe our approach to post-Moore's law computing with three neuromorphic computing models that share a RISC philosophy, featuring simple components combined with a flexible and programmable structure. We envision these to be leveraged as co-processors, or as data filters to provide in situ data analysis in supercomputing environments.

  3. A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs).

    Science.gov (United States)

    Moradi, Saber; Qiao, Ning; Stefanini, Fabio; Indiveri, Giacomo

    2018-02-01

    Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here, we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multicore neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.

  4. A Binaural Neuromorphic Auditory Sensor for FPGA: A Spike Signal Processing Approach.

    Science.gov (United States)

    Jimenez-Fernandez, Angel; Cerezuela-Escudero, Elena; Miro-Amarante, Lourdes; Dominguez-Moralse, Manuel Jesus; de Asis Gomez-Rodriguez, Francisco; Linares-Barranco, Alejandro; Jimenez-Moreno, Gabriel

    2017-04-01

    This paper presents a new architecture, design flow, and field-programmable gate array (FPGA) implementation analysis of a neuromorphic binaural auditory sensor, designed completely in the spike domain. Unlike digital cochleae that decompose audio signals using classical digital signal processing techniques, the model presented in this paper processes information directly encoded as spikes using pulse frequency modulation and provides a set of frequency-decomposed audio information using an address-event representation interface. In this case, a systematic approach to design led to a generic process for building, tuning, and implementing audio frequency decomposers with different features, facilitating synthesis with custom features. This allows researchers to implement their own parameterized neuromorphic auditory systems in a low-cost FPGA in order to study the audio processing and learning activity that takes place in the brain. In this paper, we present a 64-channel binaural neuromorphic auditory system implemented in a Virtex-5 FPGA using a commercial development board. The system was excited with a diverse set of audio signals in order to analyze its response and characterize its features. The neuromorphic auditory system response times and frequencies are reported. The experimental results of the proposed system implementation with 64-channel stereo are: a frequency range between 9.6 Hz and 14.6 kHz (adjustable), a maximum output event rate of 2.19 Mevents/s, a power consumption of 29.7 mW, the slices requirements of 11141, and a system clock frequency of 27 MHz.

  5. PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems

    Directory of Open Access Journals (Sweden)

    Fabio eStefanini

    2014-08-01

    Full Text Available Neuromorphic hardware offers an electronic substrate for the realization of asynchronousevent-based sensory-motor systems and large-scale spiking neural network architectures. Inorder to characterize these systems, configure them, and carry out modeling experiments, it isoften necessary to interface them to workstations. The software used for this purpose typicallyconsists of a large monolithic block of code highly specific to the hardware setup used. While thisapproach can lead to highly integrated hardware/software systems, it hampers the developmentof modular and neuromorphic infrastructures. To alleviate this problem, we propose PyNCS,an open-source front-end for the definition of neural network models that is interfaced to thehardware through a set of Python Application Programming Interfaces (APIs. The designof PyNCS promotes modularity, portability and expandability and separates implementationfrom hardware description. The high-level front-end that comes with PyNCS includes tools todefine neural network models as well as to create, monitor and analyze spiking data. Here wereport the design philosophy behind the PyNCS framework and describe its implementation.We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carryingout a cognitive decision-making task involving state-dependent computation. PyNCS, alreadyapplicable to a wide range of existing spike-based neuromorphic setups, will accelerate thedevelopment of hybrid software/hardware neuromorphic systems, thanks to its code flexibility.The code developed is open-source and available online at https://github.com/inincs/pyNCS.

  6. Bistable dynamics of a levitated nanoparticle (Presentation Recording)

    Science.gov (United States)

    Ricci, Francesco; Spasenovic, M.; Rica, Raúl A.; Novotny, Lukas; Quidant, Romain

    2015-08-01

    Bistable systems are ubiquitous in nature. Classical examples in chemistry and biology include relaxation kinetics in chemical reactions [1] and stochastic resonance processes such as neuron firing [2,3]. Likewise, bistable systems play a key role in signal processing and information handling at the nanoscale, giving rise to intriguing applications such as optical switches [4], coherent signal amplification [5,6] and weak forces detection [5]. The interest and applicability of bistable systems are intimately connected with the complexity of their dynamics, typically due to the presence of a large number of parameters and nonlinearities. Appropriate modeling is therefore challenging. Alternatively, the possibility to experimentally recreate bistable systems in a clean and controlled way has recently become very appealing, but elusive and complicated. With this aim, we combined optical tweezers with a novel active feedback-cooling scheme to develop a well-defined opto-mechanical platform reaching unprecedented performances in terms of Q-factor, frequency stability and force sensitivity [7,8]. Our experimental system consists of a single nanoparticle levitated in high vacuum with optical tweezers, which behaves as a non-linear (Duffing) oscillator under appropriate conditions. Here, we prove it to be an ideal tool for a deep study of bistability. We demonstrate bistability of the nanoparticle by noise activated switching between two oscillation states, discussing our results in terms of a double-well potential model. We also show the flexibility of our system in shaping the potential at will, in order to meet the conditions prescribed by any bistable system that could therefore then be simulated with our setup. References [1] T. Amemiya, T. Ohmori, M. Nakaiwa, T. Yamamoto, and T. Yamaguchi, "Modeling of Nonlinear Chemical Reaction Systems and Two-Parameter Stochastic Resonance," J. Biol. Phys. 25 (1999) 73 [2] F. Moss, L. M. Ward, and W. G. Sannita, "Stochastic

  7. Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System

    Science.gov (United States)

    Milde, Moritz B.; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

    2017-01-01

    Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware. PMID:28747883

  8. Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System

    Directory of Open Access Journals (Sweden)

    Moritz B. Milde

    2017-07-01

    Full Text Available Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware.

  9. Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System.

    Science.gov (United States)

    Milde, Moritz B; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

    2017-01-01

    Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware.

  10. Energy landscape and dynamics of brain activity during human bistable perception.

    OpenAIRE

    Watanabe, T; Masuda, N.; Megumi, F.; Kanai, R.; Rees, G.

    2014-01-01

    Individual differences in the structure of parietal and prefrontal cortex predict the stability of bistable visual perception. However, the mechanisms linking such individual differences in brain structures to behaviour remain elusive. Here we demonstrate a systematic relationship between the dynamics of brain activity, cortical structure and behaviour underpinning bistable perception. Using fMRI in humans, we find that the activity dynamics during bistable perception are well described as fl...

  11. Bistability of the naturally induced lactose utilization system of Escherichia coli

    Science.gov (United States)

    Stajic, Jelena; Wall, Michael

    2006-03-01

    In the absence of the preferred sugar glucose, lactose utilization machinery in the bacterium E. coli is activated. The genetic circuit responsible for this response, lac operon, has been observed to exhibit bistability when induced by an artificial inducer, TMG. Here we investigate conditions under which bistability might be observed in response to lactose. The aim of our study is to establish whether the natural system exhibits bistability, as is often assumed despite the lack of experimental support.

  12. Control of Bistability in a Delayed Duffing Oscillator

    Directory of Open Access Journals (Sweden)

    Mustapha Hamdi

    2012-01-01

    Full Text Available The effect of a high-frequency excitation on nontrivial solutions and bistability in a delayed Duffing oscillator with a delayed displacement feedback is investigated in this paper. We use the technique of direct partition of motion and the multiple scales method to obtain the slow dynamic of the system and its slow flow. The analysis of the slow flow provides approximations of the Hopf and secondary Hopf bifurcation curves. As a result, this study shows that increasing the delay gain, the system undergoes a secondary Hopf bifurcation. Further, it is indicated that as the frequency of the excitation is increased, the Hopf and secondary Hopf bifurcation curves overlap giving birth in the parameter space to small regions of bistability where a stable trivial steady state and a stable limit cycle coexist. Numerical simulations are carried out to validate the analytical finding.

  13. Bistable memory device based on DNA biopolymer nanocomposite

    Science.gov (United States)

    Lin, Yi-Tzu; Lin, Ting-Yu; Hung, Yu-Chueh

    2014-05-01

    Deoxyribonucleic acid (DNA), as one kind of biopolymer, has recently emerged as an attractive optical material, showing promise in making versatile optoelectronic devices. In the present study, we report the fabrication and characterization of DNA biopolymer nanocomposite with tunable conductivities and the application in bistable memory device. DNA nanocomposite consisting of DNA biopolymer and silver nanoparticles is synthesized using a phototriggered method. The nanocomposite exhibits tunable conductivities when exposed to UV light under different periods of time. The electrical conductivity is suggested to be dependent on the quantity and the distribution of silver nanoparticles formed in DNA biopolymer. In addition, a memory device based on DNA biopolymer nanocomposite is demonstrated. The operation of different conductivity states can be adjusted by the concentration of nanoparticles. The device shows bistability of current, and presents a stable write-read-erase cycle. Detailed performance of the DNA-based memory device will be presented and discussed.

  14. A New Bistable SmA Display Mode

    Science.gov (United States)

    Chen, Hui-Yu; Shao, Renfan; Korblova, Eva; Walba, David; Lee, Wei; Clark, Noel A.

    2007-03-01

    In the traditional SmA display, crossed polarizers are absent and one can switch a light transparent state to an opaque light scattering state by using laser addressing or electric addressing. Such displays are bright, but of only moderate contrast ratio. Here, we present a new operation mode for a SmA display using two sets of electrodes, with one to induce homeotropic orientation and the other having an in-plane structure to induce planar orientation. This switching with crossed polarizer and analyzer enables a high contrast, bistable electro-optical effect. This SmA display mode exhibits a high contrast ratio (2500:1) for non-striped ITO pattern cells, prefect bistability, and reasonably fast switching (a few ms). These characteristics may enable potential applications on e-paper.

  15. Stochastic sensitivity of a bistable energy model for visual perception

    Science.gov (United States)

    Pisarchik, Alexander N.; Bashkirtseva, Irina; Ryashko, Lev

    2017-01-01

    Modern trends in physiology, psychology and cognitive neuroscience suggest that noise is an essential component of brain functionality and self-organization. With adequate noise the brain as a complex dynamical system can easily access different ordered states and improve signal detection for decision-making by preventing deadlocks. Using a stochastic sensitivity function approach, we analyze how sensitive equilibrium points are to Gaussian noise in a bistable energy model often used for qualitative description of visual perception. The probability distribution of noise-induced transitions between two coexisting percepts is calculated at different noise intensity and system stability. Stochastic squeezing of the hysteresis range and its transition from positive (bistable regime) to negative (intermittency regime) are demonstrated as the noise intensity increases. The hysteresis is more sensitive to noise in the system with higher stability.

  16. Stochastic resonance enhanced by dichotomic noise in a bistable system

    Energy Technology Data Exchange (ETDEWEB)

    Rozenfeld, Robert [Institute for Physics, Humboldt University at Berlin, D-10115, Berlin, (Germany); Neiman, Alexander [Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri 63121 (United States); Schimansky-Geier, Lutz [Institute for Physics, Humboldt University at Berlin, D-10115, Berlin, (Germany)

    2000-09-01

    We study linear responses of a stochastic bistable system driven by dichotomic noise to a weak periodic signal. We show that the effect of stochastic resonance can be greatly enhanced in comparison with the conventional case when dichotomic forcing is absent, that is, both the signal-to-noise ratio and the spectral power amplification reach much greater values than in the standard stochastic resonance setup. (c) 2000 The American Physical Society.

  17. A Precise Temperature-Responsive Bistable Switch Controlling Yersinia Virulence.

    Directory of Open Access Journals (Sweden)

    Aaron Mischa Nuss

    2016-12-01

    Full Text Available Different biomolecules have been identified in bacterial pathogens that sense changes in temperature and trigger expression of virulence programs upon host entry. However, the dynamics and quantitative outcome of this response in individual cells of a population, and how this influences pathogenicity are unknown. Here, we address these questions using a thermosensing virulence regulator of an intestinal pathogen (RovA of Yersinia pseudotuberculosis as a model. We reveal that this regulator is part of a novel thermoresponsive bistable switch, which leads to high- and low-invasive subpopulations within a narrow temperature range. The temperature range in which bistability is observed is defined by the degradation and synthesis rate of the regulator, and is further adjustable via a nutrient-responsive regulator. The thermoresponsive switch is also characterized by a hysteretic behavior in which activation and deactivation occurred on vastly different time scales. Mathematical modeling accurately mirrored the experimental behavior and predicted that the thermoresponsiveness of this sophisticated bistable switch is mainly determined by the thermo-triggered increase of RovA proteolysis. We further observed RovA ON and OFF subpopulations of Y. pseudotuberculosis in the Peyer's patches and caecum of infected mice, and that changes in the RovA ON/OFF cell ratio reduce tissue colonization and overall virulence. This points to a bet-hedging strategy in which the thermoresponsive bistable switch plays a key role in adapting the bacteria to the fluctuating conditions encountered as they pass through the host's intestinal epithelium and suggests novel strategies for the development of antimicrobial therapies.

  18. Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions

    Science.gov (United States)

    Semenov, Sergey N.; Kraft, Lewis J.; Ainla, Alar; Zhao, Mengxia; Baghbanzadeh, Mostafa; Campbell, Victoria E.; Kang, Kyungtae; Fox, Jerome M.; Whitesides, George M.

    2016-09-01

    Networks of organic chemical reactions are important in life and probably played a central part in its origin. Network dynamics regulate cell division, circadian rhythms, nerve impulses and chemotaxis, and guide the development of organisms. Although out-of-equilibrium networks of chemical reactions have the potential to display emergent network dynamics such as spontaneous pattern formation, bistability and periodic oscillations, the principles that enable networks of organic reactions to develop complex behaviours are incompletely understood. Here we describe a network of biologically relevant organic reactions (amide formation, thiolate-thioester exchange, thiolate-disulfide interchange and conjugate addition) that displays bistability and oscillations in the concentrations of organic thiols and amides. Oscillations arise from the interaction between three subcomponents of the network: an autocatalytic cycle that generates thiols and amides from thioesters and dialkyl disulfides; a trigger that controls autocatalytic growth; and inhibitory processes that remove activating thiol species that are produced during the autocatalytic cycle. In contrast to previous studies that have demonstrated oscillations and bistability using highly evolved biomolecules (enzymes and DNA) or inorganic molecules of questionable biochemical relevance (for example, those used in Belousov-Zhabotinskii-type reactions), the organic molecules we use are relevant to metabolism and similar to those that might have existed on the early Earth. By using small organic molecules to build a network of organic reactions with autocatalytic, bistable and oscillatory behaviour, we identify principles that explain the ways in which dynamic networks relevant to life could have developed. Modifications of this network will clarify the influence of molecular structure on the dynamics of reaction networks, and may enable the design of biomimetic networks and of synthetic self-regulating and evolving

  19. Electro-optic bistability in organosiloxane bimesogenic liquid crystals

    Science.gov (United States)

    Gardiner, D. J.; Davenport, C. J.; Newton, J.; Coles, H. J.

    2006-06-01

    In this paper we report the electro-optic characterization of two homologous series of low molar mass bimesogenic siloxane-containing liquid crystals. The materials used have two alkoxycyanobiphenyl mesogenic units with variable alkyl chain joined by a two- or five-siloxane moiety and all exhibit stable smectic A mesophases over wide temperature ranges (up to 100 °C wide). Due to their inherent ruggedness these materials have potential for use in polarizer-free, bistable, scattering display and storage devices. The bistable modes are at low and high frequencies. The low frequency mode (write) is a highly scattering focal conic texture resulting from electrohydrodynamic instabilities while the high frequency mode (erase) is a clear state due to dielectric reorientation of the material. Both modes are preserved upon removal of the applied electric field. We present threshold voltages as a function of temperature, frequency, and cell thickness and response times as a function of voltage for each of the bistable modes. We find reduced threshold voltages (5<=Vth<=12 V/μm) and response times that are strongly dependent on applied voltage (50 ms<=τ<=10 s). These operating conditions would suggest that these materials are particularly suitable for slow update, large area, low power information panels and displays.

  20. Behavior of optical bistability in multifold quantum dot molecules

    Science.gov (United States)

    Hamedi, H. R.; Mehmannavaz, M. R.

    2015-02-01

    We analyze the optical bistability (OB) behavior in a multifold quantum dot (QD) molecule composed of five quantum dots controlled by the tunneling coupling. It is shown that the optical bistability can strongly be affected by the tunneling inter-dot coupling coefficients as well as detuning parameters. In addition, we find that the rate of an incoherent pump field has a leading role in modification of the OB threshold. We then generalize our analysis to the case of multifold quantum dot molecules where the number of the quantum dots is N (with a center dot and N-1 satellite dots). We compare the OB features that could occur in a multifold QD system consist of three (N= ), four (N=\\text{4} ), and five (N = 5) quantum dots. We realize that the OB threshold increases as the number of satellite QDs increases. Such controllable optical bistability in multiple QD molecules may provide some new possibilities for technological applications in optoelectronics and solid-state quantum information science.

  1. Bistability induced by generalist natural enemies can reverse pest invasions.

    Science.gov (United States)

    Madec, Sten; Casas, Jérôme; Barles, Guy; Suppo, Christelle

    2017-09-01

    Analytical modeling of predator-prey systems has shown that specialist natural enemies can slow, stop and even reverse pest invasions, assuming that the prey population displays a strong Allee effect in its growth. We aimed to formalize the conditions in which spatial biological control can be achieved by generalists, through an analytical approach based on reaction-diffusion equations. Using comparison principles, we obtain sufficient conditions for control and for invasion, based on scalar bistable partial differential equations. The ability of generalist predators to control prey populations with logistic growth lies in the bistable dynamics of the coupled system, rather than in the bistability of prey-only dynamics as observed for specialist predators attacking prey populations displaying Allee effects. As a consequence, prey control is predicted to be possible when space is considered in additional situations other than those identified without considering space. The reverse situation is also possible. None of these considerations apply to spatial predator-prey systems with specialist natural enemies.

  2. Experimental chaotic quantification in bistable vortex induced vibration systems

    Science.gov (United States)

    Huynh, B. H.; Tjahjowidodo, T.

    2017-02-01

    The study of energy harvesting by means of vortex induced vibration systems has been initiated a few years ago and it is considered to be potential as a low water current energy source. The energy harvester is realized by exposing an elastically supported blunt structure under water flow. However, it is realized that the system will only perform at a limited operating range (water flow) that is attributed to the resonance phenomenon that occurs only at a frequency that corresponds to the fluid flow. An introduction of nonlinear elements seems to be a prominent solution to overcome the problem. Among many nonlinear elements, a bistable spring is known to be able to improve the harvested power by a vortex induced vibrations (VIV) based energy converter at the low velocity water flows. However, it is also observed that chaotic vibrations will occur at different operating ranges that will erratically diminish the harvested power and cause a difficulty in controlling the system that is due to the unpredictability in motions of the VIV structure. In order to design a bistable VIV energy converter with improved harvested power and minimum negative effect of chaotic vibrations, the bifurcation map of the system for varying governing parameters is highly on demand. In this study, chaotic vibrations of a VIV energy converter enhanced by a bistable stiffness element are quantified in a wide range of the governing parameters, i.e. damping and bistable gap. Chaotic vibrations of the bistable VIV energy converter are simulated by utilization of a wake oscillator model and quantified based on the calculation of the Lyapunov exponent. Ultimately, a series of experiments of the system in a water tunnel, facilitated by a computer-based force-feedback testing platform, is carried out to validate the existence of chaotic responses. The main challenge in dealing with experimental data is in distinguishing chaotic response from noise-contaminated periodic responses as noise will smear

  3. Constant fan-in digital neural networks are VLSI-optimal

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1995-12-31

    The paper presents a theoretical proof revealing an intrinsic limitation of digital VLSI technology: its inability to cope with highly connected structures (e.g. neural networks). We are in fact able to prove that efficient digital VLSI implementations (known as VLSI-optimal when minimizing the AT{sup 2} complexity measure - A being the area of the chip, and T the delay for propagating the inputs to the outputs) of neural networks are achieved for small-constant fan-in gates. This result builds on quite recent ones dealing with a very close estimate of the area of neural networks when implemented by threshold gates, but it is also valid for classical Boolean gates. Limitations and open questions are presented in the conclusions.

  4. Memristive and neuromorphic behavior in a LixCoO2 nanobattery

    Science.gov (United States)

    Mai, V. H.; Moradpour, A.; Senzier, P. Auban; Pasquier, C.; Wang, K.; Rozenberg, M. J.; Giapintzakis, J.; Mihailescu, C. N.; Orfanidou, C. M.; Svoukis, E.; Breza, A.; Lioutas, Ch B.; Franger, S.; Revcolevschi, A.; Maroutian, T.; Lecoeur, P.; Aubert, P.; Agnus, G.; Salot, R.; Albouy, P. A.; Weil, R.; Alamarguy, D.; March, K.; Jomard, F.; Chrétien, P.; Schneegans, O.

    2015-01-01

    The phenomenon of resistive switching (RS), which was initially linked to non-volatile resistive memory applications, has recently also been associated with the concept of memristors, whose adjustable multilevel resistance characteristics open up unforeseen perspectives in cognitive computing. Herein, we demonstrate that the resistance states of LixCoO2 thin film-based metal-insulator-metal (MIM) solid-state cells can be tuned by sequential programming voltage pulses, and that these resistance states are dramatically dependent on the pulses input rate, hence emulating biological synapse plasticity. In addition, we identify the underlying electrochemical processes of RS in our MIM cells, which also reveal a nanobattery-like behavior, leading to the generation of electrical signals that bring an unprecedented new dimension to the connection between memristors and neuromorphic systems. Therefore, these LixCoO2-based MIM devices allow for a combination of possibilities, offering new perspectives of usage in nanoelectronics and bio-inspired neuromorphic circuits.

  5. Hierarchical Address Event Routing for Reconfigurable Large-Scale Neuromorphic Systems.

    Science.gov (United States)

    Park, Jongkil; Yu, Theodore; Joshi, Siddharth; Maier, Christoph; Cauwenberghs, Gert

    2017-10-01

    We present a hierarchical address-event routing (HiAER) architecture for scalable communication of neural and synaptic spike events between neuromorphic processors, implemented with five Xilinx Spartan-6 field-programmable gate arrays and four custom analog neuromophic integrated circuits serving 262k neurons and 262M synapses. The architecture extends the single-bus address-event representation protocol to a hierarchy of multiple nested buses, routing events across increasing scales of spatial distance. The HiAER protocol provides individually programmable axonal delay in addition to strength for each synapse, lending itself toward biologically plausible neural network architectures, and scales across a range of hierarchies suitable for multichip and multiboard systems in reconfigurable large-scale neuromorphic systems. We show approximately linear scaling of net global synaptic event throughput with number of routing nodes in the network, at 3.6×107 synaptic events per second per 16k-neuron node in the hierarchy.

  6. Real-time neuromorphic algorithms for inverse kinematics of redundant manipulators

    Science.gov (United States)

    Barhen, Jacob; Gulati, Sandeep; Zak, Michail

    1989-01-01

    The paper presents an efficient neuromorphic formulation to accurately solve the inverse kinematics problem for redundant manipulators. The approach involves a dynamical learning procedure based on a novel formalism in neural network theory: the concept of 'terminal' attractors. Topographically mapped terminal attractors are used to define a neural network whose synaptic elements can rapidly encapture the inverse kinematics transformations, and, subsequently generalize to compute joint-space coordinates required to achieve arbitrary end-effector configurations. Unlike prior neuromorphic implementations, this technique can also systematically exploit redundancy to optimize kinematic criteria, e.g., torque optimization. Simulations on 3-DOF and 7-DOF redundant manipulators, are used to validate the theoretical framework and illustrate its computational efficacy.

  7. A memristor crossbar array of titanium oxide for non-volatile memory and neuromorphic applications

    Science.gov (United States)

    Abbas, Haider; Abbas, Yawar; Truong, Son Ngoc; Min, Kyeong-Sik; Park, Mi Ra; Cho, Jongweon; Yoon, Tae-Sik; Kang, Chi Jung

    2017-06-01

    In this work 3 × 3 crossbar arrays of titanium oxide were fabricated and tested for non-volatile memory applications and neuromorphic pattern recognition. The non-volatile memory characteristics of the memristor were examined using retention tests for each memristor. In order to test neuromorphic pattern recognition, the memristor crossbar array was programmed to store '111', '100' and '010' at the first, second and third columns of the array, where '0' and '1' represent the high-resistance state (HRS) and low-resistance state (LRS), respectively. The three similar input patterns of '111', '100' and '010' were applied to the crossbar array, for pattern recognition. Using a twin memristor crossbar array mechanism all three input patterns were recognized.

  8. Applying Memristors Towards Low-Power, Dynamic Learning for Neuromorphic Applications

    Science.gov (United States)

    2017-03-01

    time speech recognition and spatio-temporal navigation. We present simulations of the mrDANNA system using physically integrated memristors (aka ReRAM...neuromorphic computation, which has gained widespread acceptance for its success in areas such as speech recognition , artificial intelligence, and...he top-perform and modified il a network w ionary optimiz rks which sol 2D navigatio Figure 1b. Futu d include thr speech recogn ted in hardwa PGAs

  9. Tunable low energy, compact and high performance neuromorphic circuit for spike-based synaptic plasticity.

    Directory of Open Access Journals (Sweden)

    Mostafa Rahimi Azghadi

    Full Text Available Cortical circuits in the brain have long been recognised for their information processing capabilities and have been studied both experimentally and theoretically via spiking neural networks. Neuromorphic engineers are primarily concerned with translating the computational capabilities of biological cortical circuits, using the Spiking Neural Network (SNN paradigm, into in silico applications that can mimic the behaviour and capabilities of real biological circuits/systems. These capabilities include low power consumption, compactness, and relevant dynamics. In this paper, we propose a new accelerated-time circuit that has several advantages over its previous neuromorphic counterparts in terms of compactness, power consumption, and capability to mimic the outcomes of biological experiments. The presented circuit simulation results demonstrate that, in comparing the new circuit to previous published synaptic plasticity circuits, reduced silicon area and lower energy consumption for processing each spike is achieved. In addition, it can be tuned in order to closely mimic the outcomes of various spike timing- and rate-based synaptic plasticity experiments. The proposed circuit is also investigated and compared to other designs in terms of tolerance to mismatch and process variation. Monte Carlo simulation results show that the proposed design is much more stable than its previous counterparts in terms of vulnerability to transistor mismatch, which is a significant challenge in analog neuromorphic design. All these features make the proposed design an ideal circuit for use in large scale SNNs, which aim at implementing neuromorphic systems with an inherent capability that can adapt to a continuously changing environment, thus leading to systems with significant learning and computational abilities.

  10. PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems.

    Science.gov (United States)

    Stefanini, Fabio; Neftci, Emre O; Sheik, Sadique; Indiveri, Giacomo

    2014-01-01

    Neuromorphic hardware offers an electronic substrate for the realization of asynchronous event-based sensory-motor systems and large-scale spiking neural network architectures. In order to characterize these systems, configure them, and carry out modeling experiments, it is often necessary to interface them to workstations. The software used for this purpose typically consists of a large monolithic block of code which is highly specific to the hardware setup used. While this approach can lead to highly integrated hardware/software systems, it hampers the development of modular and reconfigurable infrastructures thus preventing a rapid evolution of such systems. To alleviate this problem, we propose PyNCS, an open-source front-end for the definition of neural network models that is interfaced to the hardware through a set of Python Application Programming Interfaces (APIs). The design of PyNCS promotes modularity, portability and expandability and separates implementation from hardware description. The high-level front-end that comes with PyNCS includes tools to define neural network models as well as to create, monitor and analyze spiking data. Here we report the design philosophy behind the PyNCS framework and describe its implementation. We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carrying out a cognitive decision-making task involving state-dependent computation. PyNCS, already applicable to a wide range of existing spike-based neuromorphic setups, will accelerate the development of hybrid software/hardware neuromorphic systems, thanks to its code flexibility. The code is open-source and available online at https://github.com/inincs/pyNCS.

  11. Controllable spiking patterns in long-wavelength VCSELs for neuromorphic photonics systems

    CERN Document Server

    Hurtado, Antonio

    2015-01-01

    Multiple controllable spiking patterns are obtained in a 1310 nm Vertical Cavity Surface Emitting Laser (VCSEL) in response to induced perturbations and for two different cases of polarized optical injection, namely parallel and orthogonal. Achievement of reproducible spiking responses in VCSELs operating at the telecom wavelengths offers great promise for future uses of these devices in ultrafast neuromorphic photonic systems for non-traditional computing applications.

  12. An adaptable neuromorphic model of orientation selectivity based on floating gate dynamics

    Science.gov (United States)

    Gupta, Priti; Markan, C. M.

    2014-01-01

    The biggest challenge that the neuromorphic community faces today is to build systems that can be considered truly cognitive. Adaptation and self-organization are the two basic principles that underlie any cognitive function that the brain performs. If we can replicate this behavior in hardware, we move a step closer to our goal of having cognitive neuromorphic systems. Adaptive feature selectivity is a mechanism by which nature optimizes resources so as to have greater acuity for more abundant features. Developing neuromorphic feature maps can help design generic machines that can emulate this adaptive behavior. Most neuromorphic models that have attempted to build self-organizing systems, follow the approach of modeling abstract theoretical frameworks in hardware. While this is good from a modeling and analysis perspective, it may not lead to the most efficient hardware. On the other hand, exploiting hardware dynamics to build adaptive systems rather than forcing the hardware to behave like mathematical equations, seems to be a more robust methodology when it comes to developing actual hardware for real world applications. In this paper we use a novel time-staggered Winner Take All circuit, that exploits the adaptation dynamics of floating gate transistors, to model an adaptive cortical cell that demonstrates Orientation Selectivity, a well-known biological phenomenon observed in the visual cortex. The cell performs competitive learning, refining its weights in response to input patterns resembling different oriented bars, becoming selective to a particular oriented pattern. Different analysis performed on the cell such as orientation tuning, application of abnormal inputs, response to spatial frequency and periodic patterns reveal close similarity between our cell and its biological counterpart. Embedded in a RC grid, these cells interact diffusively exhibiting cluster formation, making way for adaptively building orientation selective maps in silicon. PMID

  13. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

    Directory of Open Access Journals (Sweden)

    Emre O. Neftci

    2017-06-01

    Full Text Available An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

  14. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines.

    Science.gov (United States)

    Neftci, Emre O; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

  15. Neuromorphic Kalman filter implementation in IBM’s TrueNorth

    Science.gov (United States)

    Carney, R.; Bouchard, K.; Calafiura, P.; Clark, D.; Donofrio, D.; Garcia-Sciveres, M.; Livezey, J.

    2017-10-01

    Following the advent of a post-Moore’s law field of computation, novel architectures continue to emerge. With composite, multi-million connection neuromorphic chips like IBM’s TrueNorth, neural engineering has now become a feasible technology in this novel computing paradigm. High Energy Physics experiments are continuously exploring new methods of computation and data handling, including neuromorphic, to support the growing challenges of the field and be prepared for future commodity computing trends. This work details the first instance of a Kalman filter implementation in IBM’s neuromorphic architecture, TrueNorth, for both parallel and serial spike trains. The implementation is tested on multiple simulated systems and its performance is evaluated with respect to an equivalent non-spiking Kalman filter. The limits of the implementation are explored whilst varying the size of weight and threshold registers, the number of spikes used to encode a state, size of neuron block for spatial encoding, and neuron potential reset schemes.

  16. Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware

    Directory of Open Access Journals (Sweden)

    Narayan eSrinivasa

    2015-12-01

    Full Text Available Neuromorphic hardware are designed by drawing inspiration from biology to overcome limitations of current computer architectures while forging the development of a new class of autonomous systems that are can exhibit adaptive behaviors.Many such designs in the recent past are capable of emulating large scale networks but avoid complexity in network dynamics by minimizing the number of dynamic variables that are supported and tunable in hardware. We believe that this is due to the lack of a clear understanding of how to design self-tuning complex systems. It has been widely demonstrated that criticality appears to be the default state of the brain and manifests in the form of spontaneous scale-invariant cascades of neural activity. Experiment, theory and recent models have shown that neuronal networks at criticality demonstrate optimal information transfer, learning and information processing capabilities that affect behavior. In this perspective article, we argue that understanding how large scale neuromorphic electronics can be designed to enable emergent adaptive behavior will require an understanding of how networks emulated by such hardware can self-tune local parameters to maintain criticality as a set-point. We believe that such capability will enable the design of truly scalable intelligent systems using neuromorphic hardware that embrace complexity in network dynamics rather than avoid it.

  17. A robust and scalable neuromorphic communication system by combining synaptic time multiplexing and MIMO-OFDM.

    Science.gov (United States)

    Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna

    2014-03-01

    This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.

  18. A digital implementation of neuron-astrocyte interaction for neuromorphic applications.

    Science.gov (United States)

    Nazari, Soheila; Faez, Karim; Amiri, Mahmood; Karami, Ehsan

    2015-06-01

    Recent neurophysiologic findings have shown that astrocytes play important roles in information processing and modulation of neuronal activity. Motivated by these findings, in the present research, a digital neuromorphic circuit to study neuron-astrocyte interaction is proposed. In this digital circuit, the firing dynamics of the neuron is described by Izhikevich model and the calcium dynamics of a single astrocyte is explained by a functional model introduced by Postnov and colleagues. For digital implementation of the neuron-astrocyte signaling, Single Constant Multiply (SCM) technique and several linear approximations are used for efficient low-cost hardware implementation on digital platforms. Using the proposed neuron-astrocyte circuit and based on the results of MATLAB simulations, hardware synthesis and FPGA implementation, it is demonstrated that the proposed digital astrocyte is able to change the firing patterns of the neuron through bidirectional communication. Utilizing the proposed digital circuit, it will be illustrated that information processing in synaptic clefts is strongly regulated by astrocyte. Moreover, our results suggest that the digital circuit of neuron-astrocyte crosstalk produces diverse neural responses and therefore enhances the information processing capabilities of the neuromorphic circuits. This is suitable for applications in reconfigurable neuromorphic devices which implement biologically brain circuits. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

    Science.gov (United States)

    Neftci, Emre O.; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning. PMID:28680387

  20. Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing

    Science.gov (United States)

    Sengupta, Abhronil; Roy, Kaushik

    2017-12-01

    Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform every day. This has recently resulted in a seismic shift in the field of computation where research efforts are being directed to develop a neurocomputer that attempts to mimic the human brain by nanoelectronic components and thereby harness its efficiency in recognition problems. Bridging the gap between neuroscience and nanoelectronics, this paper attempts to provide a review of the recent developments in the field of spintronic device based neuromorphic computing. Description of various spin-transfer torque mechanisms that can be potentially utilized for realizing device structures mimicking neural and synaptic functionalities is provided. A cross-layer perspective extending from the device to the circuit and system level is presented to envision the design of an All-Spin neuromorphic processor enabled with on-chip learning functionalities. Device-circuit-algorithm co-simulation framework calibrated to experimental results suggest that such All-Spin neuromorphic systems can potentially achieve almost two orders of magnitude energy improvement in comparison to state-of-the-art CMOS implementations.

  1. FPGA implementation of a configurable neuromorphic CPG-based locomotion controller.

    Science.gov (United States)

    Barron-Zambrano, Jose Hugo; Torres-Huitzil, Cesar

    2013-09-01

    Neuromorphic engineering is a discipline devoted to the design and development of computational hardware that mimics the characteristics and capabilities of neuro-biological systems. In recent years, neuromorphic hardware systems have been implemented using a hybrid approach incorporating digital hardware so as to provide flexibility and scalability at the cost of power efficiency and some biological realism. This paper proposes an FPGA-based neuromorphic-like embedded system on a chip to generate locomotion patterns of periodic rhythmic movements inspired by Central Pattern Generators (CPGs). The proposed implementation follows a top-down approach where modularity and hierarchy are two desirable features. The locomotion controller is based on CPG models to produce rhythmic locomotion patterns or gaits for legged robots such as quadrupeds and hexapods. The architecture is configurable and scalable for robots with either different morphologies or different degrees of freedom (DOFs). Experiments performed on a real robot are presented and discussed. The obtained results demonstrate that the CPG-based controller provides the necessary flexibility to generate different rhythmic patterns at run-time suitable for adaptable locomotion. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware.

    Science.gov (United States)

    Srinivasa, Narayan; Stepp, Nigel D; Cruz-Albrecht, Jose

    2015-01-01

    Neuromorphic hardware are designed by drawing inspiration from biology to overcome limitations of current computer architectures while forging the development of a new class of autonomous systems that can exhibit adaptive behaviors. Several designs in the recent past are capable of emulating large scale networks but avoid complexity in network dynamics by minimizing the number of dynamic variables that are supported and tunable in hardware. We believe that this is due to the lack of a clear understanding of how to design self-tuning complex systems. It has been widely demonstrated that criticality appears to be the default state of the brain and manifests in the form of spontaneous scale-invariant cascades of neural activity. Experiment, theory and recent models have shown that neuronal networks at criticality demonstrate optimal information transfer, learning and information processing capabilities that affect behavior. In this perspective article, we argue that understanding how large scale neuromorphic electronics can be designed to enable emergent adaptive behavior will require an understanding of how networks emulated by such hardware can self-tune local parameters to maintain criticality as a set-point. We believe that such capability will enable the design of truly scalable intelligent systems using neuromorphic hardware that embrace complexity in network dynamics rather than avoiding it.

  3. A parallel VLSI architecture for a digital filter using a number theoretic transform

    Science.gov (United States)

    Truong, T. K.; Reed, I. S.; Yeh, C. S.; Shao, H. M.

    1983-01-01

    The advantages of a very large scalee integration (VLSI) architecture for implementing a digital filter using fermat number transforms (FNT) are the following: It requires no multiplication. Only additions and bit rotations are needed. It alleviates the usual dynamic range limitation for long sequence FNT's. It utilizes the FNT and inverse FNT circuits 100% of the time. The lengths of the input data and filter sequences can be arbitraty and different. It is regular, simple, and expandable, and as a consequence suitable for VLSI implementation.

  4. Circuit design of VLSI for microelectronic coordinate-sensitive detector for material element analysis

    Directory of Open Access Journals (Sweden)

    Sidorenko V. P.

    2012-08-01

    Full Text Available There has been designed, manufactured and tested a VLSI providing as a part of the microelectronic coordinate-sensitive detector the simultaneous elemental analysis of all the principles of the substance. VLSI ensures the amplifier-converter response on receiving of 1,6.10–13 С negative charge to its input. Response speed of the microcircuit is at least 3 MHz in the counting mode and more than 4 MHz in the counter information read-out mode. The power consumption of the microcircuit is no more than 7 mA.

  5. Optical bistability in Er-Yb codoped phosphate glass microspheres at room temperature

    NARCIS (Netherlands)

    Warda, Jonathan M.; O'Shea, Danny G.; Shortt, Brian J.; Chormaic, Sile Nic

    2007-01-01

    We experimentally demonstrate optical bistability in Er(3+)-Yb(3+) phosphate glass microspheres at 295 K. Bistability is associated with both Er(3+) fluorescence and lasing behavior, and chromatic switching. The chromatic switching results from an intrinsic mechanism exploiting the thermal coupling

  6. Topical Meeting on Optical Bistability Held at Rochester, New York on 15-17 June 1983.

    Science.gov (United States)

    1983-01-01

    Beting Instabilities in Sistable Devices, J. A. Martin- bistability. Pereda and M. A. Muriel, Universidad Politecnica de Madrid , Ciudad Universitaria ... de Madrid , Ciudad Universitaria , Madrid , Poster ThB23 Spain. Instabliitles and Chaos In TV-Opticai Feeback, G. Hausler and N. Streibl, Physikalisches...TELECOMUNICACION UNIVERSIDAD POLITECNICA DE MADRID CTUIDAD INIVERSITARIA MADRID - 3 SPAIN Since the observation of optical bistability, several 3

  7. Bistable optical response of a nanoparticle heterodimer : Mechanism, phase diagram, and switching time

    NARCIS (Netherlands)

    Nugroho, Bintoro; Iskandar, Alexander; Malyshev, V.A.; Knoester, Jasper

    2013-01-01

    We conduct a theoretical study of the bistable optical response of a nanoparticle heterodimer comprised of a closely spaced semiconductor quantum dot and a metal nanoparticle. The bistable nature of the response results from the interplay between the quantum dot's optical nonlinearity and its

  8. Optical bistability and multistability in an open ladder-type atomic system

    Science.gov (United States)

    Asadpour, Seyyed Hossein; Hamedi, Hamid Reza; Rahimpour Soleimani, Hamid

    2013-05-01

    A novel scheme is proposed for controlling the optical bistability and multistability in an atomic system. In an open ladder-type three-level atomic system, it is shown that, by adjusting the ratio between atomic injections and exit rates from the cavity, the intensity threshold of optical bistability can be controlled. The effect of incoherent pumping field and spontaneously generated coherence (SGC) on optical bistability for different values of exit rates is also discussed. It is found that SGC makes the medium phase dependent, so the optical bistability and multistability threshold can be controlled via relative phase between applied fields. Moreover, it is shown that the optical bistability can be switched to optical multistability, which is favorable for the next generation of all-optical systems and quantum networks.

  9. VLSI implementation of a 2.8 Gevent/s packet based AER interface with routing and event sorting functionality

    Directory of Open Access Journals (Sweden)

    Stefan eScholze

    2011-10-01

    Full Text Available State-of-the-art large scale neuromorphic systems require sophisticated spike event communication between units of the neural network. We present a high-speed communication infrastructure for a waferscale neuromorphic system, based on application-specific neuromorphic communication ICs in an FPGA-maintained environment. The ICs implement configurable axonal delays, as required for certain types of dynamic processing or for emulating spike based learning among distant cortical areas. Measurements are presented which show the efficacy of these delays in influencing behaviour of neuromorphic benchmarks. The specialized, dedicated AER communication in most current systems requires separate, low-bandwidth configuration channels. In contrast, the configuration of the waferscale neuromorphic system is also handled by the digital packet-based pulse channel, which transmits configuration data at the full bandwidth otherwise used for pulse transmission. The overall so-called pulse communication subgroup (ICs and FPGA delivers a factor 25-50 more event transmission rate than other current neuromorphic communication infrastructures.

  10. Adaptive visual and auditory map alignment in barn owl superior colliculus and its neuromorphic implementation.

    Science.gov (United States)

    Huo, Juan; Murray, Alan; Wei, Dongqing

    2012-09-01

    Adaptation is one of the most important phenomena in biology. A young barn owl can adapt to imposed environmental changes, such as artificial visual distortion caused by wearing a prism. This adjustment process has been modeled mathematically and the model replicates the sensory map realignment of barn owl superior colliculus (SC) through axonogenesis and synaptogenesis. This allows the biological mechanism to be transferred to an artificial computing system and thereby imbue it with a new form of adaptability to the environment. The model is demonstrated in a real-time robot environment. Results of the experiments are compared with and without prism distortion of vision, and show improved adaptability for the robot. However, the computation speed of the embedded system in the robot is slow. A digital and analog mixed signal very-large-scale integration (VLSI) circuit has been fabricated to implement adaptive sensory pathway changes derived from the SC model at higher speed. VLSI experimental results are consistent with simulation results.

  11. Bistability and chaos in the Taylor-Green dynamo.

    Science.gov (United States)

    Yadav, Rakesh K; Verma, Mahendra K; Wahi, Pankaj

    2012-03-01

    Using direct numerical simulations, we study dynamo action under Taylor-Green forcing for a magnetic Prandtl number of 0.5. We observe bistability with weak- and strong-magnetic-field branches. Both the dynamo branches undergo subcritical dynamo transition. We also observe a host of dynamo states including constant, periodic, quasiperiodic, and chaotic magnetic fields. One of the chaotic states originates through a quasiperiodic route with phase locking, while the other chaotic attractor appears to follow the Newhouse-Ruelle-Takens route to chaos. We also observe intermittent transitions between quasiperiodic and chaotic states for a given Taylor-Green forcing.

  12. Optical bistability of graphene in the terahertz range

    DEFF Research Database (Denmark)

    Peres, N. M. R.; Bludov, Yu V.; Santos, Jaime E.

    2014-01-01

    We use an exact solution of the relaxation-time Boltzmann equation in a uniform ac electric field to describe the nonlinear optical response of graphene in the terahertz (THz) range. The cases of monolayer, bilayer, and ABA-stacked trilayer graphene are considered, and the monolayer species...... is shown to be the most appropriate one to exploit the nonlinear free electron response. We find that a single layer of graphene shows optical bistability in the THz range, within the electromagnetic power range attainable in practice. The current associated with the third harmonic generation is also...

  13. Toggling bistable atoms via mechanical switching of bond angle.

    Science.gov (United States)

    Sweetman, Adam; Jarvis, Sam; Danza, Rosanna; Bamidele, Joseph; Gangopadhyay, Subhashis; Shaw, Gordon A; Kantorovich, Lev; Moriarty, Philip

    2011-04-01

    We reversibly switch the state of a bistable atom by direct mechanical manipulation of bond angle using a dynamic force microscope. Individual buckled dimers at the Si(100) surface are flipped via the formation of a single covalent bond, actuating the smallest conceivable in-plane toggle switch (two atoms) via chemical force alone. The response of a given dimer to a flip event depends critically on both the local and nonlocal environment of the target atom-an important consideration for future atomic scale fabrication strategies. © 2011 American Physical Society

  14. Optical bistability in electrically coupled SOA-BJT devices

    Science.gov (United States)

    Costanzo-Caso, Pablo A.; Jin, Yiye; Gehl, Michael; Granieri, Sergio; Siahmakoun, Azad

    2010-06-01

    A novel optical bistable device based on an electrically coupled semiconductor optical amplifier (SOA) and a bipolar juncture transistor (BJT) is proposed and experimentally demonstrated. The measured switching time is about 0.9-1.0 us, mainly limited by the electrical capacitance of the SOA and the parasitic inductance of the electrical connections. However, the effects of parasitic components can be reduced employing current electronic-photonic integration circuits (EPIC). Numerical simulations confirm that for capacitance values in tens of femtofarads switching speed can reach tens of GHz.

  15. Spatial bistability generates hunchback expression sharpness in the Drosophila embryo.

    Directory of Open Access Journals (Sweden)

    Francisco J P Lopes

    2008-09-01

    Full Text Available During embryonic development, the positional information provided by concentration gradients of maternal factors directs pattern formation by providing spatially dependent cues for gene expression. In the fruit fly, Drosophila melanogaster, a classic example of this is the sharp on-off activation of the hunchback (hb gene at midembryo, in response to local concentrations of the smooth anterior-posterior Bicoid (Bcd gradient. The regulatory region for hb contains multiple binding sites for the Bcd protein as well as multiple binding sites for the Hb protein. Some previous studies have suggested that Bcd is sufficient for properly sharpened Hb expression, yet other evidence suggests a need for additional regulation. We experimentally quantified the dynamics of hb gene expression in flies that were wild-type, were mutant for hb self-regulation or Bcd binding, or contained an artificial promoter construct consisting of six Bcd and two Hb sites. In addition to these experiments, we developed a reaction-diffusion model of hb transcription, with Bcd cooperative binding and hb self-regulation, and used Zero Eigenvalue Analysis to look for multiple stationary states in the reaction network. Our model reproduces the hb developmental dynamics and correctly predicts the mutant patterns. Analysis of our model indicates that the Hb sharpness can be produced by spatial bistability, in which hb self-regulation produces two stable levels of expression. In the absence of self-regulation, the bistable behavior vanishes and Hb sharpness is disrupted. Bcd cooperative binding affects the position where bistability occurs but is not itself sufficient for a sharp Hb pattern. Our results show that the control of Hb sharpness and positioning, by hb self-regulation and Bcd cooperativity, respectively, are separate processes that can be altered independently. Our model, which matches the changes in Hb position and sharpness observed in different experiments, provides a

  16. Application of the Asymptotic Taylor Expansion Method to Bistable Potentials

    Directory of Open Access Journals (Sweden)

    Okan Ozer

    2013-01-01

    Full Text Available A recent method called asymptotic Taylor expansion (ATEM is applied to determine the analytical expression for eigenfunctions and numerical results for eigenvalues of the Schrödinger equation for the bistable potentials. Optimal truncation of the Taylor series gives a best possible analytical expression for eigenfunctions and numerical results for eigenvalues. It is shown that the results are obtained by a simple algorithm constructed for a computer system using symbolic or numerical calculation. It is observed that ATEM produces excellent results consistent with the existing literature.

  17. Optical bistabilities of higher harmonics: Inhomogeneous and transverse effects

    Energy Technology Data Exchange (ETDEWEB)

    Hassan, S.S., E-mail: Shoukryhassan@hotmail.com [Department of Mathematics, College of Science, University of Bahrain, P.O. Box 32038 (Bahrain); Manchester Metropolitan University, Dept. of Computing, Maths. and Digital Technology, Manchester M1 5GD (United Kingdom); Sharaby, Y.A., E-mail: Yasser_Sharaby@hotmail.com [Department of Physics, Faculty of Science, Suez Canal University, Suez (Egypt); Ali, M.F.M., E-mail: dr.mona.fathy@hotmail.com [Department of Mathematics: Faculty of Science, Ain Shams University, Cairo (Egypt); Joshi, A., E-mail: ajoshi@eiu.edu [Department of Physics, Eastern Illinois University, Charleston, IL 61920 (United States)

    2012-10-15

    The steady state behavior of optical bistable system in a ring cavity with transverse field variations and inhomogeneousely broadened two-level atoms is investigated outside the rotating wave approximation (RWA). Analytical and numerical investigation is presented for different cases of transverse field variations with Lorentzian or Gaussian line widths. When both (transverse and inhomogeneous) features taken into account, the first harmonic output field component outside the RWA exhibits a one-way switching down processes (butterfly OB) or reversed (clockwise) OB behavior, depending on the atomic linewidth shape.

  18. VLSI top-down design based on the separation of hierarchies

    NARCIS (Netherlands)

    Spaanenburg, L.; Broekema, A.; Leenstra, J.; Huys, C.

    1986-01-01

    Despite the presence of structure, interactions between the three views on VLSI design still lead to lengthy iterations. By separating the hierarchies for the respective views, the interactions are reduced. This separated hierarchy allows top-down design with functional abstractions as exemplified

  19. Synthesis of on-chip control circuits for mVLSI biochips

    DEFF Research Database (Denmark)

    Potluri, Seetal; Schneider, Alexander Rüdiger; Hørslev-Petersen, Martin

    2017-01-01

    them to laboratory environments. To address this issue, researchers have proposed methods to reduce the number of offchip pressure sources, through integration of on-chip pneumatic control logic circuits fabricated using three-layer monolithic membrane valve technology. Traditionally, mVLSI biochip...... applied to generate biochip layouts with integrated on-chip pneumatic control....

  20. Multiple Bistability in Quinonoid-Bridged Diiron(II) Complexes: Influence of Bridge Symmetry on Bistable Properties.

    Science.gov (United States)

    van der Meer, Margarethe; Rechkemmer, Yvonne; Breitgoff, Frauke D; Marx, Raphael; Neugebauer, Petr; Frank, Uta; van Slageren, Joris; Sarkar, Biprajit

    2016-11-21

    Quinonoid bridges are well-suited for generating dinuclear assemblies that might display various bistable properties. In this contribution we present two diiron(II) complexes where the iron(II) centers are either bridged by the doubly deprotonated form of a symmetrically substituted quinonoid bridge, 2,5-bis[4-(isopropyl)anilino]-1,4-benzoquinone (H2L2') with a [O,N,O,N] donor set, or with the doubly deprotonated form of an unsymmetrically substituted quinonoid bridge, 2-[4-(isopropyl)anilino]-5-hydroxy-1,4-benzoquinone (H2L5') with a [O,O,O,N] donor set. Both complexes display temperature-induced spin crossover (SCO). The nature of the SCO is strongly dependent on the bridging ligand, with only the complex with the [O,O,O,N] donor set displaying a prominent hysteresis loop of about 55 K. Importantly, only the latter complex also shows a pronounced light-induced spin state change. Furthermore, both complexes can be oxidized to the mixed-valent iron(II)-iron(III) form, and the nature of the bridge determines the Robin and Day classification of these forms. Both complexes have been probed by a battery of electrochemical, spectroscopic, and magnetic methods, and this combined approach is used to shed light on the electronic structures of the complexes and on bistability. The results presented here thus show the potential of using the relatively new class of unsymmetrically substituted bridging quinonoid ligands for generating intriguing bistable properties and for performing site-specific magnetic switching.

  1. Magnetic actuation and transition shapes of a bistable spherical cap

    Directory of Open Access Journals (Sweden)

    E.G. Loukaides

    2014-10-01

    Full Text Available Multistable shells have been proposed for a variety of applications; however, their actuation is almost exclusively addressed through embedded piezoelectric patches. Additional actuation techniques are needed for applications requiring high strains or where remote actuation is desirable. Part of the reason for the lack of research in this area is the absence of appropriate models describing the detailed deformation and energetics of such shells. This work presents a bistable spherical cap made of iron carbonyl-infused polydimethylsiloxane. The magnetizable structure can be actuated remotely through permanent magnets while the transition is recorded with a high-speed camera. Moreover, the experiment is reproduced in a finite element (FE dynamic model for comparison with the physical observations. High-speed footage of the physical cap inversion together with the FE modeling gives valuable insight on preferable intermediate geometries. Both methods return similar values for the magnetic field strength required for the snap-through. High-strain multistable spherical cap transformation is demonstrated, based on informed material selection. We discover that non-axisymmetric transition shapes are preferred in intermediate geometries by bistable spherical caps. We develop the methods for design and analysis of such actuators, including the feasibility of remote actuation methods for multistable shells.

  2. Optical bi-stable shutter development/improvement

    Science.gov (United States)

    Lizon, J. L.; Haddad, N.; Castillo, R.

    2012-09-01

    Two of the VLT instruments (Giraffe and VIMOS) are using the large magnetic E/150 from Prontor (with an aperture diameter of 150 mm). As we were facing an unacceptable number of failures with this component some improvement plan was discussed already in 2004. The final decision for starting this program was conditioned by the decision from the constructor to stop the production. The opportunity was taken to improve the design building a fully bi-stable mechanism in order to reduce the thermal dissipation. The project was developed in collaboration between the two main ESO sites doing the best use of the manpower and of the technical capability available at the two centers. The project took advantage of the laser Mask Manufacturing Unit and the invar sheets used to prepare the VIMOS MOS mask to fabricate the shutter petals. Our paper describes the development including the intensive and long optimization period. To conclude this optimization we proceed with a long life test on two units. These units have demonstrate a very high level of reliability (up to 100 000 cycles without failure which can be estimated to an equivalent 6 years of operation of the instrument) A new bi-stable shutter driver and controller have also been developed. Some of the highlights of this unit are the fully configurable coil driving parameters, usage of braking strategy to dump mechanical vibration and reduce mechanical wearing, configurable usage of OPEN and CLOSE sensors, non volatile storage of parameters, user friendly front panel interface.

  3. Control and characterization of a bistable laminate generated with piezoelectricity

    Science.gov (United States)

    Lee, Andrew J.; Moosavian, Amin; Inman, Daniel J.

    2017-08-01

    Extensive research has been conducted on utilizing smart materials such as piezoelectric and shape memory alloy actuators to induce snap through of bistable structures for morphing applications. However, there has only been limited success in initiating snap through from both stable states due to the lack of actuation authority. A novel solution in the form of a piezoelectrically generated bistable laminate consisting of only macro fiber composites (MFC), allowing complete configuration control without any external assistance, is explored in detail here. Specifically, this paper presents the full analytical, computational, and experimental results of the laminate’s design, geometry, bifurcation behavior, and snap through capability. By bonding two actuated MFCs in a [0MFC/90MFC]T layup and releasing the voltage post cure, piezoelectric strain anisotropy and the resulting in-plane residual stresses yield two statically stable states that are cylindrically shaped. The analytical model uses the Rayleigh-Ritz minimization of total potential energy and finite element analysis is implemented in MSC Nastran. The [0MFC/90MFC]T laminate is then manufactured and experimentally characterized for model validation. This paper demonstrates the adaptive laminate’s unassisted forward and reverse snap through capability enabled by the efficiencies gained from simultaneously being the actuator and the primary structure.

  4. Designing a stochastic genetic switch by coupling chaos and bistability

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Xiang [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Ouyang, Qi [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Center for Quantitative Biology, Peking University, Beijing 100871 (China); The Peking-Tsinghua Center for Life Sciences, Beijing 100871 (China); Wang, Hongli, E-mail: hlwang@pku.edu.cn [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Center for Quantitative Biology, Peking University, Beijing 100871 (China)

    2015-11-15

    In stem cell differentiation, a pluripotent stem cell becomes progressively specialized and generates specific cell types through a series of epigenetic processes. How cells can precisely determine their fate in a fluctuating environment is a currently unsolved problem. In this paper, we suggest an abstract gene regulatory network to describe mathematically the differentiation phenomenon featuring stochasticity, divergent cell fates, and robustness. The network consists of three functional motifs: an upstream chaotic motif, a buffering motif of incoherent feed forward loop capable of generating a pulse, and a downstream motif which is bistable. The dynamic behavior is typically a transient chaos with fractal basin boundaries. The trajectories take transiently chaotic journeys before divergently settling down to the bistable states. The ratio of the probability that the high state is achieved to the probability that the low state is reached can maintain a constant in a population of cells with varied molecular fluctuations. The ratio can be turned up or down when proper parameters are adjusted. The model suggests a possible mechanism for the robustness against fluctuations that is prominently featured in pluripotent cell differentiations and developmental phenomena.

  5. Advanced plasma etching processes for dielectric materials in VLSI technology

    Science.gov (United States)

    Wang, Juan Juan

    Manufacturable plasma etching processes for dielectric materials have played an important role in the Integrated Circuits (IC) industry in recent decades. Dielectric materials such as SiO2 and SiN are widely used to electrically isolate the active device regions (like the gate, source and drain from the first level of metallic interconnects) and to isolate different metallic interconnect levels from each other. However, development of new state-of-the-art etching processes is urgently needed for higher aspect ratio (oxide depth/hole diameter---6:1) in Very Large Scale Integrated (VLSI) circuits technology. The smaller features can provide greater packing density of devices on a single chip and greater number of chips on a single wafer. This dissertation focuses on understanding and optimizing of several key aspects of etching processes for dielectric materials. The challenges are how to get higher selectivity of oxide/Si for contact and oxide/TiN for vias; tight Critical Dimension (CD) control; wide process margin (enough over-etch); uniformity and repeatability. By exploring all of the parameters for the plasma etch process, the key variables are found and studied extensively. The parameters investigated here are Power, Pressure, Gas ratio, and Temperature. In particular, the novel gases such as C4F8, C5F8, and C4F6 were studied in order to meet the requirements of the design rules. We also studied CF4 that is used frequently for dielectric material etching in the industry. Advanced etch equipment was used for the above applications: the medium-density plasma tools (like Magnet-Enhanced Reactive Ion Etching (MERIE) tool) and the high-density plasma tools. By applying the Design of Experiments (DOE) method, we found the key factors needed to predict the trend of the etch process (such as how to increase the etch rates, selectivity, etc.; and how to control the stability of the etch process). We used JMP software to analyze the DOE data. The characterization of the

  6. A Bistable Switch and Anatomical Site Control Vibrio cholerae Virulence Gene Expression in the Intestine

    DEFF Research Database (Denmark)

    Nielsen, Alex Toftgaard; Dolganov, N. A.; Rasmussen, Thomas

    2010-01-01

    master regulator of virulence gene expression also exhibited the bifurcation phenotype. The bifurcation phenotype was found to be reversible, epigenetic and to persist after removal of bicarbonate, features consistent with bistable switches. The bistable switch requires the positive-feedback circuit...... controlling ToxT expression and formation of the CRP-cAMP complex during entry into stationary phase. Key features of this bistable switch also were demonstrated in vivo, where striking heterogeneity in tcpA expression was observed in luminal fluid in later stages of the infection. When this fluid was diluted...

  7. Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware

    Science.gov (United States)

    Knight, James C.; Tully, Philip J.; Kaplan, Bernhard A.; Lansner, Anders; Furber, Steve B.

    2016-01-01

    SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 2.0 × 104 neurons and 5.1 × 107 plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately 45× more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models. PMID:27092061

  8. Large-scale simulations of plastic neural networks on neuromorphic hardware

    Directory of Open Access Journals (Sweden)

    James Courtney Knight

    2016-04-01

    Full Text Available SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 20000 neurons and 51200000 plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models.

  9. A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems.

    Science.gov (United States)

    Brüderle, Daniel; Petrovici, Mihai A; Vogginger, Bernhard; Ehrlich, Matthias; Pfeil, Thomas; Millner, Sebastian; Grübl, Andreas; Wendt, Karsten; Müller, Eric; Schwartz, Marc-Olivier; de Oliveira, Dan Husmann; Jeltsch, Sebastian; Fieres, Johannes; Schilling, Moritz; Müller, Paul; Breitwieser, Oliver; Petkov, Venelin; Muller, Lyle; Davison, Andrew P; Krishnamurthy, Pradeep; Kremkow, Jens; Lundqvist, Mikael; Muller, Eilif; Partzsch, Johannes; Scholze, Stefan; Zühl, Lukas; Mayr, Christian; Destexhe, Alain; Diesmann, Markus; Potjans, Tobias C; Lansner, Anders; Schüffny, René; Schemmel, Johannes; Meier, Karlheinz

    2011-05-01

    In this article, we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results.

  10. An Asynchronous Low Power and High Performance VLSI Architecture for Viterbi Decoder Implemented with Quasi Delay Insensitive Templates

    OpenAIRE

    T. Kalavathi Devi; Sakthivel Palaniappan

    2015-01-01

    Convolutional codes are comprehensively used as Forward Error Correction (FEC) codes in digital communication systems. For decoding of convolutional codes at the receiver end, Viterbi decoder is often used to have high priority. This decoder meets the demand of high speed and low power. At present, the design of a competent system in Very Large Scale Integration (VLSI) technology requires these VLSI parameters to be finely defined. The proposed asynchronous method focuses on reducing the powe...

  11. Controllable spiking patterns in long-wavelength vertical cavity surface emitting lasers for neuromorphic photonics systems

    Energy Technology Data Exchange (ETDEWEB)

    Hurtado, Antonio, E-mail: antonio.hurtado@strath.ac.uk [Institute of Photonics, SUPA Department of Physics, University of Strathclyde, TIC Centre, 99 George Street, Glasgow G1 1RD (United Kingdom); Javaloyes, Julien [Departament de Fisica, Universitat de les Illes Balears, c/Valldemossa km 7.5, 07122 Mallorca (Spain)

    2015-12-14

    Multiple controllable spiking patterns are achieved in a 1310 nm Vertical-Cavity Surface Emitting Laser (VCSEL) in response to induced perturbations and for two different cases of polarized optical injection, namely, parallel and orthogonal. Furthermore, reproducible spiking responses are demonstrated experimentally at sub-nanosecond speed resolution and with a controlled number of spikes fired. This work opens therefore exciting research avenues for the use of VCSELs in ultrafast neuromorphic photonic systems for non-traditional computing applications, such as all-optical binary-to-spiking format conversion and spiking information encoding.

  12. Neuromorphic Computing, Architectures, Models, and Applications. A Beyond-CMOS Approach to Future Computing, June 29-July 1, 2016, Oak Ridge, TN

    Energy Technology Data Exchange (ETDEWEB)

    Potok, Thomas [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Schuman, Catherine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Patton, Robert [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hylton, Todd [Brain Corporation, San Diego, CA (United States); Li, Hai [Univ. of Pittsburgh, PA (United States); Pino, Robinson [US Dept. of Energy, Washington, DC (United States)

    2016-12-31

    The White House and Department of Energy have been instrumental in driving the development of a neuromorphic computing program to help the United States continue its lead in basic research into (1) Beyond Exascale—high performance computing beyond Moore’s Law and von Neumann architectures, (2) Scientific Discovery—new paradigms for understanding increasingly large and complex scientific data, and (3) Emerging Architectures—assessing the potential of neuromorphic and quantum architectures. Neuromorphic computing spans a broad range of scientific disciplines from materials science to devices, to computer science, to neuroscience, all of which are required to solve the neuromorphic computing grand challenge. In our workshop we focus on the computer science aspects, specifically from a neuromorphic device through an application. Neuromorphic devices present a very different paradigm to the computer science community from traditional von Neumann architectures, which raises six major questions about building a neuromorphic application from the device level. We used these fundamental questions to organize the workshop program and to direct the workshop panels and discussions. From the white papers, presentations, panels, and discussions, there emerged several recommendations on how to proceed.

  13. Synaptic Bistability Due to Nucleation and Evaporation of Receptor Clusters

    KAUST Repository

    Burlakov, V. M.

    2012-01-10

    We introduce a bistability mechanism for long-term synaptic plasticity based on switching between two metastable states that contain significantly different numbers of synaptic receptors. One state is characterized by a two-dimensional gas of mobile interacting receptors and is stabilized against clustering by a high nucleation barrier. The other state contains a receptor gas in equilibrium with a large cluster of immobile receptors, which is stabilized by the turnover rate of receptors into and out of the synapse. Transitions between the two states can be initiated by either an increase (potentiation) or a decrease (depotentiation) of the net receptor flux into the synapse. This changes the saturation level of the receptor gas and triggers nucleation or evaporation of receptor clusters. © 2012 American Physical Society.

  14. On the Functional Relevance of Frontal Cortex for Passive and Voluntarily Controlled Bistable Vision

    NARCIS (Netherlands)

    de Graaf, T.A.; de Jong, M.C.|info:eu-repo/dai/nl/314130578; Goebel, R.; van Ee, R.|info:eu-repo/dai/nl/107286912; Sack, A.T.

    2011-01-01

    In bistable vision, one constant ambiguous stimulus leads to 2 alternating conscious percepts. This perceptual switching occurs spontaneously but can also be influenced through voluntary control. Neuroimaging studies have reported that frontal regions are activated during spontaneous perceptual

  15. Oceanic hindcast simulations at high resolution suggest that the Atlantic MOC is bistable

    Science.gov (United States)

    Deshayes, J.; TréGuier, A.-M.; Barnier, B.; Lecointre, A.; Le Sommer, J.; Molines, J.-M.; Penduff, T.; Bourdallé-Badie, R.; Drillet, Y.; Garric, G.; Benshila, R.; Madec, G.; Biastoch, A.; Böning, C. W.; Scheinert, M.; Coward, A. C.; Hirschi, J. J.-M.

    2013-06-01

    All climate models predict a freshening of the North Atlantic at high latitude that may induce an abrupt change of the Atlantic Meridional Overturning Circulation (hereafter AMOC) if it resides in the bistable regime, where both a strong and a weak state coexist. The latter remains uncertain as there is no consensus among observations and ocean reanalyses, where the AMOC is bistable, versus most climate models that reproduce a mono-stable strong AMOC. A series of four hindcast simulations of the global ocean at 1/12° resolution, which is presently unique, are used to diagnose freshwater transport by the AMOC in the South Atlantic, an indicator of AMOC bistability. In all simulations, the AMOC resides in the bistable regime: it exports freshwater southward in the South Atlantic, implying a positive salt advection feedback that would act to amplify a decreasing trend in subarctic deep water formation as projected in climate scenarios.

  16. Electrical and optical switching in the bistable regime of an electrically injected polariton laser

    Science.gov (United States)

    Klaas, M.; Sigurdsson, H.; Liew, T. C. H.; Klembt, S.; Amthor, M.; Hartmann, F.; Worschech, L.; Schneider, C.; Höfling, S.

    2017-07-01

    We report on electrically and nonresonant optically induced switching in the bistable regime of an electrically pumped polariton laser. Electrical switching effects can be observed by adding controlled noise in the electrical pump of the system. Noise is expected to influence the hysteresis characteristics of a bistable device and determines its application robustness. We find that the hysteresis width decreases symmetrically with a linear dependency until we observe a quenching of the bistability at a certain noise level and the output of the system becomes monostable. Furthermore, we explore the possibility to switch between the two bistable branches by a nonresonant optical pulse. Our experimental findings can be described by a set of rate equations modeling the population dynamics with additional noise terms.

  17. Optical bistability via Josephson coupling energy in a superconducting quantum circuit

    Science.gov (United States)

    Hamedi, Hamid Reza

    2014-11-01

    A novel configuration is proposed to study optical bistability (OB) and optical multistability (OM) in a superconducting quantum circuit with a tunable V-type artificial molecule constructed by two superconducting Josephson charge qubits coupled with each other through a superconducting quantum interference device. We find that the ratio of the Josephson coupling energy to the capacitive coupling strength has a significant impact on creating optical bistability. The influence of other system parameters on bistable behavior of the artificial medium is then discussed. In particular, it is found that applying an incoherent pumping field can noticeably reduce the bistable threshold. We also realize a switch from OB to OM through proper tuning of detuning parameters. The controllability of OB and OM of this artificial molecule may be useful in building logic-gate devices for optical computing and quantum information processing and provide some new possibilities for solid-state quantum information science.

  18. Melanopsin bistability: a fly's eye technology in the human retina.

    Directory of Open Access Journals (Sweden)

    Ludovic S Mure

    Full Text Available In addition to rods and cones, the human retina contains light-sensitive ganglion cells that express melanopsin, a photopigment with signal transduction mechanisms similar to that of invertebrate rhabdomeric photopigments (IRP. Like fly rhodopsins, melanopsin acts as a dual-state photosensitive flip-flop in which light drives both phototransduction responses and chromophore photoregeneration that bestows independence from the retinoid cycle required by rods and cones to regenerate photoresponsiveness following bleaching by light. To explore the hypothesis that melanopsin in humans expresses the properties of a bistable photopigment in vivo we used the pupillary light reflex (PLR as a tool but with methods designed to study invertebrate photoreceptors. We show that the pupil only attains a fully stabilized state of constriction after several minutes of light exposure, a feature that is consistent with typical IRP photoequilibrium spectra. We further demonstrate that previous exposure to long wavelength light increases, while short wavelength light decreases the amplitude of pupil constriction, a fundamental property of IRP difference spectra. Modelling these responses to invertebrate photopigment templates yields two putative spectra for the underlying R and M photopigment states with peaks at 481 nm and 587 nm respectively. Furthermore, this bistable mechanism may confer a novel form of "photic memory" since information of prior light conditions is retained and shapes subsequent responses to light. These results suggest that the human retina exploits fly-like photoreceptive mechanisms that are potentially important for the modulation of non-visual responses to light and highlights the ubiquitous nature of photoswitchable photosensors across living organisms.

  19. Optimal Size for Maximal Energy Efficiency in Information Processing of Biological Systems Due to Bistability

    OpenAIRE

    Zhang, Chi; Liu, Li-wei; Wang, Long-Fei; Yue, Yuan; Yu, Lian-Chun

    2015-01-01

    Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this paper, we calculated the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculated the mutual information, energy cost, and energy efficiency of an array of these bistable units. We found that the optimal number of units c...

  20. A predictive coding account of bistable perception - a model-based fMRI study.

    Science.gov (United States)

    Weilnhammer, Veith; Stuke, Heiner; Hesselmann, Guido; Sterzer, Philipp; Schmack, Katharina

    2017-05-01

    In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept. Data simulations revealed close similarities between the model's predictions and key temporal characteristics of perceptual bistability, indicating that the model was able to reproduce bistable perception. Fitting the predictive coding model to behavioural data from an fMRI-experiment on bistable perception, we found a correlation across participants between the model parameter encoding perceptual stabilization and the behaviourally measured frequency of perceptual transitions, corroborating that the model successfully accounted for participants' perception. Formal model comparison with established models of bistable perception based on mutual inhibition and adaptation, noise or a combination of adaptation and noise was used for the validation of the predictive coding model against the established models. Most importantly, model-based analyses of the fMRI data revealed that prediction error time-courses derived from the predictive coding model correlated with neural signal time-courses in bilateral inferior frontal gyri and anterior insulae. Voxel-wise model selection indicated a superiority of the predictive coding model over conventional analysis approaches in explaining neural activity in these frontal areas, suggesting that frontal cortex encodes prediction errors that mediate endogenous perceptual transitions in bistable perception. Taken together, our current work

  1. American Sign Language Alphabet Recognition Using a Neuromorphic Sensor and an Artificial Neural Network.

    Science.gov (United States)

    Rivera-Acosta, Miguel; Ortega-Cisneros, Susana; Rivera, Jorge; Sandoval-Ibarra, Federico

    2017-09-22

    This paper reports the design and analysis of an American Sign Language (ASL) alphabet translation system implemented in hardware using a Field-Programmable Gate Array. The system process consists of three stages, the first being the communication with the neuromorphic camera (also called Dynamic Vision Sensor, DVS) sensor using the Universal Serial Bus protocol. The feature extraction of the events generated by the DVS is the second part of the process, consisting of a presentation of the digital image processing algorithms developed in software, which aim to reduce redundant information and prepare the data for the third stage. The last stage of the system process is the classification of the ASL alphabet, achieved with a single artificial neural network implemented in digital hardware for higher speed. The overall result is the development of a classification system using the ASL signs contour, fully implemented in a reconfigurable device. The experimental results consist of a comparative analysis of the recognition rate among the alphabet signs using the neuromorphic camera in order to prove the proper operation of the digital image processing algorithms. In the experiments performed with 720 samples of 24 signs, a recognition accuracy of 79.58% was obtained.

  2. Memristive and neuromorphic behavior in a Li(x)CoO2 nanobattery.

    Science.gov (United States)

    Mai, V H; Moradpour, A; Senzier, P Auban; Pasquier, C; Wang, K; Rozenberg, M J; Giapintzakis, J; Mihailescu, C N; Orfanidou, C M; Svoukis, E; Breza, A; Lioutas, Ch B; Franger, S; Revcolevschi, A; Maroutian, T; Lecoeur, P; Aubert, P; Agnus, G; Salot, R; Albouy, P A; Weil, R; Alamarguy, D; March, K; Jomard, F; Chrétien, P; Schneegans, O

    2015-01-14

    The phenomenon of resistive switching (RS), which was initially linked to non-volatile resistive memory applications, has recently also been associated with the concept of memristors, whose adjustable multilevel resistance characteristics open up unforeseen perspectives in cognitive computing. Herein, we demonstrate that the resistance states of Li(x)CoO2 thin film-based metal-insulator-metal (MIM) solid-state cells can be tuned by sequential programming voltage pulses, and that these resistance states are dramatically dependent on the pulses input rate, hence emulating biological synapse plasticity. In addition, we identify the underlying electrochemical processes of RS in our MIM cells, which also reveal a nanobattery-like behavior, leading to the generation of electrical signals that bring an unprecedented new dimension to the connection between memristors and neuromorphic systems. Therefore, these LixCoO2-based MIM devices allow for a combination of possibilities, offering new perspectives of usage in nanoelectronics and bio-inspired neuromorphic circuits.

  3. On-demand nanodevice with electrical and neuromorphic multifunction realized by local ion migration.

    Science.gov (United States)

    Yang, Rui; Terabe, Kazuya; Liu, Guangqiang; Tsuruoka, Tohru; Hasegawa, Tsuyoshi; Gimzewski, James K; Aono, Masakazu

    2012-11-27

    A potential route to extend Moore's law beyond the physical limits of existing materials and device architectures is to achieve nanotechnology breakthroughs in materials and device concepts. Here, we discuss an on-demand WO(3-x)-based nanoionic device where electrical and neuromorphic multifunctions are realized through externally induced local migration of oxygen ions. The device is found to possess a wide range of time scales of memorization, resistance switching, and rectification varying from volatile to permanent in a single device, and these can furthermore be realizable in both two- or three-terminal systems. The gradually changing volatile and nonvolatile resistance states are experimentally demonstrated to mimic the human brain's forgetting process for short-term memory and long-term memory.We propose this nanoionic device with its on-demand electrical and neuromorphic multifunction has a unique paradigm shifting potential for the fabrication of configurable circuits, analog memories, digital-neural fused networks, and more in one device architecture.

  4. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

    Science.gov (United States)

    Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

    2016-01-01

    Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure–Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods. PMID:27529225

  5. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

    Directory of Open Access Journals (Sweden)

    Lucas Antón Pastur-Romay

    2016-08-01

    Full Text Available Over the past decade, Deep Artificial Neural Networks (DNNs have become the state-of-the-art algorithms in Machine Learning (ML, speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs. All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS, Quantitative Structure–Activity Relationship (QSAR research, protein structure prediction and genomics (and other omics data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

  6. American Sign Language Alphabet Recognition Using a Neuromorphic Sensor and an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Miguel Rivera-Acosta

    2017-09-01

    Full Text Available This paper reports the design and analysis of an American Sign Language (ASL alphabet translation system implemented in hardware using a Field-Programmable Gate Array. The system process consists of three stages, the first being the communication with the neuromorphic camera (also called Dynamic Vision Sensor, DVS sensor using the Universal Serial Bus protocol. The feature extraction of the events generated by the DVS is the second part of the process, consisting of a presentation of the digital image processing algorithms developed in software, which aim to reduce redundant information and prepare the data for the third stage. The last stage of the system process is the classification of the ASL alphabet, achieved with a single artificial neural network implemented in digital hardware for higher speed. The overall result is the development of a classification system using the ASL signs contour, fully implemented in a reconfigurable device. The experimental results consist of a comparative analysis of the recognition rate among the alphabet signs using the neuromorphic camera in order to prove the proper operation of the digital image processing algorithms. In the experiments performed with 720 samples of 24 signs, a recognition accuracy of 79.58% was obtained.

  7. DEVELOPMENT OF NEUROMORPHIC SIFT OPERATOR WITH APPLICATION TO HIGH SPEED IMAGE MATCHING

    Directory of Open Access Journals (Sweden)

    M. Shankayi

    2015-12-01

    Full Text Available There was always a speed/accuracy challenge in photogrammetric mapping process, including feature detection and matching. Most of the researches have improved algorithm's speed with simplifications or software modifications which increase the accuracy of the image matching process. This research tries to improve speed without enhancing the accuracy of the same algorithm using Neuromorphic techniques. In this research we have developed a general design of a Neuromorphic ASIC to handle algorithms such as SIFT. We also have investigated neural assignment in each step of the SIFT algorithm. With a rough estimation based on delay of the used elements including MAC and comparator, we have estimated the resulting chip's performance for 3 scenarios, Full HD movie (Videogrammetry, 24 MP (UAV photogrammetry, and 88 MP image sequence. Our estimations led to approximate 3000 fps for Full HD movie, 250 fps for 24 MP image sequence and 68 fps for 88MP Ultracam image sequence which can be a huge improvement for current photogrammetric processing systems. We also estimated the power consumption of less than10 watts which is not comparable to current workflows.

  8. Neuromorphic crossbar circuit with nanoscale filamentary-switching binary memristors for speech recognition

    Science.gov (United States)

    Truong, Son Ngoc; Ham, Seok-Jin; Min, Kyeong-Sik

    2014-11-01

    In this paper, a neuromorphic crossbar circuit with binary memristors is proposed for speech recognition. The binary memristors which are based on filamentary-switching mechanism can be found more popularly and are easy to be fabricated than analog memristors that are rare in materials and need a more complicated fabrication process. Thus, we develop a neuromorphic crossbar circuit using filamentary-switching binary memristors not using interface-switching analog memristors. The proposed binary memristor crossbar can recognize five vowels with 4-bit 64 input channels. The proposed crossbar is tested by 2,500 speech samples and verified to be able to recognize 89.2% of the tested samples. From the statistical simulation, the recognition rate of the binary memristor crossbar is estimated to be degraded very little from 89.2% to 80%, though the percentage variation in memristance is increased very much from 0% to 15%. In contrast, the analog memristor crossbar loses its recognition rate significantly from 96% to 9% for the same percentage variation in memristance.

  9. Development of Neuromorphic Sift Operator with Application to High Speed Image Matching

    Science.gov (United States)

    Shankayi, M.; Saadatseresht, M.; Bitetto, M. A. V.

    2015-12-01

    There was always a speed/accuracy challenge in photogrammetric mapping process, including feature detection and matching. Most of the researches have improved algorithm's speed with simplifications or software modifications which increase the accuracy of the image matching process. This research tries to improve speed without enhancing the accuracy of the same algorithm using Neuromorphic techniques. In this research we have developed a general design of a Neuromorphic ASIC to handle algorithms such as SIFT. We also have investigated neural assignment in each step of the SIFT algorithm. With a rough estimation based on delay of the used elements including MAC and comparator, we have estimated the resulting chip's performance for 3 scenarios, Full HD movie (Videogrammetry), 24 MP (UAV photogrammetry), and 88 MP image sequence. Our estimations led to approximate 3000 fps for Full HD movie, 250 fps for 24 MP image sequence and 68 fps for 88MP Ultracam image sequence which can be a huge improvement for current photogrammetric processing systems. We also estimated the power consumption of less than10 watts which is not comparable to current workflows.

  10. A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers

    Energy Technology Data Exchange (ETDEWEB)

    Potok, Thomas E [ORNL; Schuman, Catherine D [ORNL; Young, Steven R [ORNL; Patton, Robert M [ORNL; Spedalieri, Federico [University of Southern California, Information Sciences Institute; Liu, Jeremy [University of Southern California, Information Sciences Institute; Yao, Ke-Thia [University of Southern California, Information Sciences Institute; Rose, Garrett [University of Tennessee (UT); Chakma, Gangotree [University of Tennessee (UT)

    2016-01-01

    Current Deep Learning models use highly optimized convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers with a fairly simple layered network topology, i.e., highly connected layers, without intra-layer connections. Complex topologies have been proposed, but are intractable to train on current systems. Building the topologies of the deep learning network requires hand tuning, and implementing the network in hardware is expensive in both cost and power. In this paper, we evaluate deep learning models using three different computing architectures to address these problems: quantum computing to train complex topologies, high performance computing (HPC) to automatically determine network topology, and neuromorphic computing for a low-power hardware implementation. Due to input size limitations of current quantum computers we use the MNIST dataset for our evaluation. The results show the possibility of using the three architectures in tandem to explore complex deep learning networks that are untrainable using a von Neumann architecture. We show that a quantum computer can find high quality values of intra-layer connections and weights, while yielding a tractable time result as the complexity of the network increases; a high performance computer can find optimal layer-based topologies; and a neuromorphic computer can represent the complex topology and weights derived from the other architectures in low power memristive hardware. This represents a new capability that is not feasible with current von Neumann architecture. It potentially enables the ability to solve very complicated problems unsolvable with current computing technologies.

  11. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications.

    Science.gov (United States)

    Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

    2016-08-11

    Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure-Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron-Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

  12. Piezoelectric vibration-driven locomotion systems - Exploiting resonance and bistable dynamics

    Science.gov (United States)

    Fang, Hongbin; Wang, K. W.

    2017-03-01

    While a piezoelectric-based vibration-driven system is an excellent candidate for actuating small-size crawling-type locomotion robots, it has the major drawback of limited stroke output that would severely constraint the system's locomotion performance. In this paper, to advance the state of the art, we propose two novel designs of piezoelectric vibration-driven locomotion systems. The first utilizes the resonant amplification concept, and the second explores the design of a bistable device. While these two ideas have been explored for piezoelectric actuation amplification in general, they have never been exploited for crawling-type robotic locomotion. Numerical analyses on both systems reveal that resonance and bistability can substantially increase the systems' average locomotion speed. Moreover, this research shows that with bistability, the system is able to output high average locomotion speed in a wider frequency band, possess multiple locomotion modes, and achieve fast switches among them. Through proof-of-concept prototypes, the predicted locomotion performance improvements brought by resonance and bistability are verified. Finally, the basin stability is evaluated to systematically describe the occurring probability of certain locomotion behavior of the bistable system, which would provide useful guideline to the design and control of bistable vibration-driven locomotion systems.

  13. Magnetic-field induced bistability in a quasi-one-dimensional semiconductor microcavity

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Chuanyi, E-mail: chyzhang@henu.edu.cn; Zhang, Weifeng

    2015-09-04

    We theoretically study the magnetic-field induced bistability in a quasi-one-dimensional semiconductor microcavity. A critical magnetic field is obtained, and the bistability appears if a magnetic field is greater than the critical value. For a positive energy detuning of the pump from the bare exciton polaritons, one bistability loop first emerges, then it divides into two loops, and finally one of them vanishes with the increasing magnetic field. This phenomenon originates from the magnetic-field modulated interactions for opposite spins. In the variational process, there are two important effects: one is a logic gate with a small variation of the excitation laser, and the other is a spin texture like skyrmion and this texture is periodic if the energy detuning varies periodically in real space, which is useful for designing the spin-dependent optoelectronic devices. - Highlights: • We study the bistability induced by a magnetic field in a microcavity. • One bistability loop can divide into two, and then the two loops return to one. • A spin texture like skyrmion and logic gate arise in the variation of bistability loop.

  14. Learning and optimization with cascaded VLSI neural network building-block chips

    Science.gov (United States)

    Duong, T.; Eberhardt, S. P.; Tran, M.; Daud, T.; Thakoor, A. P.

    1992-01-01

    To demonstrate the versatility of the building-block approach, two neural network applications were implemented on cascaded analog VLSI chips. Weights were implemented using 7-b multiplying digital-to-analog converter (MDAC) synapse circuits, with 31 x 32 and 32 x 32 synapses per chip. A novel learning algorithm compatible with analog VLSI was applied to the two-input parity problem. The algorithm combines dynamically evolving architecture with limited gradient-descent backpropagation for efficient and versatile supervised learning. To implement the learning algorithm in hardware, synapse circuits were paralleled for additional quantization levels. The hardware-in-the-loop learning system allocated 2-5 hidden neurons for parity problems. Also, a 7 x 7 assignment problem was mapped onto a cascaded 64-neuron fully connected feedback network. In 100 randomly selected problems, the network found optimal or good solutions in most cases, with settling times in the range of 7-100 microseconds.

  15. Power gating of VLSI circuits using MEMS switches in low power applications

    KAUST Repository

    Shobak, Hosam

    2011-12-01

    Power dissipation poses a great challenge for VLSI designers. With the intense down-scaling of technology, the total power consumption of the chip is made up primarily of leakage power dissipation. This paper proposes combining a custom-designed MEMS switch to power gate VLSI circuits, such that leakage power is efficiently reduced while accounting for performance and reliability. The designed MEMS switch is characterized by an 0.1876 ? ON resistance and requires 4.5 V to switch. As a result of implementing this novel power gating technique, a standby leakage power reduction of 99% and energy savings of 33.3% are achieved. Finally the possible effects of surge currents and ground bounce noise are studied. These findings allow longer operation times for battery-operated systems characterized by long standby periods. © 2011 IEEE.

  16. Test Generation for Crosstalk-Induced Delay Faults in VLSI Circuits Using Modified FAN Algorithm

    Directory of Open Access Journals (Sweden)

    S. Jayanthy

    2012-01-01

    Full Text Available As design trends move toward nanometer technology, new problems due to noise effects lead to a decrease in reliability and performance of VLSI circuits. Crosstalk is one such noise effect which affects the timing behaviour of circuits. In this paper, an efficient Automatic Test Pattern Generation (ATPG method based on a modified Fanout Oriented (FAN to detect crosstalk-induced delay faults in VLSI circuits is presented. Tests are generated for ISCAS_85 and enhanced scan version of ISCAS_89 benchmark circuits. Experimental results demonstrate that the test program gives better fault coverage, less number of backtracks, and hence reduced test generation time for most of the benchmark circuits when compared to modified Path-Oriented Decision Making (PODEM based ATPG. The number of transitions is also reduced thus reducing the power dissipation of the circuit.

  17. A subthreshold aVLSI implementation of the Izhikevich simple neuron model.

    Science.gov (United States)

    Rangan, Venkat; Ghosh, Abhishek; Aparin, Vladimir; Cauwenberghs, Gert

    2010-01-01

    We present a circuit architecture for compact analog VLSI implementation of the Izhikevich neuron model, which efficiently describes a wide variety of neuron spiking and bursting dynamics using two state variables and four adjustable parameters. Log-domain circuit design utilizing MOS transistors in subthreshold results in high energy efficiency, with less than 1pJ of energy consumed per spike. We also discuss the effects of parameter variations on the dynamics of the equations, and present simulation results that replicate several types of neural dynamics. The low power operation and compact analog VLSI realization make the architecture suitable for human-machine interface applications in neural prostheses and implantable bioelectronics, as well as large-scale neural emulation tools for computational neuroscience.

  18. Recovery Act - CAREER: Sustainable Silicon -- Energy-Efficient VLSI Interconnect for Extreme-Scale Computing

    Energy Technology Data Exchange (ETDEWEB)

    Chiang, Patrick [Oregon State Univ., Corvallis, OR (United States)

    2014-01-31

    The research goal of this CAREER proposal is to develop energy-efficient, VLSI interconnect circuits and systems that will facilitate future massively-parallel, high-performance computing. Extreme-scale computing will exhibit massive parallelism on multiple vertical levels, from thou­ sands of computational units on a single processor to thousands of processors in a single data center. Unfortunately, the energy required to communicate between these units at every level (on­ chip, off-chip, off-rack) will be the critical limitation to energy efficiency. Therefore, the PI's career goal is to become a leading researcher in the design of energy-efficient VLSI interconnect for future computing systems.

  19. A VLSI design for universal noiseless coding. [for spacecraft imaging equipment

    Science.gov (United States)

    Lee, Jun-Ji; Fang, Wai-Chi; Rice, Robert F.

    1988-01-01

    The practical, noiseless and efficient data-compression technique presented involves a conceptual VLSI design which is capable of meeting real-time processing rates and meets low-power, low-weight, and small-volume requirements. This form of data compression is applicable to image data compression aboard future low-budget spaceflight missions, for such instruments as visual-IR mapping spectrometers and high-resolution imaging spectrometers.

  20. INTERNAL MEASUREMENTS FOR FAILURE ANALYSIS AND CHIP VERIFICATION OF VLSI CIRCUITS

    OpenAIRE

    KÖlzer, J.; Otto, J.

    1989-01-01

    Chip verification and failure analysis during the design evaluation of very large scale integrated (VLSI) devices call for highly accurate internal analysis methods. After having characterized the first silicon by automated functional testing, classification and statistical analysis can be carried out : In this way a rough electrical evaluation of the material under investigation can be made. Further clues to a faulty device behavior can only be obtained by internal measurements. Serious malf...

  1. Simulation-based analysis for NBTI degradation in combinational CMOS VLSI circuits

    OpenAIRE

    Georgiev, Zdravko

    2013-01-01

    The negative-bias temperature instability (NBTI) is one of the dominant aging degradation mechanisms in today Very Large Scale Integration (VLSI) Integrated Circuits (IC). With the further decreasing of the transistor dimensions and reduction of supply voltage, the NBTI degradation may become a critical reliability threat. Nevertheless, most of the EDA tools lack in the ability to predict and analyse the impact of the NBTI. Other tools able to analyse the NBTI, are often on very low design le...

  2. International Conference on VLSI, Communication, Advanced Devices, Signals & Systems and Networking

    CERN Document Server

    Shirur, Yasha; Prasad, Rekha

    2013-01-01

    This book is a collection of papers presented by renowned researchers, keynote speakers and academicians in the International Conference on VLSI, Communication, Analog Designs, Signals and Systems, and Networking (VCASAN-2013), organized by B.N.M. Institute of Technology, Bangalore, India during July 17-19, 2013. The book provides global trends in cutting-edge technologies in electronics and communication engineering. The content of the book is useful to engineers, researchers and academicians as well as industry professionals.

  3. VLSI Architecture for Configurable and Low-Complexity Design of Hard-Decision Viterbi Decoding Algorithm

    Directory of Open Access Journals (Sweden)

    Rachmad Vidya Wicaksana Putra

    2016-06-01

    Full Text Available Convolutional encoding and data decoding are fundamental processes in convolutional error correction. One of the most popular error correction methods in decoding is the Viterbi algorithm. It is extensively implemented in many digital communication applications. Its VLSI design challenges are about area, speed, power, complexity and configurability. In this research, we specifically propose a VLSI architecture for a configurable and low-complexity design of a hard-decision Viterbi decoding algorithm. The configurable and low-complexity design is achieved by designing a generic VLSI architecture, optimizing each processing element (PE at the logical operation level and designing a conditional adapter. The proposed design can be configured for any predefined number of trace-backs, only by changing the trace-back parameter value. Its computational process only needs N + 2 clock cycles latency, with N is the number of trace-backs. Its configurability function has been proven for N = 8, N = 16, N = 32 and N = 64. Furthermore, the proposed design was synthesized and evaluated in Xilinx and Altera FPGA target boards for area consumption and speed performance.

  4. Dynamics and control of twisting bi-stable structures

    Science.gov (United States)

    Arrieta, Andres F.; van Gemmeren, Valentin; Anderson, Aaron J.; Weaver, Paul M.

    2018-02-01

    Compliance-based morphing structures have the potential to offer large shape adaptation, high stiffness and low weight, while reducing complexity, friction, and scalability problems of mechanism based systems. A promising class of structure that enables these characteristics are multi-stable structures given their ability to exhibit large deflections and rotations without the expensive need for continuous actuation, with the latter only required intermittently. Furthermore, multi-stable structures exhibit inherently fast response due to the snap-through instability governing changes between stable states, enabling rapid configuration switching between the discrete number of programmed shapes of the structure. In this paper, the design and utilisation of the inherent nonlinear dynamics of bi-stable twisting I-beam structures for actuation with low strain piezoelectric materials is presented. The I-beam structure consists of three compliant components assembled into a monolithic single element, free of moving parts, and showing large deflections between two stable states. Finite element analysis is utilised to uncover the distribution of strain across the width of the flange, guiding the choice of positioning for piezoelectric actuators. In addition, the actuation authority is maximised by calculating the generalised coupling coefficient for different positions of the piezoelectric actuators. The results obtained are employed to tailor and test I-beam designs exhibiting desired large deflection between stable states, while still enabling the activation of snap-through with the low strain piezoelectric actuators. To this end, the dynamic response of the I-beams to piezoelectric excitation is investigated, revealing that resonant excitations are insufficient to dynamically trigger snap-through. A novel bang–bang control strategy, which exploits the nonlinear dynamics of the structure successfully triggers both single and constant snap-through between the stable

  5. Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system

    Science.gov (United States)

    Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

    2017-10-01

    Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

  6. Interplay of multiple synaptic plasticity features in filamentary memristive devices for neuromorphic computing

    Science.gov (United States)

    La Barbera, Selina; Vincent, Adrien F.; Vuillaume, Dominique; Querlioz, Damien; Alibart, Fabien

    2016-12-01

    Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.

  7. Trim28 Haploinsufficiency Triggers Bi-stable Epigenetic Obesity.

    Science.gov (United States)

    Dalgaard, Kevin; Landgraf, Kathrin; Heyne, Steffen; Lempradl, Adelheid; Longinotto, John; Gossens, Klaus; Ruf, Marius; Orthofer, Michael; Strogantsev, Ruslan; Selvaraj, Madhan; Lu, Tess Tsai-Hsiu; Casas, Eduard; Teperino, Raffaele; Surani, M Azim; Zvetkova, Ilona; Rimmington, Debra; Tung, Y C Loraine; Lam, Brian; Larder, Rachel; Yeo, Giles S H; O'Rahilly, Stephen; Vavouri, Tanya; Whitelaw, Emma; Penninger, Josef M; Jenuwein, Thomas; Cheung, Ching-Lung; Ferguson-Smith, Anne C; Coll, Anthony P; Körner, Antje; Pospisilik, J Andrew

    2016-01-28

    More than one-half billion people are obese, and despite progress in genetic research, much of the heritability of obesity remains enigmatic. Here, we identify a Trim28-dependent network capable of triggering obesity in a non-Mendelian, "on/off" manner. Trim28(+/D9) mutant mice exhibit a bi-modal body-weight distribution, with isogenic animals randomly emerging as either normal or obese and few intermediates. We find that the obese-"on" state is characterized by reduced expression of an imprinted gene network including Nnat, Peg3, Cdkn1c, and Plagl1 and that independent targeting of these alleles recapitulates the stochastic bi-stable disease phenotype. Adipose tissue transcriptome analyses in children indicate that humans too cluster into distinct sub-populations, stratifying according to Trim28 expression, transcriptome organization, and obesity-associated imprinted gene dysregulation. These data provide evidence of discrete polyphenism in mouse and man and thus carry important implications for complex trait genetics, evolution, and medicine. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  8. Emergent equilibrium in many-body optical bistability

    Science.gov (United States)

    Foss-Feig, M.; Niroula, P.; Young, J. T.; Hafezi, M.; Gorshkov, A. V.; Wilson, R. M.; Maghrebi, M. F.

    2017-04-01

    Many-body systems constructed of quantum-optical building blocks can now be realized in experimental platforms ranging from exciton-polariton fluids to ultracold Rydberg gases, establishing a fascinating interface between traditional many-body physics and the driven-dissipative, nonequilibrium setting of cavity QED. At this interface, the standard techniques and intuitions of both fields are called into question, obscuring issues as fundamental as the role of fluctuations, dimensionality, and symmetry on the nature of collective behavior and phase transitions. Here, we study the driven-dissipative Bose-Hubbard model, a minimal description of numerous atomic, optical, and solid-state systems in which particle loss is countered by coherent driving. Despite being a lattice version of optical bistability, a foundational and patently nonequilibrium model of cavity QED, the steady state possesses an emergent equilibrium description in terms of a classical Ising model. We establish this picture by making new connections between traditional techniques from many-body physics (functional integrals) and quantum optics (the system-size expansion). To lowest order in a controlled expansion—organized around the experimentally relevant limit of weak interactions—the full quantum dynamics reduces to nonequilibrium Langevin equations, which support a phase transition described by model A of the Hohenberg-Halperin classification. Numerical simulations of the Langevin equations corroborate this picture, revealing that canonical behavior associated with the Ising model manifests readily in simple experimental observables.

  9. Trim28 Haploinsufficiency Triggers Bi-stable Epigenetic Obesity

    Science.gov (United States)

    Dalgaard, Kevin; Landgraf, Kathrin; Heyne, Steffen; Lempradl, Adelheid; Longinotto, John; Gossens, Klaus; Ruf, Marius; Orthofer, Michael; Strogantsev, Ruslan; Selvaraj, Madhan; Lu, Tess Tsai-Hsiu; Casas, Eduard; Teperino, Raffaele; Surani, M. Azim; Zvetkova, Ilona; Rimmington, Debra; Tung, Y.C. Loraine; Lam, Brian; Larder, Rachel; Yeo, Giles S.H.; O’Rahilly, Stephen; Vavouri, Tanya; Whitelaw, Emma; Penninger, Josef M.; Jenuwein, Thomas; Cheung, Ching-Lung; Ferguson-Smith, Anne C.; Coll, Anthony P.; Körner, Antje; Pospisilik, J. Andrew

    2016-01-01

    Summary More than one-half billion people are obese, and despite progress in genetic research, much of the heritability of obesity remains enigmatic. Here, we identify a Trim28-dependent network capable of triggering obesity in a non-Mendelian, “on/off” manner. Trim28+/D9 mutant mice exhibit a bi-modal body-weight distribution, with isogenic animals randomly emerging as either normal or obese and few intermediates. We find that the obese-“on” state is characterized by reduced expression of an imprinted gene network including Nnat, Peg3, Cdkn1c, and Plagl1 and that independent targeting of these alleles recapitulates the stochastic bi-stable disease phenotype. Adipose tissue transcriptome analyses in children indicate that humans too cluster into distinct sub-populations, stratifying according to Trim28 expression, transcriptome organization, and obesity-associated imprinted gene dysregulation. These data provide evidence of discrete polyphenism in mouse and man and thus carry important implications for complex trait genetics, evolution, and medicine. Video Abstract PMID:26824653

  10. Hindrances to bistable front propagation: application to Wolbachia invasion.

    Science.gov (United States)

    Nadin, Grégoire; Strugarek, Martin; Vauchelet, Nicolas

    2017-09-22

    We study the biological situation when an invading population propagates and replaces an existing population with different characteristics. For instance, this may occur in the presence of a vertically transmitted infection causing a cytoplasmic effect similar to the Allee effect (e.g. Wolbachia in Aedes mosquitoes): the invading dynamics we model is bistable. We aim at quantifying the propagules (what does it take for an invasion to start?) and the invasive power (how far can an invading front go, and what can stop it?). We rigorously show that a heterogeneous environment inducing a strong enough population gradient can stop an invading front, which will converge in this case to a stable front. We characterize the critical population jump, and also prove the existence of unstable fronts above the stable (blocking) fronts. Being above the maximal unstable front enables an invading front to clear the obstacle and propagate further. We are particularly interested in the case of artificial Wolbachia infection, used as a tool to fight arboviruses.

  11. Tuning size and thermal hysteresis in bistable spin crossover nanoparticles.

    Science.gov (United States)

    Galán-Mascarós, José Ramón; Coronado, Eugenio; Forment-Aliaga, Alicia; Monrabal-Capilla, María; Pinilla-Cienfuegos, Elena; Ceolin, Marcelo

    2010-06-21

    Nanoparticles of iron(II) triazole salts have been prepared from water-organic microemulsions. The mean size of the nanoparticles can be tuned down to 6 nm in diameter, with a narrow size distribution. A sharp spin transition from the low spin (LS) to the high spin (HS) state is observed above room temperature, with a 30-40-K-wide thermal hysteresis. The same preparation can yield second generation nanoparticles containing molecular alloys by mixing triazole with triazole derivatives, or from metallic mixtures of iron(II) and zinc(II). In these nanoparticles of 10-15 nm, the spin transition "moves" towards lower temperatures, reaching a 316 K limit for the cooling down transition and maintaining a thermal hysteresis over 15-20-K-wide. The nanoparticles were characterized by dynamic light scattering, TEM, and AFM, after deposition on gold or silicon surfaces. The spin transition was characterized by magnetic susceptibility measurements and EXAFS (in solid samples after solvent removal) and also by the color change between the LS (violet) and HS (colorless) states in an organic solvent suspension. The discovery of bistable magnetic nanoparticles of 6 nm with a wide thermal hysteresis above room temperature showcases the actual possibilities of spin crossover materials for nanotechnological applications.

  12. Bistable synchronization modes in hydrodynamically coupled micro-rotors

    Science.gov (United States)

    Guo, Hanliang; Kanale, Anup; Fuerthauer, Sebastian; Kanso, Eva

    2017-11-01

    Cilia often beat in synchrony, and they may transition between different synchronization modes in the same cell type. For example, cilia in the mammalian brain ventricles are reported to periodically change their collective beat orientation, providing a cilia-based switch for redirecting the transport of cerebrospinal fluid. Experimental and theoretical evidences suggest that phase coordinations can be achieved solely via hydrodynamical interactions. However, the exact mechanisms responsible for transitioning between various synchronization modes remain illusive. Here, we use a theoretical model where each cilium is represented by a bead moving along a closed trajectory close to a no-slip surface. We investigate the emergent synchronization modes and their stability for various cilia-inspired force profiles. We observe distinct stable synchronization modes between two rotors, including a bistable regime where both in-phase and anti-phase synchronizations are stable. We then extend this analysis to an array of rotors where we demonstrate the dynamical formations of metachronal waves. These findings may help us to understand the origin of synchrony in biological and bio-inspired systems, and the mechanisms underlying transitions between different synchronization modes.

  13. Piezoelectrically strained bistable laminates with macro fiber composites

    Science.gov (United States)

    Lee, Andrew J.; Moosavian, Amin; Inman, Daniel J.

    2017-04-01

    The bistability and snap through capability of an unsymmetric laminate consisting of only Macro Fiber Composites (MFC) are investigated. The non-linear analysis predicts two cylindrically stable configurations when strain anisotropy is piezoelectrically induced within a [0MFC/90MFC]T laminate. This is achieved by bonding two MFCs in their actuated states and releasing the voltage post cure to create in-plane residual stresses. The minimization of total potential energy with the Rayleigh-Ritz method are used to analytically model the resulting laminate. A finite element analysis is conducted in MSC Nastran using the piezoelectric-thermal analogy approach to verify the analytical results. The effects of adhesive properties, bonding cure cycles, MFC layup, and its geometry on the curvatures, displacements, and bifurcation voltages are characterized. Finally, the snap through and reverse snap through capabilities with piezoelectric actuation are demonstrated. This adaptive laminate functions as both the actuator and the primary structure and allows large deformations under a non-continuous energy input. Its snap through capability allows full configuration control necessary in morphing applications.

  14. Low-threshold optical bistability in a metasurface with graphene

    Science.gov (United States)

    Guo, Jun; Ruan, Banxian; Zhu, Jiaqi; Dai, Xiaoyu; Xiang, Yuanjiang; Zhang, Han

    2017-11-01

    A nonlinear metasurface made of a few-layer graphene and a metal grating is proposed in this work. It is demonstrated that the graphene plasmons can be excited in this configuration efficiently and two quite different kinds of resonances are found. The resonant behaviors and their origins are analyzed carefully, and the influences of grating groove and period on the resonances are discussed. It is surprising that the width of grating groove plays an important role in the resonant behaviors, distinct from the dielectric gratings. Due to the coupling of graphene plasmons and the grating, the highly tunability and large near field enhancement of our structure are observed. Finally, we apply our results to the optical bistability, and the low-threshold hysterical behavior with only a few MW cm-2 is observed due to the large third-order nonlinear response of graphene and the strong localized field enhancement. We believe that our results will be inspiring not only for more complicated metasurfaces involving graphene, but also for other nonlinear optical applications.

  15. A simple self-maintaining metabolic system: robustness, autocatalysis, bistability.

    Directory of Open Access Journals (Sweden)

    Gabriel Piedrafita

    Full Text Available A living organism must not only organize itself from within; it must also maintain its organization in the face of changes in its environment and degradation of its components. We show here that a simple (M,R-system consisting of three interlocking catalytic cycles, with every catalyst produced by the system itself, can both establish a non-trivial steady state and maintain this despite continuous loss of the catalysts by irreversible degradation. As long as at least one catalyst is present at a sufficient concentration in the initial state, the others can be produced and maintained. The system shows bistability, because if the amount of catalyst in the initial state is insufficient to reach the non-trivial steady state the system collapses to a trivial steady state in which all fluxes are zero. It is also robust, because if one catalyst is catastrophically lost when the system is in steady state it can recreate the same state. There are three elementary flux modes, but none of them is an enzyme-maintaining mode, the entire network being necessary to maintain the two catalysts.

  16. Bi-stability in turbulent, rotating spherical Couette flow

    CERN Document Server

    Zimmerman, Daniel S; Lathrop, Daniel P; 10.1063/1.3593465

    2011-01-01

    Flow between concentric spheres of radius ratio $\\eta = r_\\mathrm{i}/r_\\mathrm{o} = 0.35$ is studied in a 3 m outer diameter experiment. We have measured the torques required to maintain constant boundary speeds as well as localized wall shear stress, velocity, and pressure. At low Ekman number $E = 2.1\\times10^{-7}$ and modest Rossby number $0.07 < Ro < 3.4$, the resulting flow is highly turbulent, with a Reynolds number ($Re=Ro/E$) exceeding fifteen million. Several turbulent flow regimes are evident as $Ro$ is varied for fixed $E$. We focus our attention on one flow transition in particular, between $Ro = 1.8$ and $Ro = 2.6$, where the flow shows bistable behavior. For $Ro$ within this range, the flow undergoes intermittent transitions between the states observed alone at adjacent $Ro$ outside the switching range. The two states are clearly distinguished in all measured flow quantities, including a striking reduction in torque demanded from the inner sphere by the state lying at higher $Ro$. The redu...

  17. Shape transitions in bistable carbon nanotubes coupled to encapsulated gas

    Science.gov (United States)

    Shklyaev, Oleg; Mockensturm, Eric; Cole, Milton; Crespi, Vincent

    2014-03-01

    Large-diameter single-wall carbon nanotubes are bistable (i.e. can have inflated or collapsed cross-sections) and can be used to design nano-electromechanical systems such as engines, generators, and heat pumps. The underlying physical mechanism for these devices is the sensitivity of the tube's equilibrium shape to external stimuli such as temperature and applied voltage. Fixing one end in the inflated state and the other in the collapsed state creates a mobile transition region separating these states. Gas encapsulated inside the tube provides an additional means to control the tube shape by coupling its thermodynamic parameters to the equilibrium tube configuration. Depending on the conditions, the encapsulated gas can remain vapor or condense layer-by-layer on the inner wall surface. We analyze such a system with lattice-gas model and molecular dynamics simulations. Changing the gas temperature or number of gas atoms changes the relative fraction of collapsed and inflated regions, while external forces that change the tube shape also affect the phase of the encapsulated gas. Surprisingly, squashing an inflated tube that has gas condensed on its inner surface decreases the surface area available to the wetting layer, so that gas atoms are forced back into the vapor phase: a paradoxical effect where compression induces a transition from condensed to vapor phases.

  18. Sound stream segregation: a neuromorphic approach to solve the "cocktail party problem" in real-time.

    Science.gov (United States)

    Thakur, Chetan Singh; Wang, Runchun M; Afshar, Saeed; Hamilton, Tara J; Tapson, Jonathan C; Shamma, Shihab A; van Schaik, André

    2015-01-01

    The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the "cocktail party effect." It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA). This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR) of the segregated stream (90, 77, and 55 dB for simple tone, complex tone, and speech, respectively) as compared to the SNR of the mixture waveform (0 dB). This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for sound segregation and

  19. A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP

    Science.gov (United States)

    Balduzzi, David; Tononi, Giulio

    2012-01-01

    In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP). STDP is responsible for the strengthening (or weakening) of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse) spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF) neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips. PMID:22615855

  20. A bidirectional brain-machine interface featuring a neuromorphic hardware decoder

    Directory of Open Access Journals (Sweden)

    Fabio Boi

    2016-12-01

    Full Text Available Bidirectional brain-machine interfaces (BMIs establish a two-way direct communication link4 between the brain and the external world. A decoder translates recorded neural activity into motor5 commands and an encoder delivers sensory information collected from the environment directly6 to the brain creating a closed-loop system. These two modules are typically integrated in bulky7 external devices. However, the clinical support of patients with severe motor and sensory deficits8 requires compact, low-power, and fully implantable systems that can decode neural signals to9 control external devices. As a first step toward this goal, we developed a modular bidirectional BMI10 setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented11 a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits.12 On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn13 to decode neural signals recorded from the brain into motor outputs controlling the movements14 of an external device. The modularity of the BMI allowed us to tune the individual components15 of the setup without modifying the whole system. In this paper we present the features of16 this modular BMI, and describe how we configured the network of spiking neuron circuits to17 implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm18 that connects bidirectionally the brain of an anesthetized rat with an external object. We show that19 the chip learned the decoding task correctly, allowing the interfaced brain to control the object’s20 trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is21 mature enough for the development of BMI modules that are sufficiently low-power and compact,22 while being highly computationally powerful and adaptive.

  1. A neuromorphic architecture for object recognition and motion anticipation using burst-STDP.

    Directory of Open Access Journals (Sweden)

    Andrew Nere

    Full Text Available In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP. STDP is responsible for the strengthening (or weakening of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips.

  2. Virtual Neurorobotics (VNR) to Accelerate Development of Plausible Neuromorphic Brain Architectures.

    Science.gov (United States)

    Goodman, Philip H; Buntha, Sermsak; Zou, Quan; Dascalu, Sergiu-Mihai

    2007-01-01

    Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly "intelligent" systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain's interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products). We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR) intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental material.

  3. Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study

    Directory of Open Access Journals (Sweden)

    Thomas Pfeil

    2016-05-01

    Full Text Available High-level brain function, such as memory, classification, or reasoning, can be realized by means of recurrent networks of simplified model neurons. Analog neuromorphic hardware constitutes a fast and energy-efficient substrate for the implementation of such neural computing architectures in technical applications and neuroscientific research. The functional performance of neural networks is often critically dependent on the level of correlations in the neural activity. In finite networks, correlations are typically inevitable due to shared presynaptic input. Recent theoretical studies have shown that inhibitory feedback, abundant in biological neural networks, can actively suppress these shared-input correlations and thereby enable neurons to fire nearly independently. For networks of spiking neurons, the decorrelating effect of inhibitory feedback has so far been explicitly demonstrated only for homogeneous networks of neurons with linear subthreshold dynamics. Theory, however, suggests that the effect is a general phenomenon, present in any system with sufficient inhibitory feedback, irrespective of the details of the network structure or the neuronal and synaptic properties. Here, we investigate the effect of network heterogeneity on correlations in sparse, random networks of inhibitory neurons with nonlinear, conductance-based synapses. Emulations of these networks on the analog neuromorphic-hardware system Spikey allow us to test the efficiency of decorrelation by inhibitory feedback in the presence of hardware-specific heterogeneities. The configurability of the hardware substrate enables us to modulate the extent of heterogeneity in a systematic manner. We selectively study the effects of shared input and recurrent connections on correlations in membrane potentials and spike trains. Our results confirm that shared-input correlations are actively suppressed by inhibitory feedback also in highly heterogeneous networks exhibiting broad

  4. Virtual neurorobotics (VNR to accelerate development of plausible neuromorphic brain architectures

    Directory of Open Access Journals (Sweden)

    Philip H Goodman

    2007-11-01

    Full Text Available Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly “intelligent” systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain’s interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products. We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental

  5. A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

    Science.gov (United States)

    Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

    2016-01-01

    Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

  6. AnRAD: A Neuromorphic Anomaly Detection Framework for Massive Concurrent Data Streams.

    Science.gov (United States)

    Chen, Qiuwen; Luley, Ryan; Wu, Qing; Bishop, Morgan; Linderman, Richard W; Qiu, Qinru

    2017-03-17

    The evolution of high performance computing technologies has enabled the large-scale implementation of neuromorphic models and pushed the research in computational intelligence into a new era. Among the machine learning applications, unsupervised detection of anomalous streams is especially challenging due to the requirements of detection accuracy and real-time performance. Designing a computing framework that harnesses the growing computing power of the multicore systems while maintaining high sensitivity and specificity to the anomalies is an urgent research topic. In this paper, we propose anomaly recognition and detection (AnRAD), a bioinspired detection framework that performs probabilistic inferences. We analyze the feature dependency and develop a self-structuring method that learns an efficient confabulation network using unlabeled data. This network is capable of fast incremental learning, which continuously refines the knowledge base using streaming data. Compared with several existing anomaly detection approaches, our method provides competitive detection quality. Furthermore, we exploit the massive parallel structure of the AnRAD framework. Our implementations of the detection algorithm on the graphic processing unit and the Xeon Phi coprocessor both obtain substantial speedups over the sequential implementation on general-purpose microprocessor. The framework provides real-time service to concurrent data streams within diversified knowledge contexts, and can be applied to large problems with multiple local patterns. Experimental results demonstrate high computing performance and memory efficiency. For vehicle behavior detection, the framework is able to monitor up to 16,000 vehicles (data streams) and their interactions in real time with a single commodity coprocessor, and uses less than 0.2 ms for one testing subject. Finally, the detection network is ported to our spiking neural network simulator to show the potential of adapting to the emerging

  7. Specification and Design Methodologies for High-Speed Fault-Tolerant Array Algorithms and Structures for VLSI.

    Science.gov (United States)

    1987-06-01

    Verlag Lecture Notes 201, 1985. [She84] M. Sheeran , "muFP, a language for VLSI design", Proc. 1984 ACM Conference on LISP and Functional Programming...fMeshkinpour8S5 and Sheeran (Sheeran84] extended Backus’ Fl? language with operators to handle sequential circuits. 2 Brief Introduction to vFP vFP...Spring 1913, pp. 274-277. (201 Sheeran , M., "muFP, a Language for VLSI Design." Proc 1984 ACM Conference on LU and Functional Programming. August [4

  8. Microscale Adaptive Optics: Wave-Front Control with a mu-Mirror Array and a VLSI Stochastic Gradient Descent Controller.

    Science.gov (United States)

    Weyrauch, T; Vorontsov, M A; Bifano, T G; Hammer, J A; Cohen, M; Cauwenberghs, G

    2001-08-20

    The performance of adaptive systems that consist of microscale on-chip elements [microelectromechanical mirror (mu-mirror) arrays and a VLSI stochastic gradient descent microelectronic control system] is analyzed. The mu-mirror arrays with 5 x 5 and 6 x 6 actuators were driven with a control system composed of two mixed-mode VLSI chips implementing model-free beam-quality metric optimization by the stochastic parallel perturbative gradient descent technique. The adaptation rate achieved was near 6000 iterations/s. A secondary (learning) feedback loop was used to control system parameters during the adaptation process, further increasing the adaptation rate.

  9. Bistability induces episodic spike communication by inhibitory neurons in neuronal networks

    Science.gov (United States)

    Kazantsev, V. B.; Asatryan, S. Yu.

    2011-09-01

    Bistability is one of the important features of nonlinear dynamical systems. In neurodynamics, bistability has been found in basic Hodgkin-Huxley equations describing the cell membrane dynamics. When the neuron is clamped near its threshold, the stable rest potential may coexist with the stable limit cycle describing periodic spiking. However, this effect is often neglected in network computations where the neurons are typically reduced to threshold firing units (e.g., integrate-and-fire models). We found that the bistability may induce spike communication by inhibitory coupled neurons in the spiking network. The communication is realized in the form of episodic discharges with synchronous (correlated) spikes during the episodes. A spiking phase map is constructed to describe the synchronization and to estimate basic spike phase locking modes.

  10. Bistability induces episodic spike communication by inhibitory neurons in neuronal networks.

    Science.gov (United States)

    Kazantsev, V B; Asatryan, S Yu

    2011-09-01

    Bistability is one of the important features of nonlinear dynamical systems. In neurodynamics, bistability has been found in basic Hodgkin-Huxley equations describing the cell membrane dynamics. When the neuron is clamped near its threshold, the stable rest potential may coexist with the stable limit cycle describing periodic spiking. However, this effect is often neglected in network computations where the neurons are typically reduced to threshold firing units (e.g., integrate-and-fire models). We found that the bistability may induce spike communication by inhibitory coupled neurons in the spiking network. The communication is realized in the form of episodic discharges with synchronous (correlated) spikes during the episodes. A spiking phase map is constructed to describe the synchronization and to estimate basic spike phase locking modes.

  11. Optical bistability and four-wave mixing in a hybrid optomechanical system

    Science.gov (United States)

    Jiang, Lei; Yuan, Xiaorong; Cui, Yuanshun; Chen, Guibin; Zuo, Fen; Jiang, Cheng

    2017-10-01

    We explore theoretically the optical bistability and four-wave mixing (FWM) in a hybrid optomechanical system, where the mechanical resonator is simultaneously coupled to a cavity field and a two-level system (qubit). We can use a strong control field driving the cavity to control the bistable behavior of the steady-state photon number, phonon number, and the population inversion. The impact of qubit-resonator coupling strength on the bistable behavior is discussed. Furthermore, the two-level system can significantly modify the output fields of the cavity, leading to double optomechanically induced transparency (OMIT) and the enhancement of the FWM intensity. We find that the distance between the two peaks in the FWM spectrum can be controlled by the qubit-resonator coupling strength, and the peak value of the FWM intensity can be adjusted by the Rabi frequency of the control field.

  12. Improving energy harvesting by stochastic resonance in a laminated bistable beam

    Science.gov (United States)

    Li, HaiTao; Qin, WeiYang; Deng, Wangzheng; Tian, Ruilan

    2016-03-01

    This paper presents a bistable energy harvesting device as piezoelectric beam acted upon by a harmonic axial load and a transverse random excitation. A comprehensive analytical study for stochastic resonance in the bistable mechanical system is carried out, from which the system can harvest energy at a high efficiency. The bistable electromechanical model is set up and the corresponding equations are derived by extended Hamilton principle. The condition for occurrence of stochastic resonance is derived by Kramers rate. Numerical simulation is carried out and results are obtained. Stochastic resonance is proved and observed when the system is excited by a Gaussian white noise. The output voltage and power conversion in the condition of stochastic resonance is noticeably higher than those in other conditions. These results can provide a theoretical method for preliminary design and optimization of parameters, which can improve the efficiency of energy harvester.

  13. A tunable bistable device based on a coupled quantum dot-metallic nanoparticle nanosystem

    Science.gov (United States)

    Li, Jian-Bo; Liang, Shan; He, Meng-Dong; Chen, Li-Qun; Wang, Xin-Jun; Peng, Xiao-Fang

    2015-07-01

    We theoretically propose a scheme of a tunable bistable device based on a coupled semiconductor quantum dot-metal nanoparticle nanosystem in the simultaneous presence of a strong pump laser and a weak probe laser with different frequencies. The results show that it is easy to turn on or off the optical bistable effect in such system by switching the polarization direction of the pump field, and the bistability thresholds are highly sensitive to the intensity, frequency, polarization direction of the pump field, and the interparticle distance. In addition, the nonlinear absorption in the two stable states exhibits a ratio as high as 104 arising from the three-photon effect, which implies that our nanosystem can also be used as an optical memory cell.

  14. A computational role for bistability and traveling waves in motor cortex

    Directory of Open Access Journals (Sweden)

    Stewart eHeitmann

    2012-09-01

    Full Text Available Adaptive changes in behavior require rapid changes in brain states yet the brain must also remain stable. We investigated two neural mechanisms for evoking rapid transitions between spatiotemporal synchronization patterns of beta oscillations (13--30Hz in motor cortex. Cortex was modeled as a sheet of neural oscillators that were spatially coupled using a center-surround connection topology. Manipulating the inhibitory surround was found to evoke reliable transitions between synchronous oscillation patterns and traveling waves. These transitions modulated the simulated local field potential in agreement with physiological observations in humans. Intermediate levels of surround inhibition were also found to produce bistable coupling topologies that supported both waves and synchrony. State-dependent perturbation between bistable states produced very rapid transitions but were less reliable. We surmise that motor cortex may thus employ state-dependent computation to achieve very rapid changes between bistable motor states when the demand for speed exceeds the demand for accuracy.

  15. A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

    Science.gov (United States)

    Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

    2017-01-01

    Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

  16. A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems.

    Science.gov (United States)

    Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

    2017-01-12

    Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

  17. An effective timing characterization method for an accuracy-proved VLSI standard cell library

    Science.gov (United States)

    Jianhua, Jiang; Man, Liang; Lei, Wang; Yumei, Zhou

    2014-02-01

    This paper presents a method of tailoring the characterization and modeling timing of a VLSI standard cell library. The paper also presents a method to validate the reasonability of the value through accuracy analysis. In the process of designing a standard cell library, this method is applied to characterize the cell library. In addition, the error calculations of some simple circuit path delays are compared between using the characterization file and an Hspice simulation. The comparison results demonstrate the accuracy of the generated timing library file.

  18. Towards an automated system for the verification and diagnosis of intelligent VLSI circuits

    Science.gov (United States)

    Velazco, Raoul; Ziade, Haissam

    The main features of a system designed to cope with both the verification and diagnosis of Very Large Scale Integration (VLSI) intelligent circuits are detailed. The system is composed of a validation program generator, the GAPT (French Acronym for automatic generation of test programs) software and a microprocessor dedicated verification system, the TEMAC functional tester. GAPT/TEMAC tools allow an easy implementation of a top down diagnosis procedure. Each diagnosis action is composed of symptom analysis, malfunction hypothesis statement, sequence generation, execution, and result evaluation. It was successfully used in various microprocessor qualification/validation experiments. The system capabilities and the diagnosis procedure are illustrated by an actual 68000 microprocessor diagnosis experiment.

  19. VLSI Architectures for Sliding-Window-Based Space-Time Turbo Trellis Code Decoders

    Directory of Open Access Journals (Sweden)

    Georgios Passas

    2012-01-01

    Full Text Available The VLSI implementation of SISO-MAP decoders used for traditional iterative turbo coding has been investigated in the literature. In this paper, a complete architectural model of a space-time turbo code receiver that includes elementary decoders is presented. These architectures are based on newly proposed building blocks such as a recursive add-compare-select-offset (ACSO unit, A-, B-, Γ-, and LLR output calculation modules. Measurements of complexity and decoding delay of several sliding-window-technique-based MAP decoder architectures and a proposed parameter set lead to defining equations and comparison between those architectures.

  20. High-performance fault-tolerant VLSI systems using micro rollback

    Science.gov (United States)

    Tamir, Yuval; Tremblay, Marc

    1990-01-01

    A technique called micro rollback, which allows most of the performance penalty for concurrent error detection to be eliminated, is presented. Detection is performed in parallel with the transmission of information between modules, thus removing the delay for detection from the critical path. Erroneous information may thus reach its destination module several clock cycles before an error indication. Operations performed on this erroneous information are undone using a hardware mechanism for fast rollback of a few cycles. The implementation of a VLSI processor capable of micro rollback is discussed, as well as several critical issues related to its use in a complete system.

  1. Vlsi implementation of flexible architecture for decision tree classification in data mining

    Science.gov (United States)

    Sharma, K. Venkatesh; Shewandagn, Behailu; Bhukya, Shankar Nayak

    2017-07-01

    The Data mining algorithms have become vital to researchers in science, engineering, medicine, business, search and security domains. In recent years, there has been a terrific raise in the size of the data being collected and analyzed. Classification is the main difficulty faced in data mining. In a number of the solutions developed for this problem, most accepted one is Decision Tree Classification (DTC) that gives high precision while handling very large amount of data. This paper presents VLSI implementation of flexible architecture for Decision Tree classification in data mining using c4.5 algorithm.

  2. Perceptual memory drives learning of retinotopic biases for bistable stimuli.

    Directory of Open Access Journals (Sweden)

    Aidan Peter Murphy

    2014-02-01

    Full Text Available The visual system exploits past experience at multiple timescales to resolve perceptual ambiguity in the retinal image. For example, perception of a bistable stimulus can be biased towards one interpretation over another when preceded by a brief presentation of a disambiguated version of the stimulus (positive priming or through intermittent presentations of the ambiguous stimulus (stabilization. Similarly, prior presentations of unambiguous stimuli can be used to explicitly train a long-lasting association between a percept and a retinal location (perceptual association. These phenonema have typically been regarded as independent processes, with short-term biases attributed to perceptual memory and longer-term biases described as associative learning. Here we tested for interactions between these two forms of experience-dependent perceptual bias and demonstrate that short-term processes strongly influence long-term outcomes. We first demonstrate that the establishment of long-term perceptual contingencies does not require explicit training by unambiguous stimuli, but can arise spontaneously during the periodic presentation of brief, ambiguous stimuli. Using rotating Necker cube stimuli, we observed enduring, retinotopically specific perceptual biases that were expressed from the outset and remained stable for up to forty minutes, consistent with the known phenomenon of perceptual stabilization. Further, bias was undiminished after a break period of five minutes, but was readily reset by interposed periods of continuous, as opposed to periodic, ambiguous presentation. Taken together, the results demonstrate that perceptual biases can arise naturally and may principally reflect the brain’s tendency to favor recent perceptual interpretation at a given retinal location. Further, they suggest that an association between retinal location and perceptual state, rather than a physical stimulus, is sufficient to generate long-term biases in perceptual

  3. Bistable dynamics underlying excitability of ion homeostasis in neuron models.

    Directory of Open Access Journals (Sweden)

    Niklas Hübel

    2014-05-01

    Full Text Available When neurons fire action potentials, dissipation of free energy is usually not directly considered, because the change in free energy is often negligible compared to the immense reservoir stored in neural transmembrane ion gradients and the long-term energy requirements are met through chemical energy, i.e., metabolism. However, these gradients can temporarily nearly vanish in neurological diseases, such as migraine and stroke, and in traumatic brain injury from concussions to severe injuries. We study biophysical neuron models based on the Hodgkin-Huxley (HH formalism extended to include time-dependent ion concentrations inside and outside the cell and metabolic energy-driven pumps. We reveal the basic mechanism of a state of free energy-starvation (FES with bifurcation analyses showing that ion dynamics is for a large range of pump rates bistable without contact to an ion bath. This is interpreted as a threshold reduction of a new fundamental mechanism of ionic excitability that causes a long-lasting but transient FES as observed in pathological states. We can in particular conclude that a coupling of extracellular ion concentrations to a large glial-vascular bath can take a role as an inhibitory mechanism crucial in ion homeostasis, while the Na⁺/K⁺ pumps alone are insufficient to recover from FES. Our results provide the missing link between the HH formalism and activator-inhibitor models that have been successfully used for modeling migraine phenotypes, and therefore will allow us to validate the hypothesis that migraine symptoms are explained by disturbed function in ion channel subunits, Na⁺/K⁺ pumps, and other proteins that regulate ion homeostasis.

  4. Random telegraphic voltage noise due to thermal bi-stability in a superconducting weak link

    Science.gov (United States)

    Biswas, Sourav; Kumar, Nikhil; Winkelmann, C. B.; Courtois, Herve; Gupta, Anjan K.

    2016-05-01

    We investigated the random telegraphic voltage noise signal in the hysteretic bi-stable state of a superconducting weak link device. Fluctuation induced random switching between zero voltage state and non-zero-voltage state gives rise to a random telegraphic voltage signal in time domain. This telegraphic noise is used to find the mean lifetime of each of the two states. The mean life time in the zero voltage state is found to decrease with increasing bias current while that of resistive state increases and thus the two cross at certain bias current. We qualitatively discuss this observed switching behavior as arising from the bi-stable nature.

  5. Stable Amplification and High Current Drop Bistable Switching in Supercritical GaAs Tills

    DEFF Research Database (Denmark)

    Izadpanah, S.H; Jeppsson, B; Jeppesen, Palle

    1974-01-01

    Bistable switching with current drops of 40% and switching times of 100 ps are obtained in pulsed operation of 10¿m supercritically doped n+ nn+ GaAs Transferred Electron Devices (TEDs). When CW-operated the same devices exhibit a 5-17 GHz bandwidth for the stable negative resistance.......Bistable switching with current drops of 40% and switching times of 100 ps are obtained in pulsed operation of 10¿m supercritically doped n+ nn+ GaAs Transferred Electron Devices (TEDs). When CW-operated the same devices exhibit a 5-17 GHz bandwidth for the stable negative resistance....

  6. Thiol-modified MoS2 nanosheets as a functional layer for electrical bistable devices

    Science.gov (United States)

    Li, Guan; Tan, Fenxue; Lv, Bokun; Wu, Mengying; Wang, Ruiqi; Lu, Yue; Li, Xu; Li, Zhiqiang; Teng, Feng

    2018-01-01

    Molybdenum disulfide nanosheets have been synthesized by one-pot method using 1-ODT as sulfur source and surfactant. The structure, morphology and optical properties of samples were investigated by XRD, FTIR, Abs spectrum and TEM patterns. The XRD pattern indicated that the as-obtained MoS2 belong to hexagonal system. The as-obtained MoS2 nanosheets blending with PVK could be used to fabricate an electrically bistable devices through a simple spin-coating method and the device exhibited an obvious electrical bistability properties. The charge transport mechanism of the device was discussed based on the filamentary switching models.

  7. Slow light propagation and bistable switching in a graphene under an external magnetic field

    Science.gov (United States)

    Asadpour, Seyyed Hossein; Hamedi, Hamid Reza; Rahimpour Soleimani, Hamid

    2015-04-01

    In this letter, we show the possibility of controlling the optical bistability and group index switching in graphene under the action of strong magnetic and infrared laser fields. By using quantum-mechanical density matrix formalism, we obtain the equations of motion that govern the optical response of graphene in strong magnetic and optical fields. We found that by properly choosing the parameters of the system, the bistable behaviors and group velocity can be controlled. These results may have potential applications in telecommunication and optical information processing.

  8. Optical bistability through the cavity effect in a four-level open atomic medium

    Science.gov (United States)

    Hamedi, H. R.

    2014-11-01

    The optical bistability and multistability behavior in a ring cavity for the four-level open atomic system, driven by two coupling fields has been analyzed. It is shown that the presence of exit rate from cavity is having a dominant effect on generating the optical bi(multi) stability on the system. It is found that the effects of the injection rates can be used to control the threshold intensity. It is also found that optical bistability can convert to optical multistability or vice versa via the effect of intensity and detuning of the coupling fields.

  9. Bistability of self-modulation oscillations in an autonomous solid-state ring laser

    Energy Technology Data Exchange (ETDEWEB)

    Dudetskii, V Yu [Department of Physics, M.V. Lomonosov Moscow State University (Russian Federation)

    2013-11-30

    Bistable self-modulation regimes of generation for a ring YAG : Nd chip laser with the counterpropagating waves asymmetrically coupled via backward scattering are simulated numerically. Two branches of bistable self-modulation regimes of generation are found in the domain of the parametric resonance between the selfmodulation and relaxation oscillations. The self-modulation regimes observed in earlier experiments pertain to only one of the branches. Possible reasons for such a discrepancy are considered, related to the influence of technical and natural noise on the dynamics of solid-state ring lasers. (control of laser radiation parameters)

  10. Optically levitated nanoparticle as a model system for stochastic bistable dynamics

    Science.gov (United States)

    Ricci, F.; Rica, R. A.; Spasenović, M.; Gieseler, J.; Rondin, L.; Novotny, L.; Quidant, R.

    2017-05-01

    Nano-mechanical resonators have gained an increasing importance in nanotechnology owing to their contributions to both fundamental and applied science. Yet, their small dimensions and mass raises some challenges as their dynamics gets dominated by nonlinearities that degrade their performance, for instance in sensing applications. Here, we report on the precise control of the nonlinear and stochastic bistable dynamics of a levitated nanoparticle in high vacuum. We demonstrate how it can lead to efficient signal amplification schemes, including stochastic resonance. This work contributes to showing the use of levitated nanoparticles as a model system for stochastic bistable dynamics, with applications to a wide variety of fields.

  11. Controlling steady-state and dynamical properties of atomic optical bistability

    CERN Document Server

    Joshi, Amitabh

    2012-01-01

    This book provides a comprehensive introduction to the theoretical and experimental studies of atomic optical bistability and multistability, and their dynamical properties in systems with two- and three-level inhomogeneously-broadened atoms inside an optical cavity. By making use of the modified linear absorption and dispersion, as well as the greatly enhanced nonlinearity in the three-level electromagnetically induced transparency system, the optical bistablity and efficient all-optical switching can be achieved at relatively low laser powers, which can be well controlled and manipulated. Un

  12. Optical bistability via an external control laser in an erbium-doped-fiber laser

    Science.gov (United States)

    Ge, Qiang; Li, Shili; Wang, Zhiping; Zhen, Shenglai; Martín, Juan Carlos; Yu, Benli

    2018-01-01

    We demonstrate a new scheme for realizing the Optical Bistability (OB) in an erbium-doped-fiber laser with an external control laser. It is found that the OB can be significantly modified by changing the power and the wavelength of the control laser. We give an explanation of the bistability phenomenon based on numerical simulations, which are agreed very well with our experimental results. Our scheme provides a guideline for optimizing and controlling the OB in an erbium-doped-fiber laser, which might be useful for optical communications.

  13. VLSI architecture of a K-best detector for MIMO-OFDM wireless communication systems

    Energy Technology Data Exchange (ETDEWEB)

    Jian Haifang; Shi Yin, E-mail: jhf@semi.ac.c [Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083 (China)

    2009-07-15

    The K-best detector is considered as a promising technique in the MIMO-OFDM detection because of its good performance and low complexity. In this paper, a new K-best VLSI architecture is presented. In the proposed architecture, the metric computation units (MCUs) expand each surviving path only to its partial branches, based on the novel expansion scheme, which can predetermine the branches' ascending order by their local distances. Then a distributed sorter sorts out the new K surviving paths from the expanded branches in pipelines. Compared to the conventional K-best scheme, the proposed architecture can approximately reduce fundamental operations by 50% and 75% for the 16-QAM and the 64-QAM cases, respectively, and, consequently, lower the demand on the hardware resource significantly. Simulation results prove that the proposed architecture can achieve a performance very similar to conventional K-best detectors. Hence, it is an efficient solution to the K-best detector's VLSI implementation for high-throughput MIMO-OFDM systems.

  14. Parallel algorithms for placement and routing in VLSI design. Ph.D. Thesis

    Science.gov (United States)

    Brouwer, Randall Jay

    1991-01-01

    The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.

  15. Temperature persistent bistability and threshold switching in a single barrier heterostructure hot-electron diode

    DEFF Research Database (Denmark)

    Stasch, R.; Hey, R.; Asche, M.

    1996-01-01

    Bistable current–voltage characteristics caused by competition of tunneling through and field-enhanced thermionic emission across a single barrier are investigated in an n–-GaAs/Al0.34Ga0.66As/n+-GaAs structure. The S-shaped part of the characteristic persists in the whole temperature regime betw...

  16. Design criteria for bi-stable behavior in a buckled multi-layered MEMS bridge

    Science.gov (United States)

    Michael, Aron; Kwok, Chee Yee

    2006-10-01

    In this paper, the bi-stability of a buckled multi-layered micro-bridge with elastically constrained boundary conditions is studied theoretically and experimentally. The residual moment due to non-symmetric distribution of residual stress in the layers of the micro-bridge is taken into consideration. The buckled shape model, which characterizes the initial buckled deflection, is employed in this study. A systematic method of designing bi-stable buckled micro-bridges has been developed and applied to multi-layered structures. The method is tested against ANSYS simulation and shown to be in excellent agreement. Two multi-layer micro-bridges have been fabricated: (i) 2.5 µm thick low stress SiO2/1 µm thick high compressive stress SiO2/2 µm thick SCS Si; (ii) 1 µm thick high compressive stress SiO2/2 µm thick SCS Si. The fabricated bridges are tested for bi-stability by thermal actuation and the results agree well with the analysis. The intrinsic bi-stable nature of a buckled micro-bridge can only be guaranteed as long as the residual moment is within a certain threshold value.

  17. A micromachined silicon valve driven by a miniature bi-stable electro-magnetic actuator

    NARCIS (Netherlands)

    Bohm, S.; Burger, G.J.; Burger, G.J.; Korthorst, M.T.; Roseboom, F.

    2000-01-01

    In this paper a novel combination of a micromachined silicon valve with low dead volume and a bi-stable electromagnetic actuator produced by conventional machining is presented. The silicon valve part, 7×7×1 mm3 in dimensions, is a sandwich construction of two KOH etched silicon wafers with a layer

  18. Effective nonlinear optical properties and optical bistability in composite media containing spherical particles with different sizes.

    Science.gov (United States)

    Chen, H L; Gao, D L; Gao, L

    2016-03-07

    We study the effective nonlinear optical properties of composite media in which identical nonlinear nanospheres are randomly embedded in the linear host medium. In the weakly-nonlinear case, we aim at the effective linear permittivity and effective third-order nonlinear susceptibility with effective medium theory combined with the linear Mie theory. We show that large enhancement of optical nonlinear susceptibility can be achieved at the surface plasmon resonant wavelength, which can be tuned by changing the size of nanoparticles. Our numerical results are compared with those in the quasistatic limit or/and from Comsol simulations, good agreement is found. In the strong-nonlinear case, based on nonlinear Mie theory and self-consistent mean-field method, we study the optical bistability of the composite media. The optical bistability and tristability are found, and the bistable threshold fields are found to be strongly dependent on the sizes of nanoparticles and the incident wavelength. Such nonlinear nanocomposites with large optical nonlinearity and tunable bistable behavior are envisioned for use as nonlinear optical nanodevices such as optical nanoswitches, optical nanomemories and so on.

  19. Bistability breaks-off deterministic responses to intracortical stimulation during non-REM sleep

    Directory of Open Access Journals (Sweden)

    Andrea Pigorini

    2015-04-01

    These results point to bistability as the underlying critical mechanism that prevents the emergence of complex interactions in human thalamocortical networks during NREM sleep. Besides sleep, the same basic neurophysiological dynamics may play a role in pathological conditions(Casali et al., 2013; Rosanova et al., 2012 where cortico-cortical communication and consciousness are impaired in spite of preserved neuronal activity.

  20. Flexible Bistable Smectic-A Liquid Crystal Device Using Photolithography and Photoinduced Phase Separation

    Directory of Open Access Journals (Sweden)

    Yang Lu

    2012-01-01

    Full Text Available A flexible bistable smectic-A liquid crystal (SmA LC device using pixel-isolated mode was demonstrated, in which SmA LC molecules were isolated in pixels by vertical polymer wall and horizontal polymer layer. The above microstructure was achieved by using ultraviolet (UV photolithography and photoinduced phase separation. The polymer wall was fabricated by photolithography, and then the SmA LC was encapsulated in pixels between polymer wall through UV-induced phase separation, in which the polymer wall acts as supporting structure from mechanical pressure and maintains the cell gap from bending, and the polymer layer acts as adhesive for tight attachment of two substrates. The results demonstrated that all the intrinsic bistable properties of the SmA LC are preserved, and good electrooptical characteristics such as high contrast ratio and excellent stability of the bistable states were characterized. This kind of SmA bistable flexible display has high potential to be used as electronic paper, smart switchable reflective windows, and so forth.

  1. Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

    Science.gov (United States)

    Wang, Ting; Plecháč, Petr

    2017-12-01

    Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed.

  2. Interplay of Multisensory Processing, Attention, and Consciousness as Revealed by Bistable Figures

    Directory of Open Access Journals (Sweden)

    Su-Ling Yeh

    2011-10-01

    Full Text Available We examined the novel crossmodal semantic congruency effect on bistable figures in which a static stimulus gives rise to two competing percepts that alternate over time. Participants viewed the bistable figure “my wife or my mother-in-law” while listening to the voice of an old woman or a young lady speaking in an unfamiliar language. They had to report whether they saw the old woman, the young lady, or a mixed percept. Robust crossmodal semantic congruency effects in the measures of the first percept and the predominance duration were observed. The possibilities that the participants simply responded to, and/or that they fixed at the location in favor of, the percept congruent with the sound that they happened to hear were ruled out. When the participants were instructed to maintain their attention to a specific view, a strong top-down modulation on the perception of bistable figure was observed, although the audiovisual semantic congruency effect still remained. These results thus demonstrate that top-down attention (ie,, selection and/or voluntary control modulates the audiovisual semantic congruency effect. As the alternating percepts in bistable figures indicate competition for conscious perception, this study has important implications for the multifaceted interactions between multisensory processing, attention, and consciousness.

  3. Design and experiment of controlled bistable vortex induced vibration energy harvesting systems operating in chaotic regions

    Science.gov (United States)

    Huynh, B. H.; Tjahjowidodo, T.; Zhong, Z.-W.; Wang, Y.; Srikanth, N.

    2018-01-01

    Vortex induced vibration based energy harvesting systems have gained interests in these recent years due to its potential as a low water current energy source. However, the effectiveness of the system is limited only at a certain water current due to the resonance principle that governs the concept. In order to extend the working range, a bistable spring to support the structure is introduced on the system. The improvement on the performance is essentially dependent on the bistable gap as one of the main parameters of the nonlinear spring. A sufficiently large bistable gap will result in a significant performance improvement. Unfortunately, a large bistable gap might also increase a chance of chaotic responses, which in turn will result in diminutive harvested power. To mitigate the problem, an appropriate control structure is required to stabilize the chaotic vibrations of a VIV energy converter with the bistable supporting structure. Based on the nature of the double-well potential energy in a bistable spring, the ideal control structure will attempt to drive the responses to inter-well periodic vibrations in order to maximize the harvested power. In this paper, the OGY control algorithm is designed and implemented to the system. The control strategy is selected since it requires only a small perturbation in a structural parameter to execute the control effort, thus, minimum power is needed to drive the control input. Facilitated by a wake oscillator model, the bistable VIV system is modelled as a 4-dimensional autonomous continuous-time dynamical system. To implement the controller strategy, the system is discretized at a period estimated from the subspace hyperplane intersecting to the chaotic trajectory, whereas the fixed points that correspond to the desired periodic orbits are estimated by the recurrence method. Simultaneously, the Jacobian and sensitivity matrices are estimated by the least square regression method. Based on the defined fixed point and the

  4. Control of optical bistability and third-order nonlinearity via tunneling induced quantum interference in triangular quantum dot molecules

    Directory of Open Access Journals (Sweden)

    Si-Cong Tian

    2015-06-01

    Full Text Available The optical bistability of a triangular quantum dot molecules embedded inside a unidirectional ring cavity is studied. The type, the threshold and the hysteresis loop of the optical bistability curves can be modified by the tunneling parameters, as well as the probe laser field. The linear and nonlinear susceptibilities of the medium are also studied to interpret the corresponding results. The physical interpretation is that the tunneling can induce the quantum interference, which modifies the linear and the nonlinear response of the medium. As a consequence, the characteristics of the optical bistability are changed. The scheme proposed here can be utilized for optimizing and controlling the optical switching process.

  5. Electrical-pulse-induced resistivity modulation in Pt/TiO2-δ/Pt multilayer device related to nanoionics-based neuromorphic function

    Science.gov (United States)

    Kawamura, Kinya; Tsuchiya, Takashi; Takayanagi, Makoto; Terabe, Kazuya; Higuchi, Tohru

    2017-06-01

    Resistivity modulation behavior in Pt/TiO2-δ/Pt multilayer devices was investigated in terms of nanoionics-based neuromorphic function. The current relaxation behavior, which corresponds to short-term and long-term memorization in neuromorphic function, was analyzed using electrical pulses. In contrast to the huge difference in ionic conductivity for bulk crystal materials of TiO2-δ and WO3, the difference in the relaxation behavior was small. Rutherford backscattering spectrometry and hydrogen forward scattering spectrometry revealed that the TiO2-δ thin film contained 5.6 at. % of protons. This indicates that the neuromorphic function in TiO2-δ-based devices is caused by extrinsic proton transport, presumably through the grain boundary.

  6. Evolution of the bi-stable wake of a square-back automotive shape

    Science.gov (United States)

    Pavia, Giancarlo; Passmore, Martin; Sardu, Costantino

    2018-01-01

    Square-back shapes are popular in the automotive market for their high level of practicality. These geometries, however, are usually characterised by high drag and their wake dynamics present aspects, such as the coexistence of a long-time bi-stable behaviour and short-time global fluctuating modes that are not fully understood. In the present paper, the unsteady behaviour of the wake of a generic square-back car geometry is characterised with an emphasis on identifying the causal relationship between the different dynamic modes in the wake. The study is experimental, consisting of balance, pressure, and stereoscopic PIV measurements. Applying wavelet and cross-wavelet transforms to the balance data, a quasi-steady correlation is demonstrated between the forces and bi-stable modes. This is investigated by applying proper orthogonal decomposition to the pressure and velocity data sets and a new structure is proposed for each bi-stable state, consisting of a hairpin vortex that originates from one of the two model's vertical trailing edges and bends towards the opposite side as it merges into a single streamwise vortex downstream. The wake pumping motion is also identified and for the first time linked with the motion of the bi-stable vortical structure in the streamwise direction, resulting in out-of-phase pressure variations between the two vertical halves of the model base. A phase-averaged low-order model is also proposed that provides a comprehensive description of the mechanisms of the switch between the bi-stable states. It is demonstrated that, during the switch, the wake becomes laterally symmetric and, at this point, the level of interaction between the recirculating structures and the base reaches a minimum, yielding, for this geometry, a 7% reduction of the base drag compared to the time-averaged result.

  7. Involvement of the visual change detection process in facilitating perceptual alternation in the bistable image.

    Science.gov (United States)

    Urakawa, Tomokazu; Bunya, Mao; Araki, Osamu

    2017-08-01

    A bistable image induces one of two perceptual alternatives. When the bistable visual image is continuously viewed, the percept of the image alternates from one possible percept to the other. Perceptual alternation was previously reported to be induced by an exogenous perturbation in the bistable image, and this perturbation was theoretically interpreted to cause neural noise, prompting a transition between two stable perceptual states. However, little is known experimentally about the visual processing of exogenously driven perceptual alternation. Based on the findings of a previous behavioral study (Urakawa et al. in Perception 45:474-482, 2016), the present study hypothesized that the automatic visual change detection process, which is relevant to the detection of a visual change in a sequence of visual events, has an enhancing effect on the induction of perceptual alternation, similar to neural noise. In order to clarify this issue, we developed a novel experimental paradigm in which visual mismatch negativity (vMMN), an electroencephalographic brain response that reflects visual change detection, was evoked while participants continuously viewed the bistable image. In terms of inter-individual differences in neural and behavioral data, we found that enhancements in the peak amplitude of vMMN1, early vMMN at a latency of approximately 150 ms, correlated with increases in the proportion of perceptual alternation across participants. Our results indicate the involvement of automatic visual change detection in the induction of perceptual alternation, similar to neural noise, thereby providing a deeper insight into the neural mechanisms underlying exogenously driven perceptual alternation in the bistable image.

  8. A differential memristive synapse circuit for on-line learning in neuromorphic computing systems

    Science.gov (United States)

    Nair, Manu V.; Muller, Lorenz K.; Indiveri, Giacomo

    2017-12-01

    Spike-based learning with memristive devices in neuromorphic computing architectures typically uses learning circuits that require overlapping pulses from pre- and post-synaptic nodes. This imposes severe constraints on the length of the pulses transmitted in the network, and on the network’s throughput. Furthermore, most of these circuits do not decouple the currents flowing through memristive devices from the one stimulating the target neuron. This can be a problem when using devices with high conductance values, because of the resulting large currents. In this paper, we propose a novel circuit that decouples the current produced by the memristive device from the one used to stimulate the post-synaptic neuron, by using a novel differential scheme based on the Gilbert normalizer circuit. We show how this circuit is useful for reducing the effect of variability in the memristive devices, and how it is ideally suited for spike-based learning mechanisms that do not require overlapping pre- and post-synaptic pulses. We demonstrate the features of the proposed synapse circuit with SPICE simulations, and validate its learning properties with high-level behavioral network simulations which use a stochastic gradient descent learning rule in two benchmark classification tasks.

  9. Nanoscale RRAM-based synaptic electronics: toward a neuromorphic computing device

    Science.gov (United States)

    Park, Sangsu; Noh, Jinwoo; Choo, Myung-lae; Muqeem Sheri, Ahmad; Chang, Man; Kim, Young-Bae; Kim, Chang Jung; Jeon, Moongu; Lee, Byung-Geun; Lee, Byoung Hun; Hwang, Hyunsang

    2013-09-01

    Efforts to develop scalable learning algorithms for implementation of networks of spiking neurons in silicon have been hindered by the considerable footprints of learning circuits, which grow as the number of synapses increases. Recent developments in nanotechnologies provide an extremely compact device with low-power consumption. In particular, nanoscale resistive switching devices (resistive random-access memory (RRAM)) are regarded as a promising solution for implementation of biological synapses due to their nanoscale dimensions, capacity to store multiple bits and the low energy required to operate distinct states. In this paper, we report the fabrication, modeling and implementation of nanoscale RRAM with multi-level storage capability for an electronic synapse device. In addition, we first experimentally demonstrate the learning capabilities and predictable performance by a neuromorphic circuit composed of a nanoscale 1 kbit RRAM cross-point array of synapses and complementary metal-oxide-semiconductor neuron circuits. These developments open up possibilities for the development of ubiquitous ultra-dense, ultra-low-power cognitive computers.

  10. Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

    Science.gov (United States)

    Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

    2017-06-01

    We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

  11. Quasiperiodic AlGaAs superlattices for neuromorphic networks and nonlinear control systems

    Energy Technology Data Exchange (ETDEWEB)

    Malyshev, K. V., E-mail: malyshev@bmstu.ru [Electronics and Laser Technology Department, Bauman Moscow State Technical University, Moscow 105005 (Russian Federation)

    2015-01-28

    The application of quasiperiodic AlGaAs superlattices as a nonlinear element of the FitzHugh–Nagumo neuromorphic network is proposed and theoretically investigated on the example of Fibonacci and figurate superlattices. The sequences of symbols for the figurate superlattices were produced by decomposition of the Fibonacci superlattices' symbolic sequences. A length of each segment of the decomposition was equal to the corresponding figurate number. It is shown that a nonlinear network based upon Fibonacci and figurate superlattices provides better parallel filtration of a half-tone picture; then, a network based upon traditional diodes which have cubic voltage-current characteristics. It was found that the figurate superlattice F{sup 0}{sub 11}(1) as a nonlinear network's element provides the filtration error almost twice less than the conventional “cubic” diode. These advantages are explained by a wavelike shape of the decreasing part of the quasiperiodic superlattice's voltage-current characteristic, which leads to multistability of the network's cell. This multistability promises new interesting nonlinear dynamical phenomena. A variety of wavy forms of voltage-current characteristics opens up new interesting possibilities for quasiperiodic superlattices and especially for figurate superlattices in many areas—from nervous system modeling to nonlinear control systems development.

  12. Nanoscale RRAM-based synaptic electronics: toward a neuromorphic computing device.

    Science.gov (United States)

    Park, Sangsu; Noh, Jinwoo; Choo, Myung-Lae; Sheri, Ahmad Muqeem; Chang, Man; Kim, Young-Bae; Kim, Chang Jung; Jeon, Moongu; Lee, Byung-Geun; Lee, Byoung Hun; Hwang, Hyunsang

    2013-09-27

    Efforts to develop scalable learning algorithms for implementation of networks of spiking neurons in silicon have been hindered by the considerable footprints of learning circuits, which grow as the number of synapses increases. Recent developments in nanotechnologies provide an extremely compact device with low-power consumption.In particular, nanoscale resistive switching devices (resistive random-access memory (RRAM)) are regarded as a promising solution for implementation of biological synapses due to their nanoscale dimensions, capacity to store multiple bits and the low energy required to operate distinct states. In this paper, we report the fabrication, modeling and implementation of nanoscale RRAM with multi-level storage capability for an electronic synapse device. In addition, we first experimentally demonstrate the learning capabilities and predictable performance by a neuromorphic circuit composed of a nanoscale 1 kbit RRAM cross-point array of synapses and complementary metal-oxide-semiconductor neuron circuits. These developments open up possibilities for the development of ubiquitous ultra-dense, ultra-low-power cognitive computers.

  13. Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications

    Directory of Open Access Journals (Sweden)

    Francesca Sorgini

    2018-01-01

    Full Text Available We present a tactile telepresence system for real-time transmission of information about object stiffness to the human fingertips. Experimental tests were performed across two laboratories (Italy and Ireland. In the Italian laboratory, a mechatronic sensing platform indented different rubber samples. Information about rubber stiffness was converted into on-off events using a neuronal spiking model and sent to a vibrotactile glove in the Irish laboratory. Participants discriminated the variation of the stiffness of stimuli according to a two-alternative forced choice protocol. Stiffness discrimination was based on the variation of the temporal pattern of spikes generated during the indentation of the rubber samples. The results suggest that vibrotactile stimulation can effectively simulate surface stiffness when using neuronal spiking models to trigger vibrations in the haptic interface. Specifically, fractional variations of stiffness down to 0.67 were significantly discriminated with the developed neuromorphic haptic interface. This is a performance comparable, though slightly worse, to the threshold obtained in a benchmark experiment evaluating the same set of stimuli naturally with the own hand. Our paper presents a bioinspired method for delivering sensory feedback about object properties to human skin based on contingency–mimetic neuronal models, and can be useful for the design of high performance haptic devices.

  14. High Fill-Factor Imagers for Neuromorphic Processing Enabled by Floating-Gate Circuits

    Directory of Open Access Journals (Sweden)

    Hasler Paul

    2003-01-01

    Full Text Available In neuromorphic modeling of the retina, it would be very nice to have processing capabilities at the focal plane while retaining the density of typical active pixel sensor (APS imager designs. Unfortunately, these two goals have been mostly incompatible. We introduce our transform imager technology and basic architecture that uses analog floating-gate devices to make it possible to have computational imagers with high pixel densities. This imager approach allows programmable focal-plane processing that can perform retinal and higher-level bioinspired computation. The processing is performed continuously on the image via programmable matrix operations that can operate on the entire image or blocks within the image. The resulting dataflow architecture can directly perform computation of spatial transforms, motion computations, and stereo computations. The core imager performs computations at the pixel plane, but still holds a fill factor greater than 40 percent—comparable to the high fill factors of APS imagers. Each pixel is composed of a photodiode sensor element and a multiplier. We present experimental results from several imager arrays built in 0.5 m process (up to in an area of 4 millimeter squared.

  15. Sound stream segregation: a neuromorphic approach to solve the “cocktail party problem” in real-time

    OpenAIRE

    Chetan Singh Thakur; Runchun Mark Wang; Saeed eAfshar; Tara Julia Hamilton; Jonathan eTapson; Shihab eShamma; André evan Schaik

    2015-01-01

    The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the “cocktail party effect.” It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation ...

  16. A parallel VLSI architecture for a digital filter of arbitrary length using Fermat number transforms

    Science.gov (United States)

    Truong, T. K.; Reed, I. S.; Yeh, C. S.; Shao, H. M.

    1982-01-01

    A parallel architecture for computation of the linear convolution of two sequences of arbitrary lengths using the Fermat number transform (FNT) is described. In particular a pipeline structure is designed to compute a 128-point FNT. In this FNT, only additions and bit rotations are required. A standard barrel shifter circuit is modified so that it performs the required bit rotation operation. The overlap-save method is generalized for the FNT to compute a linear convolution of arbitrary length. A parallel architecture is developed to realize this type of overlap-save method using one FNT and several inverse FNTs of 128 points. The generalized overlap save method alleviates the usual dynamic range limitation in FNTs of long transform lengths. Its architecture is regular, simple, and expandable, and therefore naturally suitable for VLSI implementation.

  17. An Integrated Unix-based CAD System for the Design and Testing of Custom VLSI Chips

    Science.gov (United States)

    Deutsch, L. J.

    1985-01-01

    A computer aided design (CAD) system that is being used at the Jet Propulsion Laboratory for the design of custom and semicustom very large scale integrated (VLSI) chips is described. The system consists of a Digital Equipment Corporation VAX computer with the UNIX operating system and a collection of software tools for the layout, simulation, and verification of microcircuits. Most of these tools were written by the academic community and are, therefore, available to JPL at little or no cost. Some small pieces of software have been written in-house in order to make all the tools interact with each other with a minimal amount of effort on the part of the designer.

  18. Ant System-Corner Insertion Sequence: An Efficient VLSI Hard Module Placer

    Directory of Open Access Journals (Sweden)

    HOO, C.-S.

    2013-02-01

    Full Text Available Placement is important in VLSI physical design as it determines the time-to-market and chip's reliability. In this paper, a new floorplan representation which couples with Ant System, namely Corner Insertion Sequence (CIS is proposed. Though CIS's search complexity is smaller than the state-of-the-art representation Corner Sequence (CS, CIS adopts a preset boundary on the placement and hence, leading to search bound similar to CS. This enables the previous unutilized corner edges to become viable. Also, the redundancy of CS representation is eliminated in CIS leads to a lower search complexity of CIS. Experimental results on Microelectronics Center of North Carolina (MCNC hard block benchmark circuits show that the proposed algorithm performs comparably in terms of area yet at least two times faster than CS.

  19. An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm.

    Science.gov (United States)

    Chen, Ying-Lun; Hwang, Wen-Jyi; Ke, Chi-En

    2015-08-13

    A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO), and the feature extraction is carried out by the generalized Hebbian algorithm (GHA). To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction.

  20. Autonomous navigation of a mobile robot using custom-designed qualitative reasoning VLSI chips and boards

    Energy Technology Data Exchange (ETDEWEB)

    Pin, F.G.; Pattay, R.S. (Oak Ridge National Lab., TN (United States)); Watanabe, H.; Symon, J. (North Carolina Univ., Chapel Hill, NC (United States). Dept. of Computer Science)

    1991-01-01

    Two types of computer boards including custom-designed VLSI chips have been developed to add a qualitative reasoning capability to the real-time control of autonomous mobile robots. The design and operation of these boards are first described and an example of their use for the autonomous navigation of a mobile robot is presented. The development of qualitative reasoning schemes emulating human-like navigation is a-priori unknown environments is discussed. The efficiency of such schemes, which can consist of as little as a dozen qualitative rules, is illustrated in experiments involving an autonomous mobile robot navigating on the basis of very sparse inaccurate sensor data. 17 refs., 6 figs.

  1. Using custom-designed VLSI fuzzy inferencing chips for the autonomous navigation of a mobile robot

    Energy Technology Data Exchange (ETDEWEB)

    Pin, F.G.; Pattay, R.S. (Oak Ridge National Lab., TN (United States)); Watanabe, Hiroyuki; Symon, J. (North Carolina Univ., Chapel Hill, NC (United States). Dept. of Computer Science)

    1991-01-01

    Two types of computer boards including custom-designed VLSI fuzzy inferencing chips have been developed to add a qualitative reasoning capability to the real-time control of autonomous mobile robots. The design and operation of these boards are first described and an example of their use for the autonomous navigation of mobile robot is presented. The development of qualitative reasoning schemes emulating human-like navigation in apriori unknown environments is discussed. An approach using superposition of elemental sensor-based behaviors is shown to alloy easy development and testing of the inferencing rule base, while providing for progressive addition of behaviors to resolve situations of increasing complexity. The efficiency of such schemes, which can consist of as little as a dozen qualitative rules, is illustrated in experiments involving an autonomous mobile robot navigating on the basis of very sparse and inaccurate sensor data. 17 refs., 6 figs.

  2. Analog VLSI Models of Range-Tuned Neurons in the Bat Echolocation System

    Directory of Open Access Journals (Sweden)

    Horiuchi Timothy

    2003-01-01

    Full Text Available Bat echolocation is a fascinating topic of research for both neuroscientists and engineers, due to the complex and extremely time-constrained nature of the problem and its potential for application to engineered systems. In the bat's brainstem and midbrain exist neural circuits that are sensitive to the specific difference in time between the outgoing sonar vocalization and the returning echo. While some of the details of the neural mechanisms are known to be species-specific, a basic model of reafference-triggered, postinhibitory rebound timing is reasonably well supported by available data. We have designed low-power, analog VLSI circuits to mimic this mechanism and have demonstrated range-dependent outputs for use in a real-time sonar system. These circuits are being used to implement range-dependent vocalization amplitude, vocalization rate, and closest target isolation.

  3. Application and Integration of Quantum-Effect Devices for Cellular VLSI

    Science.gov (United States)

    Levy, Harold Joseph

    1995-01-01

    Cellular VLSI is that subclass of electronic systems for which small perturbations in a repeated cell design can dramatically influence the cost and performance of the entire system. This thesis presents examples of how the room-temperature quantum effects of tunneling and resonance may be used to condense the functionality of many conventional VLSI devices into a smaller and more efficient subunit, thus yielding tremendous benefits for the system as a whole. In particular, two and three-terminal applications of a complimentary pair of quantum-effect devices, the resonant-tunneling diode and the tunneling-switch diode, are presented. The first example is an image-segmentation network for machine vision, implemented by using resonant-tunneling diodes in one and two-dimensional networks to extract boundaries between regions of constant spatial texture. In this case a single quantum-effect device may replace up to thirty -three CMOS transistors per pixel. The second example is an artificial neural-network processor based on multistate resistors for synaptic conductances. These programmable resistors were produced by combining a vertically -integrated stack of resonant-tunneling diodes with a resistive load and a single MOSFET driven in its ohmic region. This macrostructure has the potential to provide synaptic changes on the picosecond time scale at length scales well below one micron. The third example is a current-mode transistorless memory array based on a two-dimensional network of cells containing only a single tunneling-switch diode and a resistive load. The resulting system has the potential for reaching more than an order-of-magnitude more cell density than state-of-the-art DRAM arrays, while operating at state -of-the-art SRAM speeds and reasonable power consumption.

  4. Contribution of disparity to the perception of 3D shape as revealed by bistability of stereoscopic Necker cubes.

    Science.gov (United States)

    Erkelens, C J

    2012-01-01

    The Necker cube is a famous demonstration of ambiguity in visual perception of 3D shape. Its bistability is attributed to indecisiveness because monocular cues do not allow the observer to infer one particular 3D shape from the 2D image. A remarkable but not appreciated observation is that Necker cubes are bistable during binocular viewing. One would expect disparity information to veto bistability. To investigate the effect of zero and non-zero disparity on perceptual bistability in detail, perceptual dominance durations were measured for luminance- and disparity-defined Necker cubes. Luminance-defined Necker cubes were bistable for all tested disparities between the front and back faces of the cubes. Absence of an effect of disparity on dominance durations suggested the suppression of disparity information. Judgments of depth between the front and back sides of the Necker cubes, however, showed that disparity affected perceived depth. Disparity-defined Necker cubes were also bistable but dominance durations showed different distributions. I propose a framework for 3D shape perception in which 3D shape is inferred from pictorial cues acting on luminance- and disparity-defined 2D shapes.

  5. Resistive Random Access Memory from Materials Development fnd Engineering to Novel Encryption and Neuromorphic Applications

    Science.gov (United States)

    Beckmann, Karsten

    Resistive random access memory (ReRAM or RRAM) is a novel form of non-volatile memory that is expected to play a major role in future computing and memory solutions. It has been shown that the resistance state of ReRAM devices can be precisely tuned by modulating switching voltages, by limiting peak current, and by adjusting the switching pulse properties. This enables the realization of novel applications such as memristive neuromorphic computing and neural network computing. I have developed two processes based on 100 and 300mm wafer platforms to demonstrate functional HfO2 based ReRAM devices. The first process is designed for a rapid materials engineering and device characterization, while the second is an advanced hybrid ReRAM/CMOS combination based on the IBM 65nm 10LPe process technology. The 100mm wafer efforts were used to show impacts of etch processes on ReRAM switching performance and the need for a rigorous structural evaluation of ReRAM devices before starting materials development. After an etch development, a bottom electrode comparison between the inert materials Pt, Ru and W was performed where Ru showed superior results with respect to yield and resilience against environmental impacts such as humidity over a 2-month period. A comparison of amorphous and crystalline devices showed no statistical difference in the performance with respect to random telegraph noise. This demonstrates, that the forming process fundamentally alters the crystallographic structure within and around the filament. The 300mm wafer development efforts were aimed towards implementing ReRAM in the FEOL, combined with CMOS, to yield a seamless process flow of 1 transistor 1 ReRAM structures (1T1R). This technology was customized with custom-developed tungsten metal 1 (M1) and dual tungsten/copper via 1 (V1) structures, within which the ReRAM stack is embedded. The ReRAM itself consists of an inert W bottom electrode, HfO2 based active switching layer, a Ti oxygen scavenger

  6. Reward-based learning under hardware constraints - Using a RISC processor embedded in a neuromorphic substrate

    Directory of Open Access Journals (Sweden)

    Simon eFriedmann

    2013-09-01

    Full Text Available In this study, we propose and analyze in simulations a new, highly flexible method of imple-menting synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. Thestudy focuses on globally modulated STDP, as a special use-case of this method. Flexibility isachieved by embedding a general-purpose processor dedicated to plasticity into the wafer. Toevaluate the suitability of the proposed system, we use a reward modulated STDP rule in a spiketrain learning task. A single layer of neurons is trained to fire at specific points in time withonly the reward as feedback. This model is simulated to measure its performance, i.e. the in-crease in received reward after learning. Using this performance as baseline, we then simulatethe model with various constraints imposed by the proposed implementation and compare theperformance. The simulated constraints include discretized synaptic weights, a restricted inter-face between analog synapses and embedded processor, and mismatch of analog circuits. Wefind that probabilistic updates can increase the performance of low-resolution weights, a simpleinterface between analog synapses and processor is sufficient for learning, and performance isinsensitive to mismatch. Further, we consider communication latency between wafer and theconventional control computer system that is simulating the environment. This latency increasesthe delay, with which the reward is sent to the embedded processor. Because of the time continu-ous operation of the analog synapses, delay can cause a deviation of the updates as compared tothe not delayed situation. We find that for highly accelerated systems latency has to be kept to aminimum. This study demonstrates the suitability of the proposed implementation to emulatethe selected reward modulated STDP learning rule. It is therefore an ideal candidate for imple-mentation in an upgraded version of the wafer-scale system developed within the BrainScaleSproject.

  7. A neuromorphic model of motor overflow in focal hand dystonia due to correlated sensory input

    Science.gov (United States)

    Sohn, Won Joon; Niu, Chuanxin M.; Sanger, Terence D.

    2016-10-01

    Objective. Motor overflow is a common and frustrating symptom of dystonia, manifested as unintentional muscle contraction that occurs during an intended voluntary movement. Although it is suspected that motor overflow is due to cortical disorganization in some types of dystonia (e.g. focal hand dystonia), it remains elusive which mechanisms could initiate and, more importantly, perpetuate motor overflow. We hypothesize that distinct motor elements have low risk of motor overflow if their sensory inputs remain statistically independent. But when provided with correlated sensory inputs, pre-existing crosstalk among sensory projections will grow under spike-timing-dependent-plasticity (STDP) and eventually produce irreversible motor overflow. Approach. We emulated a simplified neuromuscular system comprising two anatomically distinct digital muscles innervated by two layers of spiking neurons with STDP. The synaptic connections between layers included crosstalk connections. The input neurons received either independent or correlated sensory drive during 4 days of continuous excitation. The emulation is critically enabled and accelerated by our neuromorphic hardware created in previous work. Main results. When driven by correlated sensory inputs, the crosstalk synapses gained weight and produced prominent motor overflow; the growth of crosstalk synapses resulted in enlarged sensory representation reflecting cortical reorganization. The overflow failed to recede when the inputs resumed their original uncorrelated statistics. In the control group, no motor overflow was observed. Significance. Although our model is a highly simplified and limited representation of the human sensorimotor system, it allows us to explain how correlated sensory input to anatomically distinct muscles is by itself sufficient to cause persistent and irreversible motor overflow. Further studies are needed to locate the source of correlation in sensory input.

  8. Temperature tuning from direct to inverted bistable electroluminescence in resonant tunneling diodes

    Science.gov (United States)

    Hartmann, F.; Pfenning, A.; Rebello Sousa Dias, M.; Langer, F.; Höfling, S.; Kamp, M.; Worschech, L.; Castelano, L. K.; Marques, G. E.; Lopez-Richard, V.

    2017-10-01

    We study the electroluminescence (EL) emission of purely n-doped resonant tunneling diodes in a wide temperature range. The paper demonstrates that the EL originates from impact ionization and radiative recombination in the extended collector region of the tunneling device. Bistable current-voltage response and EL are detected and their respective high and low states are tuned under varying temperature. The bistability of the EL intensity can be switched from direct to inverted with respect to the tunneling current and the optical on/off ratio can be enhanced with increasing temperature. One order of magnitude amplification of the optical on/off ratio can be attained compared to the electrical one. Our observation can be explained by an interplay of moderate peak-to-valley current ratios, large resonance voltages, and electron energy loss mechanisms, and thus, could be applied as an alternative route towards optoelectronic applications of tunneling devices.

  9. Bifurcation properties of nematic liquid crystals exposed to an electric field: Switchability, bistability, and multistability

    KAUST Repository

    Cummings, L. J.

    2013-07-01

    Bistable liquid crystal displays (LCDs) offer the potential for considerable power savings compared with conventional (monostable) LCDs. The existence of two (or more) stable field-free states that are optically distinct means that contrast can be maintained in a display without an externally applied electric field. An applied field is required only to switch the device from one state to the other, as needed. In this paper we examine the basic physical principles involved in generating multiple stable states and the switching between these states. We consider a two-dimensional geometry in which variable surface anchoring conditions are used to control the steady-state solutions and explore how different anchoring conditions can influence the number and type of solutions and whether or not switching is possible between the states. We find a wide range of possible behaviors, including bistability, tristability, and tetrastability, and investigate how the solution landscape changes as the boundary conditions are tuned. © 2013 American Physical Society.

  10. Lake Restoration in Terms of Ecological Resilience: a Numerical Study of Biomanipulations under Bistable Conditions

    Directory of Open Access Journals (Sweden)

    Takashi Amemiya

    2005-12-01

    Full Text Available An abstract version of the comprehensive aquatic simulation model (CASM is found to exhibit bistability under intermediate loading of nutrient input, supporting the alternative-stable-states theory and field observations for shallow lakes. Our simulations of biomanipulations under the bistable conditions reveal that a reduction in the abundance of zooplanktivorous fish cannot switch the system from a turbid to a clear state. Rather, a direct reduction of phytoplankton and detritus was found to be most effective to make this switch in the present model. These results imply that multiple manipulations may be effective for practical restorations of lakes. We discuss the present results of biomanipulations in terms of ecological resilience in multivariable systems or natural systems.

  11. Phase-locking and bistability in neuronal networks with synaptic depression

    Science.gov (United States)

    Akcay, Zeynep; Huang, Xinxian; Nadim, Farzan; Bose, Amitabha

    2018-02-01

    We consider a recurrent network of two oscillatory neurons that are coupled with inhibitory synapses. We use the phase response curves of the neurons and the properties of short-term synaptic depression to define Poincaré maps for the activity of the network. The fixed points of these maps correspond to phase-locked modes of the network. Using these maps, we analyze the conditions that allow short-term synaptic depression to lead to the existence of bistable phase-locked, periodic solutions. We show that bistability arises when either the phase response curve of the neuron or the short-term depression profile changes steeply enough. The results apply to any Type I oscillator and we illustrate our findings using the Quadratic Integrate-and-Fire and Morris-Lecar neuron models.

  12. Pattern formation in the thiourea-iodate-sulfite system: Spatial bistability, waves, and stationary patterns

    Science.gov (United States)

    Horváth, Judit; Szalai, István; De Kepper, Patrick

    2010-06-01

    We present a detailed study of the reaction-diffusion patterns observed in the thiourea-iodate-sulfite (TuIS) reaction, operated in open one-side-fed reactors. Besides spatial bistability and spatio-temporal oscillatory dynamics, this proton autoactivated reaction shows stationary patterns, as a result of two back-to-back Turing bifurcations, in the presence of a low-mobility proton binding agent (sodium polyacrylate). This is the third aqueous solution system to produce stationary patterns and the second to do this through a Turing bifurcation. The stationary pattern forming capacities of the reaction are explored through a systematic design method, which is applicable to other bistable and oscillatory reactions. The spatio-temporal dynamics of this reaction is compared with that of the previous ferrocyanide-iodate-sulfite mixed Landolt system.

  13. Towards an optimal model for a bistable nematic liquid crystal display device

    KAUST Repository

    Cummings, L. J.

    2013-03-13

    Bistable liquid crystal displays offer the potential for considerable power savings compared with conventional (monostable) LCDs. The existence of two stable field-free states that are optically distinct means that contrast can be maintained in a display without an externally applied electric field. An applied field is required only to switch the device from one state to the other, as needed. In this paper we examine a theoretical model of a possible bistable device, originally proposed by Cummings and Richardson (Euro J Appl Math 17:435-463 2006), and explore means by which it may be optimized, in terms of optical contrast, manufacturing considerations, switching field strength, and switching times. The compromises inherent in these conflicting design criteria are discussed. © 2013 Springer Science+Business Media Dordrecht.

  14. A Compliant Bistable Mechanism Design Incorporating Elastica Buckling Beam Theory and Pseudo-Rigid-Body Model

    DEFF Research Database (Denmark)

    Sönmez, Ümit; Tutum, Cem Celal

    2008-01-01

    In this work, a new compliant bistable mechanism design is introduced. The combined use of pseudo-rigid-body model (PRBM) and the Elastica buckling theory is presented for the first time to analyze the new design. This mechanism consists of the large deflecting straight beams, buckling beams......, and a slider. The kinematic analysis of this new mechanism is studied, using nonlinear Elastica buckling beam theory, the PRBM of a large deflecting cantilever beam, the vector loop closure equations, and numerically solving nonlinear algebraic equations. A design method of the bistable mechanism...... in microdimensions is investigated by changing the relative stiffness of the flexible beams. The actuation force versus displacement characteristics of several cases is explored and the full simulation results of one of the cases are presented. This paper demonstrates the united application of the PRBM...

  15. Extracting nanosecond pulse signals via stochastic resonance generated by surface plasmon bistability.

    Science.gov (United States)

    Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan; Wang, Zhaolu; Li, Shaopeng

    2015-11-15

    A technology is investigated to extract nanosecond pulse noise hidden signals via stochastic resonance, which is based on surface plasmon bistability. A theoretical model for recovering nanosecond pulse signals is derived to describe the nonlinear process. It is found that the incident angle, polarization state, medium properties, and input noise intensity all determine the efficiency and fidelity of the output signal. The bistable behavior of the output intensity can be accurately controlled to obtain a cross-correlation gain larger than 6 in a wide range of input signal-to-noise ratio from 1∶5 to 1∶30. Meanwhile, the distortion in the time domain induced by phase shift can be reduced to a negligible level. This work provides a potential method for detecting low-level or hidden pulse signals in various communication fields.

  16. Application of Ge Nanowire for Two-Input Bistable Nanoelectromechanical Switch

    Directory of Open Access Journals (Sweden)

    Jana ANDZANE

    2013-09-01

    Full Text Available Recently, several research groups presented bistable two-terminal nanoelectromechanical switches based on individual single-clamped active element. All presented devices had one input electrode. Similar devices having two or more input electrodes have not been yet investigated. In this work we present the two-input bistable controlled nanoelectromechanical switch based on an individual single-clamped Ge nanowire. The switch is realised using in-situ SEM technique and operating due to balancing of electrostatic, adhesion and elastic forces. The operation conditions of the device are investigated and presented. The advantages and drawbacks of the device are discussed. DOI: http://dx.doi.org/10.5755/j01.ms.19.3.3086

  17. Inter-dot tunneling control of optical bistability in triple quantum dot molecules

    Energy Technology Data Exchange (ETDEWEB)

    Reza Hamedi, Hamid, E-mail: Hamid.r.Hamedi@gmail.com

    2014-09-15

    The behavior of optical bistability (OB) and optical multistability (OM) in a triple coupled quantum dot (QD) system is theoretically explored. It is found that the tunneling coupling between electronic levels has major effect on controlling the threshold and the hysteresis cycle shape of the optical bistability. The impact of incoherent pump field on the OB and OM behavior of such medium is then discussed. We realize that the threshold intensity reduces remarkably through increasing the rate of incoherent pumping. It is also demonstrated that the switch between OB and OM can be obtained just through proper adjusting the frequency detuning of probe field. It should be pointed that in this QD system we used tunneling instead of coupling lasers. These presented results may be applicable in real experiments for realizing an all-optical bistate switching or coding element in a solid-state platform.

  18. Coherent control of optical bistability and multistability via double dark resonances (DDRs)

    Science.gov (United States)

    Hamedi, Hamid Reza; Khaledi-Nasab, Ali; Raheli, Ali; Sahrai, M.

    2014-02-01

    We analyze theoretically optical bistability (OB) and optical multistability (OM) in a medium consisting of four-level cascade-type cold atoms by means of a unidirectional ring cavity. Due to existence of a radio-frequency (RF) field, upper two-folded levels are coupled and double dark resonances (DDRs) can arise. We show that by proper tuning of the RF field the threshold and the hysteresis cycle shape of OB and OM can be engineered. Also, the effect of intensity and frequency detuning of continuous-wave (cw) control laser field on bistable behavior of the medium is discussed. In addition, we explore the influence of different parameters on switching between OB and OM in this medium, which is applicable in all optical switching.

  19. Enhancement of response of a bistable VCSEL to modulated orthogonal optical feedback by vibrational resonance.

    Science.gov (United States)

    Chizhevsky, V N

    2012-11-01

    It is experimentally demonstrated that the response of a bistable vertical-cavity surface-emitting laser at a selected polarization to the effect of the modulated optical feedback at the orthogonal polarization can be considerably enhanced by the additional periodic current modulation via vibrational resonance. It shows up as a nonmonotonic dependence of the response at the frequency of the modulated optical feedback as a function of the amplitude of the current modulation. In such conditions the laser response can be amplified more than 80 times for a weak optical feedback. At the optimal amplitude of the current modulation a complete synchronization of optical switchings between polarization states with modulated optical feedback is observed. The effect of asymmetry of a bistable quasi-potential is also experimentally demonstrated.

  20. Double-well chimeras in 2D lattice of chaotic bistable elements

    Science.gov (United States)

    Shepelev, I. A.; Bukh, A. V.; Vadivasova, T. E.; Anishchenko, V. S.; Zakharova, A.

    2018-01-01

    We investigate spatio-temporal dynamics of a 2D ensemble of nonlocally coupled chaotic cubic maps in a bistability regime. In particular, we perform a detailed study on the transition ;coherence - incoherence; for varying coupling strength for a fixed interaction radius. For the 2D ensemble we show the appearance of amplitude and phase chimera states previously reported for 1D ensembles of nonlocally coupled chaotic systems. Moreover, we uncover a novel type of chimera state, double-well chimera, which occurs due to the interplay of the bistability of the local dynamics and the 2D ensemble structure. Additionally, we find double-well chimera behavior for steady states which we call double-well chimera death. A distinguishing feature of chimera patterns observed in the lattice is that they mainly combine clusters of different chimera types: phase, amplitude and double-well chimeras.

  1. VLSI Research

    Science.gov (United States)

    1983-10-31

    Caesar and Mextra and other old programs, as well as several previously-unreleased pro- grams, such as Lyra. Crystal. Peg, and Tpack . The 1983...release was sent to eight beta test sites in January, and began general distribution on April 1. EL1. Tpack : A System for Combining Graphics and Procedures

  2. VLSI Research

    Science.gov (United States)

    1984-04-01

    23,1984 / CONTINENTAL BALLROOMS 6-9 / 9:00 A.M. *T-ś! J SESSION XII: MICROPROCESSORS ANO MICROCONTROLLERS THAM 12.1: A 32b NMOS Microprocessor...roisideration, AlC is insensitive to the interface-wrapt..2 charge. The difference between AVr and Al£, therefore, will be the con- tribution from the...reduction of AVr . Since the degree of impact ionization increases with the substrate bias, the end result is the observed decrease in AVj- with

  3. A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks

    Directory of Open Access Journals (Sweden)

    Runchun Mark Wang

    2015-05-01

    Full Text Available We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP and Spike Timing Dependent Delay Plasticity (STDDP. We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 2^26 (64M synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted and/or delayed pre-synaptic spike to the target synapse in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 2^36 (64G synaptic adaptors on a current high-end FPGA platform.

  4. A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System

    Directory of Open Access Journals (Sweden)

    Zhen Zhang

    2017-08-01

    Full Text Available Artificial Neural Networks (ANNs, including Deep Neural Networks (DNNs, have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP. The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas.

  5. A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing

    Science.gov (United States)

    van de Burgt, Yoeri; Lubberman, Ewout; Fuller, Elliot J.; Keene, Scott T.; Faria, Grégorio C.; Agarwal, Sapan; Marinella, Matthew J.; Alec Talin, A.; Salleo, Alberto

    2017-04-01

    The brain is capable of massively parallel information processing while consuming only ~1-100 fJ per synaptic event. Inspired by the efficiency of the brain, CMOS-based neural architectures and memristors are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low voltage and energy (500 distinct, non-volatile conductance states within a ~1 V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.

  6. A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System.

    Science.gov (United States)

    Zhang, Zhen; Ma, Cheng; Zhu, Rong

    2017-08-23

    Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs), have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA) architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP). The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO) real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas.

  7. A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks.

    Science.gov (United States)

    Wang, Runchun M; Hamilton, Tara J; Tapson, Jonathan C; van Schaik, André

    2015-01-01

    We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP) and Spike Timing Dependent Delay Plasticity (STDDP). We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 2(26) (64M) synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted or delayed pre-synaptic spike to the post-synaptic neuron in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 2(36) (64G) synaptic adaptors on a current high-end FPGA platform.

  8. Optical regeneration based on noise generated in bistable devices: going from 2R to 3R

    OpenAIRE

    González Marcos, Ana; Vivero Palmer, Tania Rosa; Rivas Moscoso, José Manuel; Martín Pereda, José Antonio

    2007-01-01

    In this paper we propose to employ an instability that occurs in bistable devices as a control signal at the reception stage to generate the clock signal. One of the adopted configurations is composed of two semiconductor optical amplifiers arranged in a cascaded structure. This configuration has an output equivalent to that obtained from Self-Electrooptic Effect Devices (SEEDs), and it can implement the main Boolean functions of two binary inputs. These outputs, obtained from the addition of...

  9. Demonstration of brain noise on human EEG signals in perception of bistable images

    Science.gov (United States)

    Grubov, Vadim V.; Runnova, Anastasiya E.; Kurovskaya, Maria K.; Pavlov, Alexey N.; Koronovskii, Alexey A.; Hramov, Alexander E.

    2016-03-01

    In this report we studied human brain activity in the case of bistable visual perception. We proposed a new approach for quantitative characterization of this activity based on analysis of EEG oscillatory patterns and evoked potentials. Accordingly to theoretical background, obtained experimental EEG data and results of its analysis we studied a characteristics of brain activity during decision-making. Also we have shown that decisionmaking process has the special patterns on the EEG data.

  10. Basins of attraction of the bistable region of time-delayed cutting dynamics

    Science.gov (United States)

    Yan, Yao; Xu, Jian; Wiercigroch, Marian

    2017-09-01

    This paper investigates the effects of bistability in a nonsmooth time-delayed dynamical system, which is often manifested in science and engineering. Previous studies on cutting dynamics have demonstrated persistent coexistence of chatter and chatter-free responses in a bistable region located in the linearly stable zone. As there is no widely accepted definition of basins of attraction for time-delayed systems, bistable regions are coined as unsafe zones (UZs). Hence, we have attempted to define the basins of attraction and stability basins for a typical delayed system to get insight into the bistability in systems with time delays. Special attention was paid to the influences of delayed initial conditions, starting points, and states at time zero on the long-term dynamics of time-delayed systems. By using this concept, it has been confirmed that the chatter is prone to occur when the waviness frequency in the workpiece surface coincides with the effective natural frequency of the cutting process. Further investigations unveil a thin "boundary layer" inside the UZ in the immediate vicinity of the stability boundary, in which we observe an extremely fast growth of the chatter basin stability. The results reveal that the system is more stable when the initial cutting depth is smaller. The physics of the tool deflection at the instant of the tool-workpiece engagement is used to evaluate the cutting safety, and the safe level could be zero when the geometry of tool engagement is unfavorable. Finally, the basins of attraction are used to quench the chatter by a single strike, where the resultant "islands" offer an opportunity to suppress the chatter even when the cutting is very close to the stability boundary.

  11. Bistability and low-frequency fluctuations in semiconductor lasers with optical feedback: a theoretical analysis

    DEFF Research Database (Denmark)

    Mørk, Jesper; Tromborg, Bjarne; Christiansen, Peter Leth

    1988-01-01

    Near-threshold operation of a semiconductor laser exposed to moderate optical feedback may lead to low-frequency fluctuations. In the same region, a kink is observed in the light-current characteristic. Here it is demonstrated that these nonlinear phenomena are predicted by a noise driven multimode...... traveling-wave model. The dynamics of the low-frequency fluctuations are explained qualitatively in terms of bistability through an iterative description...

  12. Solution-verified reliability analysis and design of bistable MEMS using error estimation and adaptivity.

    Energy Technology Data Exchange (ETDEWEB)

    Eldred, Michael Scott; Subia, Samuel Ramirez; Neckels, David; Hopkins, Matthew Morgan; Notz, Patrick K.; Adams, Brian M.; Carnes, Brian; Wittwer, Jonathan W.; Bichon, Barron J.; Copps, Kevin D.

    2006-10-01

    This report documents the results for an FY06 ASC Algorithms Level 2 milestone combining error estimation and adaptivity, uncertainty quantification, and probabilistic design capabilities applied to the analysis and design of bistable MEMS. Through the use of error estimation and adaptive mesh refinement, solution verification can be performed in an automated and parameter-adaptive manner. The resulting uncertainty analysis and probabilistic design studies are shown to be more accurate, efficient, reliable, and convenient.

  13. Distribution of residence times in bistable noisy systems with time-delayed feedback

    OpenAIRE

    Curtin, D.

    2004-01-01

    We analyze theoretically and experimentally the residence time distribution of bistable systems in the presence of noise and time-delayed feedback. We explain various nonexponential features of the residence time distribution using a two-state model and obtain a quantitative agreement with an experiment based on a Schmitt trigger. The limitations of the two-state model are also analyzed theoretically and experimentally using a semiconductor laser with optoelectronic feedback.

  14. Priming with real motion biases visual cortical response to bistable apparent motion

    OpenAIRE

    Zhang, Qing-fang; Wen, Yunqing; Zhang, Deng; She, Liang; Wu, Jian-Young; Dan, Yang; Poo, Mu-ming

    2012-01-01

    Apparent motion quartet is an ambiguous stimulus that elicits bistable perception, with the perceived motion alternating between two orthogonal paths. In human psychophysical experiments, the probability of perceiving motion in each path is greatly enhanced by a brief exposure to real motion along that path. To examine the neural mechanism underlying this priming effect, we used voltage-sensitive dye (VSD) imaging to measure the spatiotemporal activity in the primary visual cortex (V1) of awa...

  15. The optimal regulation mode of Bcl-2 apoptotic switch revealed by bistability analysis.

    Science.gov (United States)

    Yin, Zhiyong; Qi, Hong; Liu, Lili; Jin, Zhen

    2017-12-01

    In most cell types, apoptosis occurs by the mitochondrial outer membrane permeability (MOMP)-mediated pathway, which is controlled by Bcl-2 family proteins (often referred to as Bcl-2 apoptotic switch). These proteins, which display a range of bioactivities, can be divided into four types: effectors, inhibitors, activators and sensitizers. Although the complex interactions among Bcl-2 family members have been studied intensively, a unifying hypothesis for the mechanism they use to regulate MOMP remains elusive. The bistable behaviors are often used to explain the all-or-none decisions of apoptosis. Here, we attempt to reveal the optimal interaction mode by comparing the bistable performances of three different modes (direct activation, indirect activation, and unified mode) proposed by biologists. Using the method that combines mathematical analysis and numerical simulation, we discover that bistability can only emerge from the unified mode when proteins synthesis and degradation are considered, which is in favor of it as an optimal regulation mode of Bcl-2 apoptotic switch. The parameter sensitivity analysis for the unified mode further consolidates this view. Moreover, two-parameter bifurcation analysis suggests that the sensitizers lower the threshold of activation of Bax, but have a negative influence on the width of the bistability region. Our study may provide mechanistic insights into the heterogeneity of tumor cells and the efficiency of BH3 mimetic-mediated killing of cancer cells, and suggest that a combination treatment might be required to overcome apoptosis resistance in the Bcl-2 family targeted therapies. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Manually operatable on-chip bistable pneumatic microstructures for microfluidic manipulations.

    Science.gov (United States)

    Chen, Arnold; Pan, Tingrui

    2014-09-07

    Bistable microvalves are of particular interest because of their distinct nature of requiring energy consumption only during the transition between the open and closed states. This characteristic can be highly advantageous in reducing the number of external inputs and the complexity of control circuitries since microfluidic devices as contemporary lab-on-a-chip platforms are transferring from research settings to low-resource environments with high integrability and a small form factor. In this paper, we first present manually operatable, on-chip bistable pneumatic microstructures (BPMs) for microfluidic manipulation. The structural design and operation of the BPM devices can be readily integrated into any pneumatically powered microfluidic network consisting of pneumatic and fluidic channels. It is mainly composed of a vacuum activation chamber (VAC) and a pressure release chamber (PRC), of which users have direct control through finger pressing to switch either to the bistable vacuum state (VS) or the atmospheric state (AS). We have integrated multiple BPM devices into a 4-to-1 microfluidic multiplexor to demonstrate on-chip digital flow switching from different sources. Furthermore, we have shown its clinical relevance in a point-of-care diagnostic chip that processes blood samples to identify the distinct blood types (A/B/O) on-chip.

  17. Bistable light shutter using dye-doped liquid crystals for a see-through display

    Science.gov (United States)

    Huh, Jae-Won; Heo, Joon; Yu, Byeong-Huh; Yoon, Tae-Hoon

    2016-03-01

    See-through displays have got high attention as one of the next generation display devices. Especially, see-through displays that use organic light-emitting diodes (OLEDs) and liquid crystal displays (LCDs) have been actively studied. However, a see-through display using OLEDs cannot provide black color because of their see-through area. Although a see-through display using LCDs can provide black color with crossed polarizers, it cannot block the background. This inevitable problem can be solved by placing a light shutter at the back of a see-through display. To maintain the transparent or opaque state, an electric field must be applied to a light shutter. To achieve low power consumption, a bistable light shutter using polymer-stabilized cholesteric liquid crystals (CLC) has been proposed. It is switchable between the translucent and transparent states only. Therefore, it cannot provide black color. Moreover, it cannot block the background perfectly because of poor performance in the translucent state. In this work we will introduce a bistable light shutter using dye-doped CLCs. To improve the electro-optic characteristics in the opaque state, we employed a crossed electrode structure instead of a parallel one. We will demonstrate that the light shutter can exhibit stable bistable operation between the transparent homeotropic and opaque focal-conic states thanks to polymer stabilization.

  18. Bistability in a hybrid optomechanical system: effect of a gain medium

    Science.gov (United States)

    Asghari Nejad, A.; Baghshahi, H. R.; Askari, H. R.

    2017-11-01

    In this paper, we investigate the optical bistability of a hybrid optomechanical system consisting of two coupled cavities: a bare optomechanical cavity (with an oscillating mirror at one end) and a traditional one. The traditional cavity is filled with an optical parametric amplifier (OPA), and an input pump laser is applied to it. The Hamiltonian of the system is written in a rotating frame. The dynamics of the system is driven by the quantum Langevin equations of motion. We demonstrate that the presence of an OPA can dramatically affect the type of stability of the optomechanical cavity. We show that it is possible to create a proper optical bistability for the optomechanical cavity by changing the gain coefficient of the OPA. Also, it is shown that changing the phase of the field driving the OPA has two different effects on the bistability region of the optomechanical cavity. Moreover, we show that by choosing a proper value for the detuning of the traditional cavity it is possible to observe a tristable behavior in the optomechanical cavity.

  19. On square-wave-driven stochastic resonance for energy harvesting in a bistable system

    Directory of Open Access Journals (Sweden)

    Dongxu Su

    2014-11-01

    Full Text Available Stochastic resonance is a physical phenomenon through which the throughput of energy within an oscillator excited by a stochastic source can be boosted by adding a small modulating excitation. This study investigates the feasibility of implementing square-wave-driven stochastic resonance to enhance energy harvesting. The motivating hypothesis was that such stochastic resonance can be efficiently realized in a bistable mechanism. However, the condition for the occurrence of stochastic resonance is conventionally defined by the Kramers rate. This definition is inadequate because of the necessity and difficulty in estimating white noise density. A bistable mechanism has been designed using an explicit analytical model which implies a new approach for achieving stochastic resonance in the paper. Experimental tests confirm that the addition of a small-scale force to the bistable system excited by a random signal apparently leads to a corresponding amplification of the response that we now term square-wave-driven stochastic resonance. The study therefore indicates that this approach may be a promising way to improve the performance of an energy harvester under certain forms of random excitation.

  20. Dynamics and bistability in a reduced model of the lac operon

    Science.gov (United States)

    Yildirim, Necmettin; Santillán, Moisés; Horike, Daisuke; Mackey, Michael C.

    2004-06-01

    It is known that the lac operon regulatory pathway is capable of showing bistable behavior. This is an important complex feature, arising from the nonlinearity of the involved mechanisms, which is essential to understand the dynamic behavior of this molecular regulatory system. To find which of the mechanisms involved in the regulation of the lac operon is the origin of bistability, we take a previously published model which accounts for the dynamics of mRNA, lactose, allolactose, permease and β-galactosidase involvement and simplify it by ignoring permease dynamics (assuming a constant permease concentration). To test the behavior of the reduced model, three existing sets of data on β-galactosidase levels as a function of time are simulated and we obtain a reasonable agreement between the data and the model predictions. The steady states of the reduced model were numerically and analytically analyzed and it was shown that it may indeed display bistability, depending on the extracellular lactose concentration and growth rate.

  1. Transcriptional Infidelity Promotes Heritable Phenotypic Change in a Bistable Gene Network

    Science.gov (United States)

    Gordon, Alasdair J. E; Halliday, Jennifer A; Blankschien, Matthew D; Burns, Philip A; Yatagai, Fumio; Herman, Christophe

    2009-01-01

    Bistable epigenetic switches are fundamental for cell fate determination in unicellular and multicellular organisms. Regulatory proteins associated with bistable switches are often present in low numbers and subject to molecular noise. It is becoming clear that noise in gene expression can influence cell fate. Although the origins and consequences of noise have been studied, the stochastic and transient nature of RNA errors during transcription has not been considered in the origin or modeling of noise nor has the capacity for such transient errors in information transfer to generate heritable phenotypic change been discussed. We used a classic bistable memory module to monitor and capture transient RNA errors: the lac operon of Escherichia coli comprises an autocatalytic positive feedback loop producing a heritable all-or-none epigenetic switch that is sensitive to molecular noise. Using single-cell analysis, we show that the frequency of epigenetic switching from one expression state to the other is increased when the fidelity of RNA transcription is decreased due to error-prone RNA polymerases or to the absence of auxiliary RNA fidelity factors GreA and GreB (functional analogues of eukaryotic TFIIS). Therefore, transcription infidelity contributes to molecular noise and can effect heritable phenotypic change in genetically identical cells in the same environment. Whereas DNA errors allow genetic space to be explored, RNA errors may allow epigenetic or expression space to be sampled. Thus, RNA infidelity should also be considered in the heritable origin of altered or aberrant cell behaviour. PMID:19243224

  2. Signal denoising using stochastic resonance and bistable circuit for acoustic emission-based structural health monitoring

    Science.gov (United States)

    Kim, Jinki; Harne, Ryan L.; Wang, K. W.

    2017-04-01

    Noise is unavoidable and ever-present in measurements. As a result, signal denoising is a necessity for many scientific and engineering disciplines. In particular, structural health monitoring applications aim to detect often weak anomaly responses generated by incipient damage (such as acoustic emission signals) from background noise that contaminates the signals. Among various approaches, stochastic resonance has been widely studied and adopted for denoising and weak signal detection to enhance the reliability of structural heath monitoring. On the other hand, many of the advancements have been focused on detecting useful information from the frequency domain generally in a postprocessing environment, such as identifying damage-induced frequency changes that become more prominent by utilizing stochastic resonance in bistable systems, rather than recovering the original time domain responses. In this study, a new adaptive signal conditioning strategy is presented for on-line signal denoising and recovery, via utilizing the stochastic resonance in a bistable circuit sensor. The input amplitude to the bistable system is adaptively adjusted to favorably activate the stochastic resonance based on the noise level of the given signal, which is one of the few quantities that can be readily assessed from noise contaminated signals in practical situations. Numerical investigations conducted by employing a theoretical model of a double-well Duffing analog circuit demonstrate the operational principle and confirm the denoising performance of the new method. This study exemplifies the promising potential of implementing the new denoising strategy for enhancing on-line acoustic emission-based structural health monitoring.

  3. On square-wave-driven stochastic resonance for energy harvesting in a bistable system

    Energy Technology Data Exchange (ETDEWEB)

    Su, Dongxu, E-mail: sudx@iis.u-tokyo.ac.jp [Graduate School of Engineering, The University of Tokyo, Tokyo 1538505 (Japan); Zheng, Rencheng; Nakano, Kimihiko [Institute of Industrial Science, The University of Tokyo, Tokyo 1538505 (Japan); Cartmell, Matthew P [Department of Mechanical Engineering, University of Sheffield, Sheffield S1 3JD (United Kingdom)

    2014-11-15

    Stochastic resonance is a physical phenomenon through which the throughput of energy within an oscillator excited by a stochastic source can be boosted by adding a small modulating excitation. This study investigates the feasibility of implementing square-wave-driven stochastic resonance to enhance energy harvesting. The motivating hypothesis was that such stochastic resonance can be efficiently realized in a bistable mechanism. However, the condition for the occurrence of stochastic resonance is conventionally defined by the Kramers rate. This definition is inadequate because of the necessity and difficulty in estimating white noise density. A bistable mechanism has been designed using an explicit analytical model which implies a new approach for achieving stochastic resonance in the paper. Experimental tests confirm that the addition of a small-scale force to the bistable system excited by a random signal apparently leads to a corresponding amplification of the response that we now term square-wave-driven stochastic resonance. The study therefore indicates that this approach may be a promising way to improve the performance of an energy harvester under certain forms of random excitation.

  4. Effects of boundary conditions on bistable behaviour in axisymmetrical shallow shells.

    Science.gov (United States)

    Sobota, P M; Seffen, K A

    2017-07-01

    Multistable shells are thin-walled structures that have more than one stable state of self-stress. We consider isotropic axisymmetrical shallow shells of arbitrary polynomial shapes using a Föppl-von Kármán analytical model. By employing a Rayleigh-Ritz approach, we identify stable shapes from local minima in the strain energy formulation, and we formally characterize the level of influence of the boundary conditions on the critical geometry for achieving bistable inversion-an effect not directly answered in the literature. Systematic insight is afforded by connecting the boundary to ground through sets of extensional and rotational linear springs. For typical cap-like shells, it is shown that bistability is generally enhanced when the extensional spring stiffness increases and when the rotational spring stiffness decreases, i.e. when boundary movements in-plane are resisted but when their rotations are not; however, for certain other shapes and large in-plane stiffness values, bistability can be enhanced by resisting but not entirely preventing edge rotations. Our predictions are furnished as detailed regime maps of the critical geometry, which are accurately correlated against finite-element analysis. Furthermore, the suitabilities of single degree-of-freedom models, for which solutions are achieved in closed form, are evaluated and compared to our more accurate predictions.

  5. Numerical and Experimental Studies on Nonlinear Dynamics and Performance of a Bistable Piezoelectric Cantilever Generator

    Directory of Open Access Journals (Sweden)

    Kangkang Guo

    2015-01-01

    Full Text Available A piezo-magneto-elastically coupled distributed-parameter model of a bistable piezoelectric cantilever generator is developed by using the generalized Hamilton principle. The influence of the spacing between two adjacent magnets on the static bifurcation characteristics of the system is studied and the range of magnet spacing corresponding to the bistable states is obtained. Numerical and experimental studies are carried out to analyze the bifurcation, response characteristics, and their impact on the electrical output performance under varying external excitations. Results indicate that interwell limit cycle motion of the beam around the two centers corresponds to optimum power output; interwell chaotic motion and multiperiodic motion including intrawell oscillations are less effective. At a given frequency, the phenomena of symmetric-breaking and amplitude-phase modulation are observed with increase of base excitation. Both period-doubling bifurcation and intermittency routes to chaotic motion in the bistable system are found. It can be observed that the power output is not proportional to the excitation level because of the bifurcation behaviours.

  6. Assessing the effects of audiovisual semantic congruency on the perception of a bistable figure.

    Science.gov (United States)

    Hsiao, Jhih-Yun; Chen, Yi-Chuan; Spence, Charles; Yeh, Su-Ling

    2012-06-01

    Bistable figures provide a fascinating window through which to explore human visual awareness. Here we demonstrate for the first time that the semantic context provided by a background auditory soundtrack (the voice of a young or old female) can modulate an observer's predominant percept while watching the bistable "my wife or my mother-in-law" figure (Experiment 1). The possibility of a response-bias account-that participants simply reported the percept that happened to be congruent with the soundtrack that they were listening to-was excluded in Experiment 2. We further demonstrate that this crossmodal semantic effect was additive with the manipulation of participants' visual fixation (Experiment 3), while it interacted with participants' voluntary attention (Experiment 4). These results indicate that audiovisual semantic congruency constrains the visual processing that gives rise to the conscious perception of bistable visual figures. Crossmodal semantic context therefore provides an important mechanism contributing to the emergence of visual awareness. Copyright © 2012 Elsevier Inc. All rights reserved.

  7. Thermal Effect on Bistable Behaviour of T700/3234 Anti-symmetric Cylindrical Shells

    Directory of Open Access Journals (Sweden)

    ZHANG Zheng

    2016-10-01

    Full Text Available The temperature effects on the bi-stable characteristics of T700/3234 anti-symmetric carbon-fiber composite structure were studied. Three different layup specimens were prepared through composite molding process.The two points loading method was used in the experiment. The modified experimental testing machine (the experimental testing machine could be used to induce the bistable composite shell to snap between the two stable shapes, and continually capture the data in the experimental process. was related to tensile testing machine at present. The load-displacement curvatures under the temperature of 20℃,40℃,60℃ and 80℃ were given. The snap load was recorded and the photos were taken in the experimental process. After the experiment, the detailed data of curvature and twisting curvature were obtained by image processing technology. The variation law of the coiled-up radius, out-of-plane displacement, maximum snap-through and snap-back loads were analyzed. The effect on the composite structure was also discussed.The result shows that the thermal effect is vital to the bistable snaps process, and corresponding influence trends to the snap through and snap back process are given.

  8. Revisiting bistability in the lysis/lysogeny circuit of bacteriophage lambda.

    Directory of Open Access Journals (Sweden)

    Michael Bednarz

    Full Text Available The lysis/lysogeny switch of bacteriophage lambda serves as a paradigm for binary cell fate decision, long-term maintenance of cellular state and stimulus-triggered switching between states. In the literature, the system is often referred to as "bistable." However, it remains unclear whether this term provides an accurate description or is instead a misnomer. Here we address this question directly. We first quantify transcriptional regulation governing lysogenic maintenance using a single-cell fluorescence reporter. We then use the single-cell data to derive a stochastic theoretical model for the underlying regulatory network. We use the model to predict the steady states of the system and then validate these predictions experimentally. Specifically, a regime of bistability, and the resulting hysteretic behavior, are observed. Beyond the steady states, the theoretical model successfully predicts the kinetics of switching from lysogeny to lysis. Our results show how the physics-inspired concept of bistability can be reliably used to describe cellular phenotype, and how an experimentally-calibrated theoretical model can have accurate predictive power for cell-state switching.

  9. Stochasticity, bistability and the wisdom of crowds: a model for associative learning in genetic regulatory networks.

    Science.gov (United States)

    Sorek, Matan; Balaban, Nathalie Q; Loewenstein, Yonatan

    2013-01-01

    It is generally believed that associative memory in the brain depends on multistable synaptic dynamics, which enable the synapses to maintain their value for extended periods of time. However, multistable dynamics are not restricted to synapses. In particular, the dynamics of some genetic regulatory networks are multistable, raising the possibility that even single cells, in the absence of a nervous system, are capable of learning associations. Here we study a standard genetic regulatory network model with bistable elements and stochastic dynamics. We demonstrate that such a genetic regulatory network model is capable of learning multiple, general, overlapping associations. The capacity of the network, defined as the number of associations that can be simultaneously stored and retrieved, is proportional to the square root of the number of bistable elements in the genetic regulatory network. Moreover, we compute the capacity of a clonal population of cells, such as in a colony of bacteria or a tissue, to store associations. We show that even if the cells do not interact, the capacity of the population to store associations substantially exceeds that of a single cell and is proportional to the number of bistable elements. Thus, we show that even single cells are endowed with the computational power to learn associations, a power that is substantially enhanced when these cells form a population.

  10. Stochasticity, bistability and the wisdom of crowds: a model for associative learning in genetic regulatory networks.

    Directory of Open Access Journals (Sweden)

    Matan Sorek

    Full Text Available It is generally believed that associative memory in the brain depends on multistable synaptic dynamics, which enable the synapses to maintain their value for extended periods of time. However, multistable dynamics are not restricted to synapses. In particular, the dynamics of some genetic regulatory networks are multistable, raising the possibility that even single cells, in the absence of a nervous system, are capable of learning associations. Here we study a standard genetic regulatory network model with bistable elements and stochastic dynamics. We demonstrate that such a genetic regulatory network model is capable of learning multiple, general, overlapping associations. The capacity of the network, defined as the number of associations that can be simultaneously stored and retrieved, is proportional to the square root of the number of bistable elements in the genetic regulatory network. Moreover, we compute the capacity of a clonal population of cells, such as in a colony of bacteria or a tissue, to store associations. We show that even if the cells do not interact, the capacity of the population to store associations substantially exceeds that of a single cell and is proportional to the number of bistable elements. Thus, we show that even single cells are endowed with the computational power to learn associations, a power that is substantially enhanced when these cells form a population.

  11. The analytical model for crosstalk noise of current-mode signaling in coupled RLC interconnects of VLSI circuits

    Science.gov (United States)

    Xu, Peng; Pan, Zhongliang

    2017-09-01

    With the continuous advancement of semiconductor technology, the interconnects crosstalk has had a great influence on the performances of VLSI circuits. To date, most of the research about the interconnects of VLSI circuits focus on the voltage-mode signaling (VMS) scheme while the current-mode signaling (CMS) scheme is rarely analyzed. First of all, an equivalent circuit model of two-line coupled interconnects is presented in this paper, which is applicable to both the CMS and VMS schemes. The coupling capacitive and mutual inductive are taken into account in the equivalent circuit model. Secondly, the output noise of CMS and VMS schemes are investigated in the paper according to the decoupling technique and ABCD parameter matrix approach at local level, intermediate level and global level, respectively. Moreover, the experimental results show that the CMS interconnects have lesser noise peak, noise width and noise amplitude than the VMS interconnects in the same cases, and the CMS scheme is especially suitable for the global interconnects communication of VLSI circuits. It is found that the results obtained by ABCD parameter matrix approach are in good accordance with the simulation results of the advanced design system. Project supported by the Guangdong Provincial Natural Science Foundation of China (No. 2014A030313441), the Guangzhou Science and Technology Project (No. 201510010169), the Guangdong Province Science and Technology Project (No. 2016B090918071), and the National Natural Science Foundation of China (No. 61072028).

  12. VLSI System Implementation of 200 MHz, 8-bit, 90nm CMOS Arithmetic and Logic Unit (ALU Processor Controller

    Directory of Open Access Journals (Sweden)

    Fazal NOORBASHA

    2012-08-01

    Full Text Available In this present study includes the Very Large Scale Integration (VLSI system implementation of 200MHz, 8-bit, 90nm Complementary Metal Oxide Semiconductor (CMOS Arithmetic and Logic Unit (ALU processor control with logic gate design style and 0.12µm six metal 90nm CMOS fabrication technology. The system blocks and the behaviour are defined and the logical design is implemented in gate level in the design phase. Then, the logic circuits are simulated and the subunits are converted in to 90nm CMOS layout. Finally, in order to construct the VLSI system these units are placed in the floor plan and simulated with analog and digital, logic and switch level simulators. The results of the simulations indicates that the VLSI system can control different instructions which can divided into sub groups: transfer instructions, arithmetic and logic instructions, rotate and shift instructions, branch instructions, input/output instructions, control instructions. The data bus of the system is 16-bit. It runs at 200MHz, and operating power is 1.2V. In this paper, the parametric analysis of the system, the design steps and obtained results are explained.

  13. Electrical bistabilities and memory mechanisms of nonvolatile organic bistable devices based on exfoliated muscovite-type mica nanoparticle/poly(methylmethacrylate) nanocomposites

    Science.gov (United States)

    Lim, Won Gyu; Lee, Dea Uk; Na, Han Gil; Kim, Hyoun Woo; Kim, Tae Whan

    2018-02-01

    Organic bistable devices (OBDs) with exfoliated mica nanoparticles (NPs) embedded into an insulating poly(methylmethacrylate) (PMMA) layer were fabricated by using a spin-coating method. Current-voltage (I-V) curves for the Al/PMMA/exfoliated mica NP/PMMA/indium-tin-oxide/glass devices at 300 K showed a clockwise current hysteresis behavior due to the existence of the exfoliated muscovite-type mica NPs, which is an essential feature for bistable devices. Write-read-erase-read data showed that the OBDs had rewritable nonvolatile memories and an endurance number of ON/OFF switching for the OBDs of 102 cycles. An ON/OFF ratio of 1 × 103 was maintained for retention times larger than 1 × 104 s. The memory mechanisms of the fabricated OBDs were described by using the trapping and the tunneling processes within a PMMA active layer containing exfoliated muscovite-type mica NPs on the basis of the energy band diagram and the I-V curves.

  14. Effects of chloride transport on bistable behaviour of the membrane potential in mouse skeletal muscle.

    Science.gov (United States)

    Geukes Foppen, R J; van Mil, H G J; van Heukelom, J Siegenbeek

    2002-07-01

    The lumbrical skeletal muscle fibres of mice exhibited electrically bistable behaviour due to the nonlinear properties of the inwardly rectifying potassium conductance. When the membrane potential (V(m)) was measured continuously using intracellular microelectrodes, either a depolarization or a hyperpolarization was observed following reduction of the extracellular potassium concentration (K+o) from 5.7 mM to values in the range 0.76-3.8 mM, and V(m) showed hysteresis when K+o was slowly decreased and then increased within this range. Hypertonicity caused membrane depolarization by enhancing chloride import through the Na+-K+-2Cl- cotransporter and altered the bistable behaviour of the muscle fibres. Addition of bumetanide, a potent inhibitor of the Na+-K+-2Cl- cotransporter, and of anthracene-9-carboxylic acid, a blocker of chloride channels, caused membrane hyperpolarization particularly under hypertonic conditions, and also altered the bistable behaviour of the cells. Hysteresis loops shifted with hypertonicity to higher K+o values and with bumetanide to lower values. The addition of 80 microM BaCl2 or temperature reduction from 35 to 27 degrees C induced a depolarization of cells that were originally hyperpolarized. In the K+o range of 5.7-22.8 mM, cells in isotonic media (289 mmol x kg(-1)) responded nearly Nernstianly to K+o reduction, i.e. 50 mV per decade; in hypertonic media this dependence was reduced to 36 mV per decade (319 mmol x kg(-1)) or to 31 mV per decade (340 mmol x kg(-1)). Our data can explain apparent discrepancies in DeltaV(m) found in the literature. We conclude that chloride import through the Na+-K+-2Cl- cotransporter and export through Cl- channels influenced the V(m) and the bistable behaviour of mammalian skeletal muscle cells. The possible implication of this bistable behaviour in hypokalaemic periodic paralysis is discussed.

  15. Real-Time Biologically Inspired Action Recognition from Key Poses Using a Neuromorphic Architecture.

    Science.gov (United States)

    Layher, Georg; Brosch, Tobias; Neumann, Heiko

    2017-01-01

    Intelligent agents, such as robots, have to serve a multitude of autonomous functions. Examples are, e.g., collision avoidance, navigation and route planning, active sensing of its environment, or the interaction and non-verbal communication with people in the extended reach space. Here, we focus on the recognition of the action of a human agent based on a biologically inspired visual architecture of analyzing articulated movements. The proposed processing architecture builds upon coarsely segregated streams of sensory processing along different pathways which separately process form and motion information (Layher et al., 2014). Action recognition is performed in an event-based scheme by identifying representations of characteristic pose configurations (key poses) in an image sequence. In line with perceptual studies, key poses are selected unsupervised utilizing a feature-driven criterion which combines extrema in the motion energy with the horizontal and the vertical extendedness of a body shape. Per class representations of key pose frames are learned using a deep convolutional neural network consisting of 15 convolutional layers. The network is trained using the energy-efficient deep neuromorphic networks ( Eedn ) framework (Esser et al., 2016), which realizes the mapping of the trained synaptic weights onto the IBM Neurosynaptic System platform (Merolla et al., 2014). After the mapping, the trained network achieves real-time capabilities for processing input streams and classify input images at about 1,000 frames per second while the computational stages only consume about 70 mW of energy (without spike transduction). Particularly regarding mobile robotic systems, a low energy profile might be crucial in a variety of application scenarios. Cross-validation results are reported for two different datasets and compared to state-of-the-art action recognition approaches. The results demonstrate, that (I) the presented approach is on par with other key pose based

  16. Real-Time Biologically Inspired Action Recognition from Key Poses Using a Neuromorphic Architecture

    Science.gov (United States)

    Layher, Georg; Brosch, Tobias; Neumann, Heiko

    2017-01-01

    Intelligent agents, such as robots, have to serve a multitude of autonomous functions. Examples are, e.g., collision avoidance, navigation and route planning, active sensing of its environment, or the interaction and non-verbal communication with people in the extended reach space. Here, we focus on the recognition of the action of a human agent based on a biologically inspired visual architecture of analyzing articulated movements. The proposed processing architecture builds upon coarsely segregated streams of sensory processing along different pathways which separately process form and motion information (Layher et al., 2014). Action recognition is performed in an event-based scheme by identifying representations of characteristic pose configurations (key poses) in an image sequence. In line with perceptual studies, key poses are selected unsupervised utilizing a feature-driven criterion which combines extrema in the motion energy with the horizontal and the vertical extendedness of a body shape. Per class representations of key pose frames are learned using a deep convolutional neural network consisting of 15 convolutional layers. The network is trained using the energy-efficient deep neuromorphic networks (Eedn) framework (Esser et al., 2016), which realizes the mapping of the trained synaptic weights onto the IBM Neurosynaptic System platform (Merolla et al., 2014). After the mapping, the trained network achieves real-time capabilities for processing input streams and classify input images at about 1,000 frames per second while the computational stages only consume about 70 mW of energy (without spike transduction). Particularly regarding mobile robotic systems, a low energy profile might be crucial in a variety of application scenarios. Cross-validation results are reported for two different datasets and compared to state-of-the-art action recognition approaches. The results demonstrate, that (I) the presented approach is on par with other key pose based

  17. A Low Cost VLSI Architecture for Spike Sorting Based on Feature Extraction with Peak Search.

    Science.gov (United States)

    Chang, Yuan-Jyun; Hwang, Wen-Jyi; Chen, Chih-Chang

    2016-12-07

    The goal of this paper is to present a novel VLSI architecture for spike sorting with high classification accuracy, low area costs and low power consumption. A novel feature extraction algorithm with low computational complexities is proposed for the design of the architecture. In the feature extraction algorithm, a spike is separated into two portions based on its peak value. The area of each portion is then used as a feature. The algorithm is simple to implement and less susceptible to noise interference. Based on the algorithm, a novel architecture capable of identifying peak values and computing spike areas concurrently is proposed. To further accelerate the computation, a spike can be divided into a number of segments for the local feature computation. The local features are subsequently merged with the global ones by a simple hardware circuit. The architecture can also be easily operated in conjunction with the circuits for commonly-used spike detection algorithms, such as the Non-linear Energy Operator (NEO). The architecture has been implemented by an Application-Specific Integrated Circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture is well suited for real-time multi-channel spike detection and feature extraction requiring low hardware area costs, low power consumption and high classification accuracy.

  18. VLSI realization of learning vector quantization with hardware/software co-design for different applications

    Science.gov (United States)

    An, Fengwei; Akazawa, Toshinobu; Yamasaki, Shogo; Chen, Lei; Jürgen Mattausch, Hans

    2015-04-01

    This paper reports a VLSI realization of learning vector quantization (LVQ) with high flexibility for different applications. It is based on a hardware/software (HW/SW) co-design concept for on-chip learning and recognition and designed as a SoC in 180 nm CMOS. The time consuming nearest Euclidean distance search in the LVQ algorithm’s competition layer is efficiently implemented as a pipeline with parallel p-word input. Since neuron number in the competition layer, weight values, input and output number are scalable, the requirements of many different applications can be satisfied without hardware changes. Classification of a d-dimensional input vector is completed in n × \\lceil d/p \\rceil + R clock cycles, where R is the pipeline depth, and n is the number of reference feature vectors (FVs). Adjustment of stored reference FVs during learning is done by the embedded 32-bit RISC CPU, because this operation is not time critical. The high flexibility is verified by the application of human detection with different numbers for the dimensionality of the FVs.

  19. A Low Cost VLSI Architecture for Spike Sorting Based on Feature Extraction with Peak Search

    Directory of Open Access Journals (Sweden)

    Yuan-Jyun Chang

    2016-12-01

    Full Text Available The goal of this paper is to present a novel VLSI architecture for spike sorting with high classification accuracy, low area costs and low power consumption. A novel feature extraction algorithm with low computational complexities is proposed for the design of the architecture. In the feature extraction algorithm, a spike is separated into two portions based on its peak value. The area of each portion is then used as a feature. The algorithm is simple to implement and less susceptible to noise interference. Based on the algorithm, a novel architecture capable of identifying peak values and computing spike areas concurrently is proposed. To further accelerate the computation, a spike can be divided into a number of segments for the local feature computation. The local features are subsequently merged with the global ones by a simple hardware circuit. The architecture can also be easily operated in conjunction with the circuits for commonly-used spike detection algorithms, such as the Non-linear Energy Operator (NEO. The architecture has been implemented by an Application-Specific Integrated Circuit (ASIC with 90-nm technology. Comparisons to the existing works show that the proposed architecture is well suited for real-time multi-channel spike detection and feature extraction requiring low hardware area costs, low power consumption and high classification accuracy.

  20. A novel VLSI processor for high-rate, high resolution spectroscopy

    CERN Document Server

    Pullia, Antonio; Gatti, E; Longoni, A; Buttler, W

    2000-01-01

    A novel time-variant VLSI shaper amplifier, suitable for multi-anode Silicon Drift Detectors or other multi-element solid-state X-ray detection systems, is proposed. The new read-out scheme has been conceived for demanding applications with synchrotron light sources, such as X-ray holography or EXAFS, where both high count-rates and high-energy resolutions are required. The circuit is of the linear time-variant class, accepts randomly distributed events and features: a finite-width (1-10 mu s) quasi-optimal weight function, an ultra-low-level energy discrimination (approx 150 eV), and a full compatibility for monolithic integration in CMOS technology. Its impulse response has a staircase-like shape, but the weight function (which is in general different from the impulse response in time-variant systems) is quasi trapezoidal. The operation principles of the new scheme as well as the first experimental results obtained with a prototype of the circuit are presented and discussed in the work.

  1. VLSI ARCHITECTURE FOR IMAGE COMPRESSION THROUGH ADDER MINIMIZATION TECHNIQUE AT DCT STRUCTURE

    Directory of Open Access Journals (Sweden)

    N.R. Divya

    2014-08-01

    Full Text Available Data compression plays a vital role in multimedia devices to present the information in a succinct frame. Initially, the DCT structure is used for Image compression, which has lesser complexity and area efficient. Similarly, 2D DCT also has provided reasonable data compression, but implementation concern, it calls more multipliers and adders thus its lead to acquire more area and high power consumption. To contain an account of all, this paper has been dealt with VLSI architecture for image compression using Rom free DA based DCT (Discrete Cosine Transform structure. This technique provides high-throughput and most suitable for real-time implementation. In order to achieve this image matrix is subdivided into odd and even terms then the multiplication functions are removed by shift and add approach. Kogge_Stone_Adder techniques are proposed for obtaining a bit-wise image quality which determines the new trade-off levels as compared to the previous techniques. Overall the proposed architecture produces reduced memory, low power consumption and high throughput. MATLAB is used as a funding tool for receiving an input pixel and obtaining output image. Verilog HDL is used for implementing the design, Model Sim for simulation, Quatres II is used to synthesize and obtain details about power and area.

  2. Digital VLSI design with Verilog a textbook from Silicon Valley Polytechnic Institute

    CERN Document Server

    Williams, John Michael

    2014-01-01

    This book is structured as a step-by-step course of study along the lines of a VLSI integrated circuit design project.  The entire Verilog language is presented, from the basics to everything necessary for synthesis of an entire 70,000 transistor, full-duplex serializer-deserializer, including synthesizable PLLs.  The author includes everything an engineer needs for in-depth understanding of the Verilog language:  Syntax, synthesis semantics, simulation, and test. Complete solutions for the 27 labs are provided in the downloadable files that accompany the book.  For readers with access to appropriate electronic design tools, all solutions can be developed, simulated, and synthesized as described in the book.   A partial list of design topics includes design partitioning, hierarchy decomposition, safe coding styles, back annotation, wrapper modules, concurrency, race conditions, assertion-based verification, clock synchronization, and design for test.   A concluding presentation of special topics inclu...

  3. VLSI IMPLEMENTATION OF NOVEL ROUND KEYS GENERATION SCHEME FOR CRYPTOGRAPHY APPLICATIONS BY ERROR CONTROL ALGORITHM

    Directory of Open Access Journals (Sweden)

    B. SENTHILKUMAR

    2015-05-01

    Full Text Available A novel implementation of code based cryptography (Cryptocoding technique for multi-layer key distribution scheme is presented. VLSI chip is designed for storing information on generation of round keys. New algorithm is developed for reduced key size with optimal performance. Error Control Algorithm is employed for both generation of round keys and diffusion of non-linearity among them. Two new functions for bit inversion and its reversal are developed for cryptocoding. Probability of retrieving original key from any other round keys is reduced by diffusing nonlinear selective bit inversions on round keys. Randomized selective bit inversions are done on equal length of key bits by Round Constant Feedback Shift Register within the error correction limits of chosen code. Complexity of retrieving the original key from any other round keys is increased by optimal hardware usage. Proposed design is simulated and synthesized using VHDL coding for Spartan3E FPGA and results are shown. Comparative analysis is done between 128 bit Advanced Encryption Standard round keys and proposed round keys for showing security strength of proposed algorithm. This paper concludes that chip based multi-layer key distribution of proposed algorithm is an enhanced solution to the existing threats on cryptography algorithms.

  4. A Single Chip VLSI Implementation of a QPSK/SQPSK Demodulator for a VSAT Receiver Station

    Science.gov (United States)

    Kwatra, S. C.; King, Brent

    1995-01-01

    This thesis presents a VLSI implementation of a QPSK/SQPSK demodulator. It is designed to be employed in a VSAT earth station that utilizes the FDMA/TDM link. A single chip architecture is used to enable this chip to be easily employed in the VSAT system. This demodulator contains lowpass filters, integrate and dump units, unique word detectors, a timing recovery unit, a phase recovery unit and a down conversion unit. The design stages start with a functional representation of the system by using the C programming language. Then it progresses into a register based representation using the VHDL language. The layout components are designed based on these VHDL models and simulated. Component generators are developed for the adder, multiplier, read-only memory and serial access memory in order to shorten the design time. These sub-components are then block routed to form the main components of the system. The main components are block routed to form the final demodulator.

  5. Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    I. Hameem Shanavas

    2014-01-01

    Full Text Available In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.

  6. Prototype architecture for a VLSI level zero processing system. [Space Station Freedom

    Science.gov (United States)

    Shi, Jianfei; Grebowsky, Gerald J.; Horner, Ward P.; Chesney, James R.

    1989-01-01

    The prototype architecture and implementation of a high-speed level zero processing (LZP) system are discussed. Due to the new processing algorithm and VLSI technology, the prototype LZP system features compact size, low cost, high processing throughput, and easy maintainability and increased reliability. Though extensive control functions have been done by hardware, the programmability of processing tasks makes it possible to adapt the system to different data formats and processing requirements. It is noted that the LZP system can handle up to 8 virtual channels and 24 sources with combined data volume of 15 Gbytes per orbit. For greater demands, multiple LZP systems can be configured in parallel, each called a processing channel and assigned a subset of virtual channels. The telemetry data stream will be steered into different processing channels in accordance with their virtual channel IDs. This super system can cope with a virtually unlimited number of virtual channels and sources. In the near future, it is expected that new disk farms with data rate exceeding 150 Mbps will be available from commercial vendors due to the advance in disk drive technology.

  7. VLSI design of an RSA encryption/decryption chip using systolic array based architecture

    Science.gov (United States)

    Sun, Chi-Chia; Lin, Bor-Shing; Jan, Gene Eu; Lin, Jheng-Yi

    2016-09-01

    This article presents the VLSI design of a configurable RSA public key cryptosystem supporting the 512-bit, 1024-bit and 2048-bit based on Montgomery algorithm achieving comparable clock cycles of current relevant works but with smaller die size. We use binary method for the modular exponentiation and adopt Montgomery algorithm for the modular multiplication to simplify computational complexity, which, together with the systolic array concept for electric circuit designs effectively, lower the die size. The main architecture of the chip consists of four functional blocks, namely input/output modules, registers module, arithmetic module and control module. We applied the concept of systolic array to design the RSA encryption/decryption chip by using VHDL hardware language and verified using the TSMC/CIC 0.35 m 1P4 M technology. The die area of the 2048-bit RSA chip without the DFT is 3.9 × 3.9 mm2 (4.58 × 4.58 mm2 with DFT). Its average baud rate can reach 10.84 kbps under a 100 MHz clock.

  8. A configurable realtime DWT-based neural data compression and communication VLSI system for wireless implants.

    Science.gov (United States)

    Yang, Yuning; Kamboh, Awais M; Mason, Andrew J

    2014-04-30

    This paper presents the design of a complete multi-channel neural recording compression and communication system for wireless implants that addresses the challenging simultaneous requirements for low power, high bandwidth and error-free communication. The compression engine implements discrete wavelet transform (DWT) and run length encoding schemes and offers a practical data compression solution that faithfully preserves neural information. The communication engine encodes data and commands separately into custom-designed packet structures utilizing a protocol capable of error handling. VLSI hardware implementation of these functions, within the design constraints of a 32-channel neural compression implant, is presented. Designed in 0.13μm CMOS, the core of the neural compression and communication chip occupies only 1.21mm(2) and consumes 800μW of power (25μW per channel at 26KS/s) demonstrating an effective solution for intra-cortical neural interfaces. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Design of 10Gbps optical encoder/decoder structure for FE-OCDMA system using SOA and opto-VLSI processors.

    Science.gov (United States)

    Aljada, Muhsen; Hwang, Seow; Alameh, Kamal

    2008-01-21

    In this paper we propose and experimentally demonstrate a reconfigurable 10Gbps frequency-encoded (1D) encoder/decoder structure for optical code division multiple access (OCDMA). The encoder is constructed using a single semiconductor optical amplifier (SOA) and 1D reflective Opto-VLSI processor. The SOA generates broadband amplified spontaneous emission that is dynamically sliced using digital phase holograms loaded onto the Opto-VLSI processor to generate 1D codewords. The selected wavelengths are injected back into the same SOA for amplifications. The decoder is constructed using single Opto-VLSI processor only. The encoded signal can successfully be retrieved at the decoder side only when the digital phase holograms of the encoder and the decoder are matched. The system performance is measured in terms of the auto-correlation and cross-correlation functions as well as the eye diagram.

  10. Room temperature operation of electro-optical bistability in the edge-emitting tunneling-collector transistor laser

    Science.gov (United States)

    Feng, M.; Holonyak, N.; Wang, C. Y.

    2017-09-01

    Optical bistable devices are fundamental to digital photonics as building blocks of switches, logic gates, and memories in future computer systems. Here, we demonstrate both optical and electrical bistability and capability for switching in a single transistor operated at room temperature. The electro-optical hysteresis is explained by the interaction of electron-hole (e-h) generation and recombination dynamics with the cavity photon modulation in different switching paths. The switch-UP and switch-DOWN threshold voltages are determined by the rate difference of photon generation at the base quantum-well and the photon absorption via intra-cavity photon-assisted tunneling controlled by the collector voltage. Thus, the transistor laser electro-optical bistable switching is programmable with base current and collector voltage, and the basis for high speed optical logic processors.

  11. Carrier transport mechanisms of organic bistable devices fabricated utilizing colloidal ZnO quantum dot-polymethylmethacrylate polymer nanocomposites

    Science.gov (United States)

    Son, Dong Ick; You, Chan Ho; Jung, Jae Hun; Kim, Tae Whan

    2010-07-01

    Organic bistable devices (OBDs) fabricated utilizing ZnO quantum dots (QDs) embedded in a poly(methyl methacrylate) (PMMA) layer were fabricated by using a spin-coating technique. Transmission electron microscopy images revealed that 5-nm-diameter ZnO QDs were formed inside the PMMA polymer layer. Current-voltage (I-V) measurements on Al/ZnO QDs embedded in PMMA layer/indium-tin-oxide devices at 300 K showed electrical bistability. The maximum ON/OFF ratio of the current bistability for the OBDs was as large as 4×104. Carrier transport mechanisms for the OBDs are described by using several models to fit the experimental I-V data.

  12. Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications.

    Science.gov (United States)

    Kasabov, Nikola; Scott, Nathan Matthew; Tu, Enmei; Marks, Stefan; Sengupta, Neelava; Capecci, Elisa; Othman, Muhaini; Doborjeh, Maryam Gholami; Murli, Norhanifah; Hartono, Reggio; Espinosa-Ramos, Josafath Israel; Zhou, Lei; Alvi, Fahad Bashir; Wang, Grace; Taylor, Denise; Feigin, Valery; Gulyaev, Sergei; Mahmoud, Mahmoud; Hou, Zeng-Guang; Yang, Jie

    2016-06-01

    The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to deal with large and fast spatio/spectro temporal data using spiking neural networks (SNN) as major processing modules. ECOS and eSTDM in particular can learn incrementally from data streams, can include 'on the fly' new input variables, new output class labels or regression outputs, can continuously adapt their structure and functionality, can be visualised and interpreted for new knowledge discovery and for a better understanding of the data and the processes that generated it. eSTDM can be used for early event prediction due to the ability of the SNN to spike early, before whole input vectors (they were trained on) are presented. A framework for building eSTDM called NeuCube along with a design methodology for building eSTDM using this is presented. The implementation of this framework in MATLAB, Java, and PyNN (Python) is presented. The latter facilitates the use of neuromorphic hardware platforms to run the eSTDM. Selected examples are given of eSTDM for pattern recognition and early event prediction on EEG data, fMRI data, multisensory seismic data, ecological data, climate data, audio-visual data. Future directions are discussed, including extension of the NeuCube framework for building neurogenetic eSTDM and also new applications of eSTDM. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Sound stream segregation: a neuromorphic approach to solve the “cocktail party problem” in real-time

    Science.gov (United States)

    Thakur, Chetan Singh; Wang, Runchun M.; Afshar, Saeed; Hamilton, Tara J.; Tapson, Jonathan C.; Shamma, Shihab A.; van Schaik, André

    2015-01-01

    The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the “cocktail party effect.” It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA). This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR) of the segregated stream (90, 77, and 55 dB for simple tone, complex tone, and speech, respectively) as compared to the SNR of the mixture waveform (0 dB). This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for sound segregation

  14. Sound stream segregation: a neuromorphic approach to solve the ‘cocktail party problem’ in real-time

    Directory of Open Access Journals (Sweden)

    Chetan Singh Thakur

    2015-09-01

    Full Text Available The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the ‘cocktail party effect’. It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA. This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR of the segregated stream (90, 77 and 55 dB for simple tone, complex tone and speech, respectively as compared to the SNR of the mixture waveform (0 dB. This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for

  15. Activation of Transducin by Bistable Pigment Parapinopsin in the Pineal Organ of Lower Vertebrates.

    Directory of Open Access Journals (Sweden)

    Emi Kawano-Yamashita

    Full Text Available Pineal organs of lower vertebrates contain several kinds of photosensitive molecules, opsins that are suggested to be involved in different light-regulated physiological functions. We previously reported that parapinopsin is an ultraviolet (UV-sensitive opsin that underlies hyperpolarization of the pineal photoreceptor cells of lower vertebrates to achieve pineal wavelength discrimination. Although, parapinopsin is phylogenetically close to vertebrate visual opsins, it exhibits a property similar to invertebrate visual opsins and melanopsin: the photoproduct of parapinopsin is stable and reverts to the original dark states, demonstrating the nature of bistable pigments. Therefore, it is of evolutionary interest to identify a phototransduction cascade driven by parapinopsin and to compare it with that in vertebrate visual cells. Here, we showed that parapinopsin is coupled to vertebrate visual G protein transducin in the pufferfish, zebrafish, and lamprey pineal organs. Biochemical analyses demonstrated that parapinopsins activated transducin in vitro in a light-dependent manner, similar to vertebrate visual opsins. Interestingly, transducin activation by parapinopsin was provoked and terminated by UV- and subsequent orange-lights irradiations, respectively, due to the bistable nature of parapinopsin, which could contribute to a wavelength-dependent control of a second messenger level in the cell as a unique optogenetic tool. Immunohistochemical examination revealed that parapinopsin was colocalized with Gt2 in the teleost, which possesses rod and cone types of transducin, Gt1, and Gt2. On the other hand, in the lamprey, which does not possess the Gt2 gene, in situ hybridization suggested that parapinopsin-expressing photoreceptor cells contained Gt1 type transducin GtS, indicating that lamprey parapinopsin may use GtS in place of Gt2. Because it is widely accepted that vertebrate visual opsins having a bleaching nature have evolved from non

  16. Switching between bistable states in a discrete nonlinear model with long-range dispersion

    DEFF Research Database (Denmark)

    Johansson, Magnus; Gaididei, Yuri B.; Christiansen, Peter Leth

    1998-01-01

    In the framework of a discrete nonlinear Schrodinger equation with long-range dispersion, we propose a general mechanism for obtaining a controlled switching between bistable localized excitations. We show that the application of a spatially symmetric kick leads to the excitation of an internal...... breathing mode and that switching between narrow, pinned states and broad, mobile states with only small radiative losses occurs when the kick strength exceeds a threshold value. This mechanism could be important for controlling energy storage and transport in molecular systems....

  17. Bistable Dithienylethene-Based Metal-Organic Framework Illustrating Optically Induced Changes in Chemical Separations.

    Science.gov (United States)

    Furlong, Brandon J; Katz, Michael J

    2017-09-27

    Dithienylethene-containing molecules have been examined due to their photoswitching capabilities. We have prepared a bistable, optically triggered, metal-organic framework (MOF) containing a dithienylethene moiety that was synthesized and characterized. The advantage of this material is that, unlike other dithienylethene-containing MOFs, the properties of the pore can be changed via an optical trigger without the potential risk of structural damage to the framework. We illustrate the application of this MOF to chemical separations. With this class of materials, optically triggered conductivity, chemical storage and release, and sensing are possible.

  18. Near field thermal memory based on radiative phase bistability of VO2

    Science.gov (United States)

    Dyakov, S. A.; Dai, J.; Yan, M.; Qiu, M.

    2015-08-01

    We report the concept of a near-field memory device based on the radiative bistability effect in the system of two closely separated parallel plates of SiO2 and VO2 which exchange heat by thermal radiation in vacuum. We demonstrate that the VO2 plate, having metal-insulator transition at 340 K, has two thermodynamical steady-states. One can switch between the states using an external laser impulse. We show that due to near-field photon tunneling between the plates, the switching time is found to be only 5 ms which is several orders lower than in case of far field.

  19. Bistable switching in supercritical n+-n-n+GaAs transferred electron devices

    DEFF Research Database (Denmark)

    Jøndrup, Peter; Jeppesen, Palle; Jeppson, Bert

    1976-01-01

    Bistable switching in supercritically doped n+-n-n+GaAs transferred electron devices (TED's) is investigated experimentally and interpreted in computer simulations, for which details of the computer program are given. Three switching modes all leading to stable anode domains are discussed, namely......: 1) cathode-triggered traveling domain; 2) cathode-triggered accumulation layer; 3) anode-triggered domain. Relative current drops up to 40 percent, and switching times down to 60 ps are obtained in low-duty-cycle pulsed experiments with threshold currents around 400 mA. Optimum device parameters...

  20. On the Hα behaviour of blue supergiants: rise and fall over the bi-stability jump

    Science.gov (United States)

    Petrov, Blagovest; Vink, Jorick S.; Gräfener, Götz

    2014-05-01

    Context. The evolutionary state of blue supergiants is still unknown. Stellar wind mass loss is one of the dominant processes determining the evolution of massive stars, and it may provide clues to the evolutionary properties of blue supergiants. As the Hα line is the most oft-used mass-loss tracer in the OB-star regime, we investigate Hα line formation as a function of Teff. Aims: We provide a detailed analysis of the Hα line for OB supergiant models over an Teff range between 30 000 and 12 500 K, with the aim of understanding the mass-loss properties of blue supergiants. Methods: We model the Hα line using the non-LTE code cmfgen, in the context of the bi-stability jump at Teff ~ 22 500 K. Results: We find a maximum in the Hα equivalent width at 22 500 K exactly at the location of the bi-stability jump. The Hα line-profile behaviour is characterised by two branches of effective temperature: (i) a hot branch between 30 000 and 22 500 K, where Hα emission becomes stronger with decreasing Teff; and (ii) a cool branch between 22 500 and 12 500 K, where the Hα line becomes weaker. Our models show that this non-monotonic Hα behaviour is related to the optical depth of Lyα, finding that at the "cool" branch the population of the 2nd level of hydrogen is enhanced in comparison to the 3rd level. This is expected to increase line absorption, leading to weaker Hα flux when Teff drops from 22 500 K downwards. We also show that for late B supergiants (at Teff below ~15 000 K), the differences in the Hα line between homogeneous and clumpy winds becomes insignificant. Moreover, we show that, at the bi-stability jump, Hα changes its character completely, from an optically thin to an optically thick line, implying that macro-clumping should play an important role at temperatures below the bi-stability jump. This would not only have consequences for the character of observed Hα line profiles, but also for the reported discrepancies between theoretical and empirical

  1. Predicting the effects of dimensional and material stiffness variations on a compliant bistable microrelay performance

    Energy Technology Data Exchange (ETDEWEB)

    Ghanbari, Ali; Bahrami, Mohsen [Mechanical Engineering Department, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

    2006-04-01

    In this paper we investigate the effects of dimensional and material stiffness variations on a microrelay performance. A linear displacement bistable micromechanism is modelled by pseudo-rigid-body model method and fully characterized. To find the effects of dimensional and material stiffness variation, an analysis of mechanical error is used. The method is a stochastic one and takes into account the random nature of variations. Variations of the contact force and required power of a microrelay example is obtained by the method introduced and the performance of the microrelay is determined. The method introduced is a simple, effective and general that may be used at the design level.

  2. Origami-based cellular metamaterial with auxetic, bistable, and self-locking properties.

    Science.gov (United States)

    Kamrava, Soroush; Mousanezhad, Davood; Ebrahimi, Hamid; Ghosh, Ranajay; Vaziri, Ashkan

    2017-04-07

    We present a novel cellular metamaterial constructed from Origami building blocks based on Miura-ori fold. The proposed cellular metamaterial exhibits unusual properties some of which stemming from the inherent properties of its Origami building blocks, and others manifesting due to its unique geometrical construction and architecture. These properties include foldability with two fully-folded configurations, auxeticity (i.e., negative Poisson's ratio), bistability, and self-locking of Origami building blocks to construct load-bearing cellular metamaterials. The kinematics and force response of the cellular metamaterial during folding were studied to investigate the underlying mechanisms resulting in its unique properties using analytical modeling and experiments.

  3. The existence of traveling wave solutions for a bistable three-component lattice dynamical system

    Science.gov (United States)

    Guo, Jong-Shenq; Wu, Chin-Chin

    2016-01-01

    We study the traveling wave solutions for a three-component lattice dynamical system. This problem arises in the modeling of three species competing two food resources in an environment with migration in which the habitat is one-dimensional and is divided into countable niches. We are concerned with the case when two species have different preferences of food and the third species has both preferences of food. To understand which species win the competition under the bistable condition, the existence of a traveling wave solution for this lattice dynamical system is proven.

  4. Bistable electroactive polymer for refreshable Braille display with improved actuation stability

    Science.gov (United States)

    Niu, Xiaofan; Brochu, Paul; Stoyanov, Hristiyan; Yun, Sung Ryul; Pei, Qibing

    2012-04-01

    Poly(t-butyl acrylate) is a bistable electroactive polymer (BSEP) capable of rigid-to-rigid actuation. The BSEP combines the large-strain actuation of dielectric elastomers with shape memory property. We have introduced a material approach to overcome pull-in instability in poly(t-butyl acrylate) that significantly improves the actuation lifetime at strains greater than 100%. Refreshable Braille display devices with size of a smartphone screen have been fabricated to manifest a potential application of the BSEP. We will report the testing results of the devices by a Braille user.

  5. Bistable Magnetism and Potential for Voltage-Induced Spin Crossover in Dilute Magnetic Ferroelectrics.

    Science.gov (United States)

    Weston, L; Cui, X Y; Ringer, S P; Stampfl, C

    2015-06-19

    A first-principles investigation into the magnetic ferroelectric PbTi(1-x)Co(x)O(3) has revealed a bi-stable magnetic system with strong spin-lattice coupling. The local distortions induced by the low-spin to high-spin crossover are ferroelectric in nature, and are characterized by the displacement of the dopant ion with respect to the surrounding O(6) octahedral cage. We demonstrate how this spin-lattice effect could mediate magnetoelectric coupling and possible electric field induced spin-crossover, indicating a promising route to voltage manipulation of isolated spins in a solid-state system.

  6. Origami-based cellular metamaterial with auxetic, bistable, and self-locking properties

    Science.gov (United States)

    Kamrava, Soroush; Mousanezhad, Davood; Ebrahimi, Hamid; Ghosh, Ranajay; Vaziri, Ashkan

    2017-04-01

    We present a novel cellular metamaterial constructed from Origami building blocks based on Miura-ori fold. The proposed cellular metamaterial exhibits unusual properties some of which stemming from the inherent properties of its Origami building blocks, and others manifesting due to its unique geometrical construction and architecture. These properties include foldability with two fully-folded configurations, auxeticity (i.e., negative Poisson’s ratio), bistability, and self-locking of Origami building blocks to construct load-bearing cellular metamaterials. The kinematics and force response of the cellular metamaterial during folding were studied to investigate the underlying mechanisms resulting in its unique properties using analytical modeling and experiments.

  7. Optical bistability in erbium-doped yttrium aluminum garnet crystal combined with a laser diode.

    Science.gov (United States)

    Maeda, Y

    1994-01-10

    Optical bistability was observed in a simple structure of an injection laser diode combined with an erbium-doped yttrium aluminum garnet crystal. Since a hysteresis characteristic exists in the relationship between the wavelength and the injection current of a laser diode, an optical memory function capable of holding the output status is confirmed. In addition, an optical signal inversion was caused by the decrease of transmission of the erbium-doped yttrium aluminum garnet crystal against the red shift (principally mode hopping) of the laser diode. It is suggested that the switching time of this phenomenon is the time necessary for a mode hopping by current injection.

  8. Bistable optical devices with laser diodes coupled to absorbers of narrow spectral bandwidth.

    Science.gov (United States)

    Maeda, Y

    1994-06-20

    An optical signal inverter was demonstrated with a combination of the following two effects: One is the decrease of the transmission of an Er-doped YAG crystal with increasing red shift of a laser diode resulting from an increase in the injection current, and the other is a negative nonlinear absorption in which the transmission decreases inversely with increasing laser intensity. Because a hysteresis characteristic exists in the relationship between the wavelength and the injection current of the laser diode, an optical bistability was observed in this system.

  9. Bistable Intrinsic Charge Fluctuations of a Dust Grain Subject to Secondary Electron Emission in a Plasma

    CERN Document Server

    Shotorban, Babak

    2015-01-01

    A master equation was formulated to study intrinsic charge fluctuations of a grain in a plasma as ions and primary electrons are attached to the grain through collisional collection, and secondary electrons are emitted from the grain. Two different plasmas with Maxwellian and non-Maxwellian distributions were considered. The fluctuations could be bistable in either plasma when the secondary electron emission is present, as two stable macrostates, associated with two stable roots of the charge net current, may exist. Metastablity of fluctuations, manifested by the passage of the grain charge between two macrostates, was shown to be possible.

  10. Controllable optical bistability and multistability in a graphene structure under external magnetic field

    Science.gov (United States)

    Raheli, Ali; Hamedi, H. R.; Sahrai, M.

    2016-02-01

    We investigate the behavior of optical bistability (OB) and optical multistability (OM) based on quantum coherence in a Landau-quantized graphene structure. Such a tunable four-level system is driven coherently by two coherent fields and an incoherent pumping field inside the unidirectional ring cavity. The influence of system parameters on the threshold of the onset of OB and OM is studied. It is found that one can efficiently control the OB/OM threshold intensity and the hysteresis loop by using the system parameters. The results obtained may be used in real experiments for the development of new types of nanoelectronic devices for realizing an all-optical switching process.

  11. Bistability of time-periodic polarization dynamics in a free-running VCSEL.

    Science.gov (United States)

    Virte, M; Sciamanna, M; Mercier, E; Panajotov, K

    2014-03-24

    We report experimentally a bistability between two limit cycles (i.e. time-periodic dynamics) in a free-running vertical-cavity surface-emitting laser. The two limit cycles originate from a bifurcation on two elliptically polarized states which exhibit a small frequency difference and whose main axes are symmetrical with respect to the linear polarization eigenaxes at threshold. We demonstrate theoretically that this peculiar behavior can be explained in the framework of the spin-flip model model by taking into account a small misalignment between the phase and amplitude anisotropies.

  12. A bistable switch and anatomical site control Vibrio cholerae virulence gene expression in the intestine.

    Directory of Open Access Journals (Sweden)

    Alex T Nielsen

    2010-09-01

    Full Text Available A fundamental, but unanswered question in host-pathogen interactions is the timing, localization and population distribution of virulence gene expression during infection. Here, microarray and in situ single cell expression methods were used to study Vibrio cholerae growth and virulence gene expression during infection of the rabbit ligated ileal loop model of cholera. Genes encoding the toxin-coregulated pilus (TCP and cholera toxin (CT were powerfully expressed early in the infectious process in bacteria adjacent to epithelial surfaces. Increased growth was found to co-localize with virulence gene expression. Significant heterogeneity in the expression of tcpA, the repeating subunit of TCP, was observed late in the infectious process. The expression of tcpA, studied in single cells in a homogeneous medium, demonstrated unimodal induction of tcpA after addition of bicarbonate, a chemical inducer of virulence gene expression. Striking bifurcation of the population occurred during entry into stationary phase: one subpopulation continued to express tcpA, whereas the expression declined in the other subpopulation. ctxA, encoding the A subunit of CT, and toxT, encoding the proximal master regulator of virulence gene expression also exhibited the bifurcation phenotype. The bifurcation phenotype was found to be reversible, epigenetic and to persist after removal of bicarbonate, features consistent with bistable switches. The bistable switch requires the positive-feedback circuit controlling ToxT expression and formation of the CRP-cAMP complex during entry into stationary phase. Key features of this bistable switch also were demonstrated in vivo, where striking heterogeneity in tcpA expression was observed in luminal fluid in later stages of the infection. When this fluid was diluted into artificial seawater, bacterial aggregates continued to express tcpA for prolonged periods of time. The bistable control of virulence gene expression points to a

  13. Actively tunable optical Yagi-Uda nanoantenna with bistable emission characteristics

    CERN Document Server

    Maksymov, Ivan S; Kivshar, Yuri S

    2012-01-01

    We suggest and study theoretically a novel type of optical Yagi-Uda nanoantennas tunable via variation of the free-carrier density of a semiconductor disk placed in a gap of a metallic dipole feeding element. Unlike its narrowband all-metal counterparts, this nanoantenna exhibits a broadband unidirectional emission and demonstrates a bistable response in a preferential direction of the far-field zone, which opens up unique possibilities for ultrafast control of subwavelength light not attainable with dipole or bowtie architectures.

  14. Asymmetric bistable reflection and polarization switching in a magnetic nonlinear multilayer structure

    DEFF Research Database (Denmark)

    Tuz, Vladimir R.; Novitsky, Denis V.; Prosvirnin, Sergey L.

    2014-01-01

    Optical properties of one-dimensional photonic structures consisting of Kerr-type nonlinear and magnetic layers under the action of an external static magnetic field in the Faraday geometry are investigated. The structure is a periodic arrangement of alternating nonlinear and magnetic layers (a one......, while light reflected from the other side has its polarization unchanged. Using the nonlinear transfer matrix calculations in the frequency domain, it is demonstrated that defect resonances in the nonlinear reflection spectra undergo bending, resulting in polarization bistability of reflected light...

  15. Finite mixture model applied in the analysis of a turbulent bistable flow on two parallel circular cylinders

    Energy Technology Data Exchange (ETDEWEB)

    De Paula, A.V.; Moeller, S.V., E-mail: vagtinski@mecanica.ufrgs.br, E-mail: svmoller@ufrgs.br [UFRGS - Univ. Federal do Rio Grande do Sul, PROMEC - Programa de Pos Graduacao em Engenharia Mecanica, Porto Alegre, RS (Brazil)

    2011-07-01

    This paper presents a study of the bistable phenomenon which occurs in the turbulent flow impinging on circular cylinders placed side-by-side. Time series of axial and transversal velocity obtained with the constant temperature hot wire anemometry technique in an aerodynamic channel are used as input data in a finite mixture model, to classify the observed data according to a family of probability density functions. Wavelet transforms are applied to analyze the unsteady turbulent signals. Results of flow visualization show a predominantly two-dimensional behavior. A double-well energy model is suggested to describe the behavior of the bistable phenomenon in this case. (author)

  16. Digital VLSI systems design a design manual for implementation of projects on FPGAs and ASICs using Verilog

    CERN Document Server

    Ramachandran, S

    2007-01-01

    Digital VLSI Systems Design is written for an advanced level course using Verilog and is meant for undergraduates, graduates and research scholars of Electrical, Electronics, Embedded Systems, Computer Engineering and interdisciplinary departments such as Bio Medical, Mechanical, Information Technology, Physics, etc. It serves as a reference design manual for practicing engineers and researchers as well. Diligent freelance readers and consultants may also start using this book with ease. The book presents new material and theory as well as synthesis of recent work with complete Project Designs

  17. The human brain on a computer, the design neuromorphic chips aims to process information as does the mind; El cerebro humano en un ordenador

    Energy Technology Data Exchange (ETDEWEB)

    Pajuelo, L.

    2015-07-01

    Develop chips that mimic the brain processes It will help create computers capable of interpreting information from image, sound and touch so that it may offer answers intelligent-not programmed before- according to these sensory data. chips neuromorphic may mimic the electrical activity neurons and brain synapses, and will be key to intelligence systems artificial (ia) that require interaction with the environment being able to extract information cognitive of what surrounds them. (Author)

  18. Driving a car with custom-designed fuzzy inferencing VLSI chips and boards

    Science.gov (United States)

    Pin, Francois G.; Watanabe, Yutaka

    1993-01-01

    Vehicle control in a-priori unknown, unpredictable, and dynamic environments requires many calculational and reasoning schemes to operate on the basis of very imprecise, incomplete, or unreliable data. For such systems, in which all the uncertainties can not be engineered away, approximate reasoning may provide an alternative to the complexity and computational requirements of conventional uncertainty analysis and propagation techniques. Two types of computer boards including custom-designed VLSI chips were developed to add a fuzzy inferencing capability to real-time control systems. All inferencing rules on a chip are processed in parallel, allowing execution of the entire rule base in about 30 microseconds, and therefore, making control of 'reflex-type' of motions envisionable. The use of these boards and the approach using superposition of elemental sensor-based behaviors for the development of qualitative reasoning schemes emulating human-like navigation in a-priori unknown environments are first discussed. Then how the human-like navigation scheme implemented on one of the qualitative inferencing boards was installed on a test-bed platform to investigate two control modes for driving a car in a-priori unknown environments on the basis of sparse and imprecise sensor data is described. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up or slow down depending on the obstacles perceived by the sensors. Experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Simulation results as well as indoors and outdoors experiments are presented and discussed to illustrate the feasibility and robustness of autonomous navigation and/or safety enhancing driver's aid using the new fuzzy inferencing hardware system and some human

  19. Theoretical and applied research on bistable dual-piezoelectric-cantilever vibration energy harvesting toward realistic ambience

    Science.gov (United States)

    Gao, Y.; Leng, Y.; Javey, A.; Tan, D.; Liu, J.; Fan, S.; Lai, Z.

    2016-11-01

    Pink noise, which is similar to realistic ambient noise, is normally used to simulate ambience where a piezoelectric energy harvesting system (PEHS) is set up. However, pink noise with standard spectral representation can only be used to simulate excitations assumed to possess constant intensity, whereas realistic ambient noise normally appears with a random spectrum and varying intensity in terms of different locations and time. The output performance of conventional bistable magnetic repulsive energy harvesters is significantly affected by the ambience intensity. Considering this fact, a model bistable dual-piezoelectric-cantilever energy harvester (DPEH) is developed in this study to achieve optimal broadband energy harvesting under a varying-intensity realistic circumstance. We utilized various realistic ambient conditions as excitations to obtain the DPEH energy harvesting performance for theoretical and applied study. The elastically supported PEHS has been proven to be more adaptive to realistic ambience with significant or medium intensity variation, but is less qualified for realistic ambience with constant intensity compared with the rigidly supported PEHS (RPEHS). Fortunately, the dual-piezoelectric-cantilever energy harvesting system is superior to the RPEHS under all circumstances because the dual-piezoelectric cantilevers are efficiently utilized for electromechanical energy conversion to realize optimal energy harvesting.

  20. Two independent positive feedbacks and bistability in the Bcl-2 apoptotic switch.

    Directory of Open Access Journals (Sweden)

    Jun Cui

    Full Text Available BACKGROUND: The complex interplay between B-cell lymphoma 2 (Bcl-2 family proteins constitutes a crucial checkpoint in apoptosis. Its detailed molecular mechanism remains controversial. Our former modeling studies have selected the 'Direct Activation Model' as a better explanation for experimental observations. In this paper, we continue to extend this model by adding interactions according to updating experimental findings. METHODOLOGY/PRINCIPAL FINDINGS: Through mathematical simulation we found bistability, a kind of switch, can arise from a positive (double negative feedback in the Bcl-2 interaction network established by anti-apoptotic group of Bcl-2 family proteins. Moreover, Bax/Bak auto-activation as an independent positive feedback can enforce the bistability, and make it more robust to parameter variations. By ensemble stochastic modeling, we also elucidated how intrinsic noise can change ultrasensitive switches into gradual responses. Our modeling result agrees well with recent experimental data where bimodal Bax activation distributions in cell population were found. CONCLUSIONS/SIGNIFICANCE: Along with the growing experimental evidences, our studies successfully elucidate the switch mechanism embedded in the Bcl-2 interaction network and provide insights into pharmacological manipulation of Bcl-2 apoptotic switch as further cancer therapies.

  1. Feedback Control of Bistability in the Turbulent Wake of an Ahmed Body

    Science.gov (United States)

    Brackston, Rowan; Wynn, Andrew; Garcia de La Cruz, Juan Marcos; Rigas, Georgios; Morrison, Jonathan

    2015-11-01

    Three-dimensional bluff body wakes have seen considerable interest in recent years, not least because of their relevance to road vehicles. A key feature of these wakes is spatial symmetry breaking, reminiscent of the large scale structures observed during the laminar and transitional regimes. For the flat backed Ahmed body, this feature manifests itself as a bistability of the wake in which the flow switches randomly between two asymmetric states. This feature is associated with instantaneous lateral forces on the body as well as increased pressure drag. Starting from the modelling approach of Rigas et al. (J. Fluid Mech. 778, R2, 2015)we identify a linearised model for this mode of the flow, obtaining parameters via a system identification. The identified model is then used to design a linear feedback controller with the aim of restoring the flow to the unstable, symmetric state. The controller is implemented experimentally at Re ~ 3 ×105 and is found to both suppress the bistability of the flow and reduce the drag on the body. Furthermore, the control system is found to have a positive energy balance, providing a key demonstration of efficient feedback control applied to a 3D bluff body at Reynolds numbers representative of road vehicle wakes.

  2. Bistability in Fc-PTM crystals: the role of intermolecular electrostatic interactions.

    Science.gov (United States)

    D'Avino, Gabriele; Grisanti, Luca; Guasch, Judith; Ratera, Imma; Veciana, Jaume; Painelli, Anna

    2008-09-10

    Fc-PTM is a valence tautomeric radical, where the ferrocene (Fc) group, a good electron donor, is linked by an ethylenic spacer to a perchlorotriphenylmethyl radical (PTM(*)), a good electron acceptor. In solution this compound exists mainly in the neutral Fc-PTM(*) form which can be photoexcited through an intramolecular electron transfer to the zwitterionic Fc(+*)-PTM(-) form. By contrast, in crystals of Fc-PTM at room temperature both the neutral and the zwitterionic forms coexist, pointing to a true bistability phenomenon. We rationalize these findings accounting for the role of intermolecular electrostatic interactions in Fc-PTM crystals. In fact the energy of the zwitterionic Fc(+*)-PTM(-) form is lowered in the crystal by attractive electrostatic intermolecular interactions and the cooperative nature of these interactions explains the observed coexistence of neutral Fc-PTM(*) and zwitterionic Fc(+*)-PTM(-) species. The temperature evolution of Mossbauer spectra of Fc-PTM is quantitatively reproduced adopting a bottom-up modeling strategy that combines a molecular model, derived from optical spectra of Fc-PTM in solution, with a model for intermolecular electrostatic interactions, supported by quantum-chemical calculations. Fc-PTM then offers the first experimental demonstration of bistability induced by electrostatic interactions in crystals of valence tautomeric donor-acceptor molecules.

  3. Polymer-ultrathin graphite sheet-polymer composite structured flexible nonvolatile bistable organic memory devices.

    Science.gov (United States)

    Son, Dong Ick; Shim, Jae Ho; Park, Dong Hee; Jung, Jae Hun; Lee, Jung Min; Park, Won Il; Kim, Tae Whan; Choi, Won Kook

    2011-07-22

    We present data, which were obtained before bending and after bending, for the electrical bistabilities, memory stabilities, and memory mechanisms of three-layer structured flexible bistable organic memory (BOM) devices, which were fabricated utilizing the ultrathin graphite sheets (UGS) sandwiched between insulating poly(methylmethacrylate) (PMMA) polymer layers. The UGS were formed by transferring UGS (about 30 layers) and using a simple spin-coating technique. Transmission electron microscopy (TEM) measurements were performed to investigate the microstructural properties of the PMMA/UGS/PMMA films. Current-voltage (I-V) measurements were carried out to investigate the electrical properties of the BOM devices containing the UGS embedded in the PMMA polymer. Current-time (I-t) and current-cycle measurements under flat and bent conditions were performed to investigate the memory stabilities of the BOM devices. The memory characteristics of the BOM maintained similar device efficiencies after bending and were stable during repeated bendings of the BOM devices. The mechanisms for these characteristics of the fabricated BOM are described on the basis of the I-V results.

  4. Performance Study of a Fluidic Hammer Controlled by an Output-Fed Bistable Fluidic Oscillator

    Directory of Open Access Journals (Sweden)

    Xinxin Zhang

    2016-10-01

    Full Text Available Using a no-moving-component output-fed bistable fluidic oscillator to control fluid flows into a parallel path has been recognized for a considerable time, but as yet it is not so widely adopted as its obvious benefits would deserve. This may be attributed to the encountered problems associated with its jet behavior, complicated by its loading characteristics. In order to investigate a typical case for the application of the output-fed fluidic oscillator, this paper elaborates on the computational fluid dynamics (CFD simulation method for studying the performance of a fluidic hammer controlled by an output-fed bistable fluidic oscillator. Given that couple mechanism exists between the flow field in the fluidic oscillator and the impact body, dynamic mesh technique and a user-defined function written in C programming language were used to update the mesh in the simulations. In terms of the evaluation of performance, the focus is on the single-impact energy and output power of the fluidic hammer in this study, to investigate the effect of different parameters of the impact body on them. Experimental tests based on the noncontact measuring method were conducted to verify the simulation results, by which the accuracy and reliability of this CFD simulation method was proved.

  5. Systematic reverse engineering of network topologies: a case study of resettable bistable cellular responses.

    Science.gov (United States)

    Mondal, Debasish; Dougherty, Edward; Mukhopadhyay, Abhishek; Carbo, Adria; Yao, Guang; Xing, Jianhua

    2014-01-01

    A focused theme in systems biology is to uncover design principles of biological networks, that is, how specific network structures yield specific systems properties. For this purpose, we have previously developed a reverse engineering procedure to identify network topologies with high likelihood in generating desired systems properties. Our method searches the continuous parameter space of an assembly of network topologies, without enumerating individual network topologies separately as traditionally done in other reverse engineering procedures. Here we tested this CPSS (continuous parameter space search) method on a previously studied problem: the resettable bistability of an Rb-E2F gene network in regulating the quiescence-to-proliferation transition of mammalian cells. From a simplified Rb-E2F gene network, we identified network topologies responsible for generating resettable bistability. The CPSS-identified topologies are consistent with those reported in the previous study based on individual topology search (ITS), demonstrating the effectiveness of the CPSS approach. Since the CPSS and ITS searches are based on different mathematical formulations and different algorithms, the consistency of the results also helps cross-validate both approaches. A unique advantage of the CPSS approach lies in its applicability to biological networks with large numbers of nodes. To aid the application of the CPSS approach to the study of other biological systems, we have developed a computer package that is available in Information S1.

  6. Numerical implementation of a VCSEL-based stochastic logic gate via polarization bistability.

    Science.gov (United States)

    Zamora-Munt, J; Masoller, C

    2010-08-02

    We study the interplay of polarization bistability, spontaneous emission noise and aperiodic current modulation in vertical cavity surface emitting lasers (VCSELs). We demonstrate the phenomenon of logic stochastic resonance (LSR), by which the laser gives robust and reliable logic response to two logic inputs encoded in an aperiodic signal directly modulating the laser bias current. The probability of a correct response is controlled by the noise strength, and is equal to 1 in a wide region of noise strengths. LSR is associated with optimal noise-activated polarization switchings (the so-called "inter-well" dynamics if one considers the VCSEL as a bistable system described by a double-well potential) and optimal sensitivity to spontaneous emission in each polarization (the "intra-well" dynamics in the double-well potential picture). The robust nature of LSR in VCSELs offers interesting perspectives for novel applications and provides yet another example of a driven nonlinear optical system where noise can be employed constructively.

  7. Bi-stability in type 2 diabetes mellitus multi-organ signalling network.

    Directory of Open Access Journals (Sweden)

    Shubhankar Kulkarni

    Full Text Available Type 2 diabetes mellitus (T2DM is believed to be irreversible although no component of the pathophysiology is irreversible. We show here with a network model that the apparent irreversibility is contributed by the structure of the network of inter-organ signalling. A network model comprising all known inter-organ signals in T2DM showed bi-stability with one insulin sensitive and one insulin resistant attractor. The bi-stability was made robust by multiple positive feedback loops suggesting an evolved allostatic system rather than a homeostatic system. In the absence of the complete network, impaired insulin signalling alone failed to give a stable insulin resistant or hyperglycemic state. The model made a number of correlational predictions many of which were validated by empirical data. The current treatment practice targeting obesity, insulin resistance, beta cell function and normalization of plasma glucose failed to reverse T2DM in the model. However certain behavioural and neuro-endocrine interventions ensured a reversal. These results suggest novel prevention and treatment approaches which need to be tested empirically.

  8. Understanding bistability in yeast glycolysis using general properties of metabolic pathways.

    Science.gov (United States)

    Planqué, Robert; Bruggeman, Frank J; Teusink, Bas; Hulshof, Josephus

    2014-09-01

    Glycolysis is the central pathway in energy metabolism in the majority of organisms. In a recent paper, van Heerden et al. showed experimentally and computationally that glycolysis can exist in two states, a global steady state and a so-called imbalanced state. In the imbalanced state, intermediary metabolites accumulate at low levels of ATP and inorganic phosphate. It was shown that Baker's yeast uses a peculiar regulatory mechanism--via trehalose metabolism--to ensure that most yeast cells reach the steady state and not the imbalanced state. Here we explore the apparent bistable behaviour in a core model of glycolysis that is based on a well-established detailed model, and study in great detail the bifurcation behaviour of solutions, without using any numerical information on parameter values. We uncover a rich suite of solutions, including so-called imbalanced states, bistability, and oscillatory behaviour. The techniques employed are generic, directly suitable for a wide class of biochemical pathways, and could lead to better analytical treatments of more detailed models. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. UP-DOWN cortical dynamics reflect state transitions in a bistable network

    Science.gov (United States)

    Roxin, Alex; Barthó, Peter; Luczak, Artur

    2017-01-01

    In the idling brain, neuronal circuits transition between periods of sustained firing (UP state) and quiescence (DOWN state), a pattern the mechanisms of which remain unclear. Here we analyzed spontaneous cortical population activity from anesthetized rats and found that UP and DOWN durations were highly variable and that population rates showed no significant decay during UP periods. We built a network rate model with excitatory (E) and inhibitory (I) populations exhibiting a novel bistable regime between a quiescent and an inhibition-stabilized state of arbitrarily low rate. Fluctuations triggered state transitions, while adaptation in E cells paradoxically caused a marginal decay of E-rate but a marked decay of I-rate in UP periods, a prediction that we validated experimentally. A spiking network implementation further predicted that DOWN-to-UP transitions must be caused by synchronous high-amplitude events. Our findings provide evidence of bistable cortical networks that exhibit non-rhythmic state transitions when the brain rests. PMID:28826485

  10. Dispersive optical bistability in a nonideal Fabry-Perot cavity II. Numerical results on side-mode instabilities

    NARCIS (Netherlands)

    van Wonderen, A.J.; Suttorp, L.G.

    1991-01-01

    Instabilities in the nearest side-modes are predicted for dispersive optical bistability in a nonideal Fabry-Perot cavity. The results are based on a linear stability analysis of the Maxwell-Bloch equations. This analysis leads to a boundary value problem for a four-dimensional set of linear

  11. Investigating the bistability characteristics of GaN/AlN resonant tunneling diodes for ultrafast nonvolatile memory

    Science.gov (United States)

    Nagase, Masanori; Takahashi, Tokio; Shimizu, Mitsuaki

    2015-03-01

    The bistability characteristics of GaN/AlN resonant tunneling diodes (RTDs) grown on a sapphire substrate by metalorganic vapor phase epitaxy (MOVPE) were investigated to better understand their physical origin and explore their use in nonvolatile memories. The bistability current-voltage (I-V) characteristics of GaN/AlN RTDs, which were due to intersubband transitions and electron accumulation in the quantum well, were clearly observed over a wide temperature range between 50 and 300 K. However, the I-V characteristics sometimes degraded at temperatures above 250 K. Complex staircase structures were observed in the voltage region showing a negative differential resistance in the I-V curve, and the forward current increased or decreased rapidly as the forward-bias voltage increased. Repeated measurements of the I-V characteristics over the wide temperature range between 50 and 300 K revealed that the bistability characteristics of GaN/AlN RTDs degraded owing to the leakage of electrons accumulating in the quantum well through a deep level in the AlN barrier associated with crystal defects such as dislocations and impurities. Therefore, reduction in crystal defect and impurity densities in the AlN barrier, and a careful design that considers deep levels are important for realizing realize ultrafast nonvolatile memories based on the bistability characteristics of GaN/AlN RTDs.

  12. A statically balanced and bi-stable compliant end effector combined with a laparoscopic 2DoF robotic arm

    NARCIS (Netherlands)

    Lassooij, J.; Tolou, N.; Tortora, G.; Caccavaro, S.; Menciassi, A.; Herder, J.L.

    2012-01-01

    This article presents the design of a newly developed 2DoF robotic arm with a novel statically balanced and bi-stable compliant grasper as the end effector for laparoscopic surgery application. The arm is based on internal motors actuating 2 rotational DoFs: pitch and roll. The positive stiffness of

  13. All-optical induction and efficient control of molecular orientation switching, bistability, and dynamic precession in nematic liquid crystals

    Science.gov (United States)

    Galstian, Tigran V.; Drnoyan, V.

    1998-01-01

    Collective character of molecular interaction in liquid crystals creates an intrinsic feedback mechanism. Two co- propagating noncoherent beams of orthogonal polarization produce strong molecular orientation switching and optical bistability without additional external fields and feedback. The angular momentum of the combined light is easily controlled, and a light-driven molecular motor is demonstrated.

  14. An analytical approach for predicting the energy capture and conversion by impulsively-excited bistable vibration energy harvesters

    Science.gov (United States)

    Harne, R. L.; Zhang, Chunlin; Li, Bing; Wang, K. W.

    2016-07-01

    Impulsive energies are abundant throughout the natural and built environments, for instance as stimulated by wind gusts, foot-steps, or vehicle-road interactions. In the interest of maximizing the sustainability of society's technological developments, one idea is to capture these high-amplitude and abrupt energies and convert them into usable electrical power such as for sensors which otherwise rely on less sustainable power supplies. In this spirit, the considerable sensitivity to impulse-type events previously uncovered for bistable oscillators has motivated recent experimental and numerical studies on the power generation performance of bistable vibration energy harvesters. To lead to an effective and efficient predictive tool and design guide, this research develops a new analytical approach to estimate the electroelastic response and power generation of a bistable energy harvester when excited by an impulse. Comparison with values determined by direct simulation of the governing equations shows that the analytically predicted net converted energies are very accurate for a wide range of impulse strengths. Extensive experimental investigations are undertaken to validate the analytical approach and it is seen that the predicted estimates of the impulsive energy conversion are in excellent agreement with the measurements, and the detailed structural dynamics are correctly reproduced. As a result, the analytical approach represents a significant leap forward in the understanding of how to effectively leverage bistable structures as energy harvesting devices and introduces new means to elucidate the transient and far-from-equilibrium dynamics of nonlinear systems more generally.

  15. Analog very large-scale integrated (VLSI) implementation of a model of amplitude-modulation sensitivity in the auditory brainstem.

    Science.gov (United States)

    van Schaik, A; Meddis, R

    1999-02-01

    An analog very large-scale integrated (VLSI) implementation of a model of signal processing in the auditory brainstem is presented and evaluated. The implementation is based on a model of amplitude-modulation sensitivity in the central nucleus of the inferior colliculus (CNIC) previously described by Hewitt and Meddis [J. Acoust. Soc. Am. 95, 2145-2159 (1994)]. A single chip is used to implement the three processing stages of the model; the inner-hair cell (IHC), cochlear nucleus sustained-chopper, and CNIC coincidence-detection stages. The chip incorporates two new circuits: an IHC circuit and a neuron circuit. The input to the chip is taken from a "silicon cochlea" consisting of a cascade of filters that simulate basilar membrane mechanical frequency selectivity. The chip which contains 142 neurons was evaluated using amplitude-modulated pure tones. Individual cells in the CNIC stage demonstrate bandpass rate-modulation responses using these stimuli. The frequency of modulation is represented spatially in an array of these cells as the location of the cell generating the highest rate of action potentials. The chip processes acoustic signals in real time and demonstrates the feasibility of using analog VLSI to build and test auditory models that use large numbers of component neurons.

  16. An Asynchronous Low Power and High Performance VLSI Architecture for Viterbi Decoder Implemented with Quasi Delay Insensitive Templates.

    Science.gov (United States)

    Devi, T Kalavathi; Palaniappan, Sakthivel

    2015-01-01

    Convolutional codes are comprehensively used as Forward Error Correction (FEC) codes in digital communication systems. For decoding of convolutional codes at the receiver end, Viterbi decoder is often used to have high priority. This decoder meets the demand of high speed and low power. At present, the design of a competent system in Very Large Scale Integration (VLSI) technology requires these VLSI parameters to be finely defined. The proposed asynchronous method focuses on reducing the power consumption of Viterbi decoder for various constraint lengths using asynchronous modules. The asynchronous designs are based on commonly used Quasi Delay Insensitive (QDI) templates, namely, Precharge Half Buffer (PCHB) and Weak Conditioned Half Buffer (WCHB). The functionality of the proposed asynchronous design is simulated and verified using Tanner Spice (TSPICE) in 0.25 µm, 65 nm, and 180 nm technologies of Taiwan Semiconductor Manufacture Company (TSMC). The simulation result illustrates that the asynchronous design techniques have 25.21% of power reduction compared to synchronous design and work at a speed of 475 MHz.

  17. An Asynchronous Low Power and High Performance VLSI Architecture for Viterbi Decoder Implemented with Quasi Delay Insensitive Templates

    Directory of Open Access Journals (Sweden)

    T. Kalavathi Devi

    2015-01-01

    Full Text Available Convolutional codes are comprehensively used as Forward Error Correction (FEC codes in digital communication systems. For decoding of convolutional codes at the receiver end, Viterbi decoder is often used to have high priority. This decoder meets the demand of high speed and low power. At present, the design of a competent system in Very Large Scale Integration (VLSI technology requires these VLSI parameters to be finely defined. The proposed asynchronous method focuses on reducing the power consumption of Viterbi decoder for various constraint lengths using asynchronous modules. The asynchronous designs are based on commonly used Quasi Delay Insensitive (QDI templates, namely, Precharge Half Buffer (PCHB and Weak Conditioned Half Buffer (WCHB. The functionality of the proposed asynchronous design is simulated and verified using Tanner Spice (TSPICE in 0.25 µm, 65 nm, and 180 nm technologies of Taiwan Semiconductor Manufacture Company (TSMC. The simulation result illustrates that the asynchronous design techniques have 25.21% of power reduction compared to synchronous design and work at a speed of 475 MHz.

  18. Isomerization and optical bistability of DR1 doped organic-inorganic sol-gel thin film

    Science.gov (United States)

    Gao, Tianxi; Que, Wenxiu; Shao, Jinyou

    2015-10-01

    To investigate the isomerization process of the disperse red 1 (DR1) doped TiO2/ormosil thin film, both the photo-isomerization and the thermal isomerization of the thin films were observed as a change of the absorption spectrum. Under a real-time heat treatment, the change of the linear refractive index shows a thermal stable working temperature range below Tg. The optical bistability (OB) effect of the DR1 doped thin films based on different matrices was studied and measured at a wavelength of 532 nm. Results indicate that the TiO2/ormosils based thin film presents a better OB-gain than that of the poly (methyl methacrylate) (PMMA) based thin film due to its more rigid network structure. Moreover, it is also noted that higher titanium content is helpful for enhancing the OB-gain of the as-prepared hybrid thin films.

  19. Is "Σ" purple or green? Bistable grapheme-color synesthesia induced by ambiguous characters.

    Science.gov (United States)

    Kim, Suhkyung; Blake, Randolph; Kim, Chai-Youn

    2013-09-01

    People with grapheme-color synesthesia perceive specific colors when viewing different letters or numbers. Previous studies have suggested that synesthetic color experience can be bistable when induced by an ambiguous character. However, the exact relationship between processes underlying the identity of an alphanumeric character and the experience of the induced synesthetic color has not been examined. In the present study, we explored this by focusing on the temporal relation of inducer identification and color emergence using inducers whose identity could be rendered ambiguous upon rotation of the characters. Specifically, achromatic alphabetic letters (W/M) and digits (6/9) were presented at varying angles to 9 grapheme-color synesthetes. Results showed that grapheme identification and synesthetically perceived grapheme color covary with the orientation of the test stimulus and that synesthetes were slower naming the experienced color than identifying the character, particularly at intermediate angles where ambiguity was greatest. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. Bi-stability in a two-level quantum dot with attracting e–e interaction

    Energy Technology Data Exchange (ETDEWEB)

    Eskandari-asl, Amir, E-mail: amir.eskandari.asl@gmail.com

    2016-12-15

    By considering a current carrying two-level quantum dot (QD) with e–e attraction, we obtain the current and electron populations as functions of applied bias voltage using a self-consistent Hartree–Fock (HF) approximation and show that the system could be bi-stable and there exist hysteresis loops. Investigating the permanent polarization, we also show that the permanent polarization changes sign and interpret this as a quantum phase transition, since our system is at zero temperature. - Highlights: • Our system could have zero, one or two steps in its I–V curve. • Depending on the strength of the e–e attraction, there could be hysteresis loops around each step. • The polarization of the system changes sign by changing the bias voltage and this is a quantum phase transition.