WorldWideScience

Sample records for neuromorphic bistable vlsi

  1. Pursuit, Avoidance, and Cohesion in Flight: Multi-Purpose Control Laws and Neuromorphic VLSI

    Science.gov (United States)

    2010-10-01

    spatial navigation in mammals. We have designed, fabricated, and are now testing a neuromorphic VLSI chip that implements a spike-based, attractor...Control Laws and Neuromorphic VLSI 5a. CONTRACT NUMBER 070402-7705 5b. GRANT NUMBER FA9550-07-1-0446 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...implementations (custom Neuromorphic VLSI and robotics) we will apply important practical constraints that can lead to deeper insight into how and why efficient

  2. Modeling selective attention using a neuromorphic analog VLSI device.

    Science.gov (United States)

    Indiveri, G

    2000-12-01

    Attentional mechanisms are required to overcome the problem of flooding a limited processing capacity system with information. They are present in biological sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) chip, using analog neuromorphic circuits. The chip exploits a spike-based representation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the selective attention mechanism and provide experimental data for each circuit. We demonstrate the expected behavior of the model at the system level by stimulating the chip with both artificially generated control signals and signals obtained from a saliency map, computed from an image containing several salient features.

  3. Spike Neuromorphic VLSI-Based Bat Echolocation for Micro-Aerial Vehicle Guidance

    Science.gov (United States)

    2007-03-31

    IFinal 03/01/04 - 02/28/07 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Neuromorphic VLSI-based Bat Echolocation for Micro-aerial 5b.GRANTNUMBER Vehicle...uncovered interesting new issues in our choice for representing the intensity of signals. We have just finished testing the first chip version of an echo...timing-based algorithm (’openspace’) for sonar-guided navigation amidst multiple obstacles. 15. SUBJECT TERMS Neuromorphic VLSI, bat echolocation

  4. 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.

  5. Robust Working Memory in an Asynchronously Spiking Neural Network Realized with Neuromorphic VLSI.

    Science.gov (United States)

    Giulioni, Massimiliano; Camilleri, Patrick; Mattia, Maurizio; Dante, Vittorio; Braun, Jochen; Del Giudice, Paolo

    2011-01-01

    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 leaky 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.

  6. Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

    Science.gov (United States)

    Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

    2017-12-01

    Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

  7. Adaptive WTA with an analog VLSI neuromorphic learning chip.

    Science.gov (United States)

    Häfliger, Philipp

    2007-03-01

    In this paper, we demonstrate how a particular spike-based learning rule (where exact temporal relations between input and output spikes of a spiking model neuron determine the changes of the synaptic weights) can be tuned to express rate-based classical Hebbian learning behavior (where the average input and output spike rates are sufficient to describe the synaptic changes). This shift in behavior is controlled by the input statistic and by a single time constant. The learning rule has been implemented in a neuromorphic very large scale integration (VLSI) chip as part of a neurally inspired spike signal image processing system. The latter is the result of the European Union research project Convolution AER Vision Architecture for Real-Time (CAVIAR). Since it is implemented as a spike-based learning rule (which is most convenient in the overall spike-based system), even if it is tuned to show rate behavior, no explicit long-term average signals are computed on the chip. We show the rule's rate-based Hebbian learning ability in a classification task in both simulation and chip experiment, first with artificial stimuli and then with sensor input from the CAVIAR system.

  8. Towards an Analogue Neuromorphic VLSI Instrument for the Sensing of Complex Odours

    Science.gov (United States)

    Ab Aziz, Muhammad Fazli; Harun, Fauzan Khairi Che; Covington, James A.; Gardner, Julian W.

    2011-09-01

    Almost all electronic nose instruments reported today employ pattern recognition algorithms written in software and run on digital processors, e.g. micro-processors, microcontrollers or FPGAs. Conversely, in this paper we describe the analogue VLSI implementation of an electronic nose through the design of a neuromorphic olfactory chip. The modelling, design and fabrication of the chip have already been reported. Here a smart interface has been designed and characterised for thisneuromorphic chip. Thus we can demonstrate the functionality of the a VLSI neuromorphic chip, producing differing principal neuron firing patterns to real sensor response data. Further work is directed towards integrating 9 separate neuromorphic chips to create a large neuronal network to solve more complex olfactory problems.

  9. 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.

  10. Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System.

    Science.gov (United States)

    Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas; Chicca, Elisabetta

    2012-01-01

    Many sounds of ecological importance, such as communication calls, are characterized 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 thalamo-cortical 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 spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

  11. A neuromorphic VLSI device for implementing 2-D selective attention systems.

    Science.gov (United States)

    Indiveri, G

    2001-01-01

    Selective attention is a mechanism used to sequentially select and process salient subregions of the input space, while suppressing inputs arriving from nonsalient regions. By processing small amounts of sensory information in a serial fashion, rather than attempting to process all the sensory data in parallel, this mechanism overcomes the problem of flooding limited processing capacity systems with sensory inputs. It is found in many biological systems and can be a useful engineering tool for developing artificial systems that need to process in real-time sensory data. In this paper we present a neuromorphic hardware model of a selective attention mechanism implemented on a very large scale integration (VLSI) chip, using analog circuits. The chip makes use of a spike-based representation for receiving input signals, transmitting output signals and for shifting the selection of the attended input stimulus over time. It can be interfaced to neuromorphic sensors and actuators, for implementing multichip selective attention systems. We describe the characteristics of the circuits used in the architecture and present experimental data measured from the system.

  12. Implementation of neuromorphic systems: from discrete components to analog VLSI chips (testing and communication issues).

    Science.gov (United States)

    Dante, V; Del Giudice, P; Mattia, M

    2001-01-01

    We review a series of implementations of electronic devices aiming at imitating to some extent structure and function of simple neural systems, with particular emphasis on communication issues. We first provide a short overview of general features of such "neuromorphic" devices and the implications of setting up "tests" for them. We then review the developments directly related to our work at the Istituto Superiore di Sanità (ISS): a pilot electronic neural network implementing a simple classifier, autonomously developing internal representations of incoming stimuli; an output network, collecting information from the previous classifier and extracting the relevant part to be forwarded to the observer; an analog, VLSI (very large scale integration) neural chip implementing a recurrent network of spiking neurons and plastic synapses, and the test setup for it; a board designed to interface the standard PCI (peripheral component interconnect) bus of a PC with a special purpose, asynchronous bus for communication among neuromorphic chips; a short and preliminary account of an application-oriented device, taking advantage of the above communication infrastructure.

  13. Spike Neuromorphic VLSI-Based Bat Echolocation for Micro-Aerial Vehicle Guidance

    National Research Council Canada - National Science Library

    Horiuchi, Timothy K; Krishnaprasad, P. S

    2007-01-01

    .... This includes multiple efforts related to a VLSI-based echolocation system being developed in one of our laboratories from algorithm development, bat flight data analysis, to VLSI circuit design...

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

    OpenAIRE

    Massimiliano Giulioni; Federico Corradi; Vittorio Dante; Paolo del Giudice

    2015-01-01

    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 compri...

  15. Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems.

    Science.gov (United States)

    Indiveri, Giacomo

    2008-09-03

    Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA) network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

  16. 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.

  17. Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

    Directory of Open Access Journals (Sweden)

    Giacomo Indiveri

    2008-09-01

    Full Text Available Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

  18. Coupling an aVLSI neuromorphic vision chip to a neurotrophic model of synaptic plasticity: the development of topography.

    Science.gov (United States)

    Elliott, Terry; Kramer, Jörg

    2002-10-01

    We couple a previously studied, biologically inspired neurotrophic model of activity-dependent competitive synaptic plasticity and neuronal development to a neuromorphic retina chip. Using this system, we examine the development and refinement of a topographic mapping between an array of afferent neurons (the retinal ganglion cells) and an array of target neurons. We find that the plasticity model can indeed drive topographic refinement in the presence of afferent activity patterns generated by a real-world device. We examine the resilience of the developing system to the presence of high levels of noise by adjusting the spontaneous firing rate of the silicon neurons.

  19. 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

  20. 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...

  1. Neuromorphic olfaction neuromorphic olfaction

    CERN Document Server

    Persaud, Krishna C; Marco, Santiago

    2016-01-01

    Engineering Aspects of Olfaction; Krishna C. PersaudStudy of the Coding Efficiency of Populations of OlfactoryReceptor Neurons and Olfactory Glomeruli; Agustín Gutiérrez-Gálvez and Santiago MarcoMimicking Biological Olfaction with Very Large ChemicalArrays; Mara Bernabei, Romeo Beccherelli, Emiliano Zampetti,Simone Pantalei, and Krishna C. PersaudThe Synthetic Moth: A Neuromorphic Approach towardArtificial Olfaction in Robots; Vasiliki Vouloutsi, Lucas L. Lopez-Serrano,Zenon Mathews, Alex Escuredo Chimeno, Andrey Ziyatdinov, Alexandre Perera i Lluna, Sergi Bermúdez i Badia, and Paul F. M. J. Verschure Reactive and Cognitive Search Strategies for Olfactory Robots; Dominique Martinez and Eduardo Martin MoraudPerformance of a Computational Model of the MammalianOlfactory System; Simon Benjaminsson, Pawel Herman, and Anders LansnerIndex.

  2. 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

  3. Neuromorphic walking gait control.

    Science.gov (United States)

    Still, Susanne; Hepp, Klaus; Douglas, Rodney J

    2006-03-01

    We present a neuromorphic pattern generator for controlling the walking gaits of four-legged robots which is inspired by central pattern generators found in the nervous system and which is implemented as a very large scale integrated (VLSI) chip. The chip contains oscillator circuits that mimic the output of motor neurons in a strongly simplified way. We show that four coupled oscillators can produce rhythmic patterns with phase relationships that are appropriate to generate all four-legged animal walking gaits. These phase relationships together with frequency and duty cycle of the oscillators determine the walking behavior of a robot driven by the chip, and they depend on a small set of stationary bias voltages. We give analytic expressions for these dependencies. This chip reduces the complex, dynamic inter-leg control problem associated with walking gait generation to the problem of setting a few stationary parameters. It provides a compact and low power solution for walking gait control in robots.

  4. 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.

  5. Systematic configuration and automatic tuning of neuromorphic systems

    OpenAIRE

    Sheik Sadique; Stefanini Fabio; Neftci Emre; Chicca Elisabetta; Indiveri Giacomo

    2011-01-01

    In the past recent years several research groups have proposed neuromorphic Very Large Scale Integration (VLSI) devices that implement event-based sensors or biophysically realistic networks of spiking neurons. It has been argued that these devices can be used to build event-based systems, for solving real-world applications in real-time, with efficiencies and robustness that cannot be achieved with conventional computing technologies. In order to implement complex event-based neuromorphic sy...

  6. 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

  7. Towards a neuromorphic vestibular system.

    Science.gov (United States)

    Corradi, Federico; Zambrano, Davide; Raglianti, Marco; Passetti, Giovanni; Laschi, Cecilia; Indiveri, Giacomo

    2014-10-01

    The vestibular system plays a crucial role in the sense of balance and spatial orientation in mammals. It is a sensory system that detects both rotational and translational motion of the head, via its semicircular canals and otoliths respectively. In this work, we propose a real-time hardware model of an artificial vestibular system, implemented using a custom neuromorphic Very Large Scale Integration (VLSI) multi-neuron chip interfaced to a commercial Inertial Measurement Unit (IMU). The artificial vestibular system is realized with spiking neurons that reproduce the responses of biological hair cells present in the real semicircular canals and otholitic organs. We demonstrate the real-time performance of the hybrid analog-digital system and characterize its response properties, presenting measurements of a successful encoding of angular velocities as well as linear accelerations. As an application, we realized a novel implementation of a recurrent integrator network capable of keeping track of the current angular position. The experimental results provided validate the hardware implementation via comparisons with a detailed computational neuroscience model. In addition to being an ideal tool for developing bio-inspired robotic technologies, this work provides a basis for developing a complete low-power neuromorphic vestibular system which integrates the hardware model of the neural signal processing pathway described with custom bio-mimetic gyroscopic sensors, exploiting neuromorphic principles in both mechanical and electronic aspects.

  8. A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.

    Science.gov (United States)

    Qiao, Ning; Mostafa, Hesham; Corradi, Federico; Osswald, Marc; Stefanini, Fabio; Sumislawska, Dora; Indiveri, Giacomo

    2015-01-01

    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.

  9. 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

  10. 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

  11. 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.

  12. Foundations of Neuromorphic Computing

    Science.gov (United States)

    2013-05-01

    paradigms: few sensors/complex computations and many sensors/simple computation. Challenges with Nano-enabled Neuromorphic Chips A wide variety of...FOUNDATIONS OF NEUROMORPHIC COMPUTING MAY 2013 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION...2009 – SEP 2012 4. TITLE AND SUBTITLE FOUNDATIONS OF NEUROMORPHIC COMPUTING 5a. CONTRACT NUMBER IN-HOUSE 5b. GRANT NUMBER N/A 5c. PROGRAM

  13. 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

  14. 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

  15. A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long-term memory.

    Science.gov (United States)

    Chicca, E; Badoni, D; Dante, V; D'Andreagiovanni, M; Salina, G; Carota, L; Fusi, S; Del Giudice, P

    2003-01-01

    Electronic neuromorphic devices with on-chip, on-line learning should be able to modify quickly the synaptic couplings to acquire information about new patterns to be stored (synaptic plasticity) and, at the same time, preserve this information on very long time scales (synaptic stability). Here, we illustrate the electronic implementation of a simple solution to this stability-plasticity problem, recently proposed and studied in various contexts. It is based on the observation that reducing the analog depth of the synapses to the extreme (bistable synapses) does not necessarily disrupt the performance of the device as an associative memory, provided that 1) the number of neurons is large enough; 2) the transitions between stable synaptic states are stochastic; and 3) learning is slow. The drastic reduction of the analog depth of the synaptic variable also makes this solution appealing from the point of view of electronic implementation and offers a simple methodological alternative to the technological solution based on floating gates. We describe the full custom analog very large-scale integration (VLSI) realization of a small network of integrate-and-fire neurons connected by bistable deterministic plastic synapses which can implement the idea of stochastic learning. In the absence of stimuli, the memory is preserved indefinitely. During the stimulation the synapse undergoes quick temporary changes through the activities of the pre- and postsynaptic neurons; those changes stochastically result in a long-term modification of the synaptic efficacy. The intentionally disordered pattern of connectivity allows the system to generate a randomness suited to drive the stochastic selection mechanism. We check by a suitable stimulation protocol that the stochastic synaptic plasticity produces the expected pattern of potentiation and depression in the electronic network.

  16. Foldable neuromorphic memristive electronics

    KAUST Repository

    Ghoneim, Mohamed T.; Zidan, Mohammed A.; Salama, Khaled N.; Hussain, Muhammad Mustafa

    2014-01-01

    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

  17. Neuromorphic Data Microscope

    Energy Technology Data Exchange (ETDEWEB)

    Naegle, John H.; Suppona, Roger A.; Aimone, James Bradley; James, Conrad D.; Follett, David R.; Townsend, Duncan C.M.; Follett, Pamela L.; Karpman, Gabe D.

    2017-08-01

    In 2016, Lewis Rhodes Labs, (LRL), shipped the first commercially viable Neuromorphic Processing Unit, (NPU), branded as a Neuromorphic Data Microscope (NDM). This product leverages architectural mechanisms derived from the sensory cortex of the human brain to efficiently implement pattern matching. LRL and Sandia National Labs have optimized this product for streaming analytics, and demonstrated a 1,000x power per operation reduction in an FPGA format. When reduced to an ASIC, the efficiency will improve to 1,000,000x. Additionally, the neuromorphic nature of the device gives it powerful computational attributes that are counterintuitive to those schooled in traditional von Neumann architectures. The Neuromorphic Data Microscope is the first of a broad class of brain-inspired, time domain processors that will profoundly alter the functionality and economics of data processing.

  18. 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

  19. Neuromorphic VLSI vision system for real-time texture segregation.

    Science.gov (United States)

    Shimonomura, Kazuhiro; Yagi, Tetsuya

    2008-10-01

    The visual system of the brain can perceive an external scene in real-time with extremely low power dissipation, although the response speed of an individual neuron is considerably lower than that of semiconductor devices. The neurons in the visual pathway generate their receptive fields using a parallel and hierarchical architecture. This architecture of the visual cortex is interesting and important for designing a novel perception system from an engineering perspective. The aim of this study is to develop a vision system hardware, which is designed inspired by a hierarchical visual processing in V1, for real time texture segregation. The system consists of a silicon retina, orientation chip, and field programmable gate array (FPGA) circuit. The silicon retina emulates the neural circuits of the vertebrate retina and exhibits a Laplacian-Gaussian-like receptive field. The orientation chip selectively aggregates multiple pixels of the silicon retina in order to produce Gabor-like receptive fields that are tuned to various orientations by mimicking the feed-forward model proposed by Hubel and Wiesel. The FPGA circuit receives the output of the orientation chip and computes the responses of the complex cells. Using this system, the neural images of simple cells were computed in real-time for various orientations and spatial frequencies. Using the orientation-selective outputs obtained from the multi-chip system, a real-time texture segregation was conducted based on a computational model inspired by psychophysics and neurophysiology. The texture image was filtered by the two orthogonally oriented receptive fields of the multi-chip system and the filtered images were combined to segregate the area of different texture orientation with the aid of FPGA. The present system is also useful for the investigation of the functions of the higher-order cells that can be obtained by combining the simple and complex cells.

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

    Directory of Open Access Journals (Sweden)

    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. 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.

  2. Energy-efficient neuromorphic classifiers

    OpenAIRE

    Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano

    2015-01-01

    Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. Neuromorphic engineering promises extremely low energy consumptions, comparable to those of the nervous system. However, until now the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, rendering el...

  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 sensory systems.

    Science.gov (United States)

    Liu, Shih-Chii; Delbruck, Tobi

    2010-06-01

    Biology provides examples of efficient machines which greatly outperform conventional technology. Designers in neuromorphic engineering aim to construct electronic systems with the same efficient style of computation. This task requires a melding of novel engineering principles with knowledge gleaned from neuroscience. We discuss recent progress in realizing neuromorphic sensory systems which mimic the biological retina and cochlea, and subsequent sensor processing. The main trends are the increasing number of sensors and sensory systems that communicate through asynchronous digital signals analogous to neural spikes; the improved performance and usability of these sensors; and novel sensory processing methods which capitalize on the timing of spikes from these sensors. Experiments using these sensors can impact how we think the brain processes sensory information. 2010 Elsevier Ltd. All rights reserved.

  5. 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.

  6. Neuromorphic Deep Learning Machines

    OpenAIRE

    Neftci, E; Augustine, C; Paul, S; Detorakis, G

    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 Back Propagation (BP) rule, often relies on the immediate availability of network-wide...

  7. 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.

  8. Parallel VLSI Architecture

    Science.gov (United States)

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

    1985-01-01

    Fermat number transformation convolutes two digital data sequences. Very-large-scale integration (VLSI) applications, such as image and radar signal processing, X-ray reconstruction, and spectrum shaping, linear convolution of two digital data sequences of arbitrary lenghts accomplished using Fermat number transform (ENT).

  9. 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.

  10. 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

  11. Bistable Reflective Etalon (BRET)

    National Research Council Canada - National Science Library

    Shellenbarger, Zane

    2003-01-01

    This project designed, fabricated, and characterized normal-incidence etalon structures at 1550 nm wavelength operation for application, as bistable elements, to photonic analog-to-digital conversion...

  12. 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

  13. 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.

  14. Energy-Efficient Neuromorphic Classifiers.

    Science.gov (United States)

    Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano

    2016-10-01

    Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. The energy consumptions promised by neuromorphic engineering are extremely low, comparable to those of the nervous system. Until now, however, the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, thereby obfuscating a direct comparison of their energy consumption to that used by conventional von Neumann digital machines solving real-world tasks. Here we show that a recent technology developed by IBM can be leveraged to realize neuromorphic circuits that operate as classifiers of complex real-world stimuli. Specifically, we provide a set of general prescriptions to enable the practical implementation of neural architectures that compete with state-of-the-art classifiers. We also show that the energy consumption of these architectures, realized on the IBM chip, is typically two or more orders of magnitude lower than that of conventional digital machines implementing classifiers with comparable performance. Moreover, the spike-based dynamics display a trade-off between integration time and accuracy, which naturally translates into algorithms that can be flexibly deployed for either fast and approximate classifications, or more accurate classifications at the mere expense of longer running times and higher energy costs. This work finally proves that the neuromorphic approach can be efficiently used in real-world applications and has significant advantages over conventional digital devices when energy consumption is considered.

  15. 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...

  16. Nano lasers in photonic VLSI

    NARCIS (Netherlands)

    Hill, M.T.; Oei, Y.S.; Smit, M.K.

    2007-01-01

    We examine the use of micro and nano lasers to form digital photonic VLSI building blocks. Problems such as isolation and cascading of building blocks are addressed, and the potential of future nano lasers explored.

  17. VLSI Architectures for Computing DFT's

    Science.gov (United States)

    Truong, T. K.; Chang, J. J.; Hsu, I. S.; Reed, I. S.; Pei, D. Y.

    1986-01-01

    Simplifications result from use of residue Fermat number systems. System of finite arithmetic over residue Fermat number systems enables calculation of discrete Fourier transform (DFT) of series of complex numbers with reduced number of multiplications. Computer architectures based on approach suitable for design of very-large-scale integrated (VLSI) circuits for computing DFT's. General approach not limited to DFT's; Applicable to decoding of error-correcting codes and other transform calculations. System readily implemented in VLSI.

  18. 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

  19. Digital characterization of a neuromorphic IRFPA

    Science.gov (United States)

    Caulfield, John T.; Fisher, John; Zadnik, Jerome A.; Mak, Ernest S.; Scribner, Dean A.

    1995-05-01

    This paper reports on the performance of the Neuromorphic IRFPA, the first IRFPA designed and fabricated to conduct temporal and spatial processing on the focal plane. The Neuromorphic IRFPA's unique on-chip processing capability can perform retina-like functions such as lateral inhibition and contrast enhancement, spatial and temporal filtering, image compression and edge enhancement, and logarithmic response. Previously, all evaluations of the Neuromorphic IRFPA camera have been performed on the analog video output. In the work leading up to this paper, the Neuromorphic was integrated to a digital recorder to collect quantitative laboratory and field data. This paper describes the operation and characterization of specific on-chip processes such as spatial and temporal kernel size control. The use of Neuromorphic on-chip processing in future IRFPAs is analyzed as applied to improving SNR via adaptive nonuniformity, charge handling, and dynamic range problems.

  20. Anthropomorphic reasoning about neuromorphic AGI safety

    Science.gov (United States)

    Jilk, David J.; Herd, Seth J.; Read, Stephen J.; O'Reilly, Randall C.

    2017-11-01

    One candidate approach to creating artificial general intelligence (AGI) is to imitate the essential computations of human cognition. This process is sometimes called 'reverse-engineering the brain' and the end product called 'neuromorphic.' We argue that, unlike with other approaches to AGI, anthropomorphic reasoning about behaviour and safety concerns is appropriate and crucial in a neuromorphic context. Using such reasoning, we offer some initial ideas to make neuromorphic AGI safer. In particular, we explore how basic drives that promote social interaction may be essential to the development of cognitive capabilities as well as serving as a focal point for human-friendly outcomes.

  1. What is refractive optical bistability

    International Nuclear Information System (INIS)

    Dzhehov, Tomislav

    1993-01-01

    The basic elements of the theory of refractive optical bistability, assuming mediums with linear absorption are given. Special attention is paid to bistable etalons of semiconductor materials an oxide glasses, since some of them are considered as promising components for optical bistability applications. The design optimization of such devices for minimum switching intensity is analyzed. Computer simulation of the transfer characteristic recording for two InSb etalons is presented. (author)

  2. The unsaturated bistable stochastic resonance system.

    Science.gov (United States)

    Zhao, Wenli; Wang, Juan; Wang, Linze

    2013-09-01

    We investigated the characteristics of the output saturation of the classical continuous bistable system (saturation bistable system) and its impact on stochastic resonance (SR). We further proposed a piecewise bistable SR system (unsaturated bistable system) and developed the expression of signal-to-noise ratio (SNR) using the adiabatic approximation theory. Compared with the saturation bistable system, the SNR is significantly improved in our unsaturated bistable SR system. The numerical simulation showed that the unsaturated bistable system performed better in extracting weak signals from strong background noise than the saturation bistable system.

  3. Controlling bistability by linear augmentation

    International Nuclear Information System (INIS)

    Sharma, Pooja Rani; Shrimali, Manish Dev; Prasad, Awadhesh; Feudel, Ulrike

    2013-01-01

    In many bistable oscillating systems only one of the attractors is desired to possessing certain system performance. We present a method to drive a bistable system to a desired target attractor by annihilating the other one. This shift from bistability to monostability is achieved by augmentation of the nonlinear oscillator with a linear control system. For a proper choice of the control function one of the attractors disappears at a critical coupling strength in an control-induced boundary crisis. This transition from bistability to monostability is demonstrated with two paradigmatic examples, the autonomous Chua oscillator and a neuronal system with a periodic input signal.

  4. Bistable Mechanisms for Space Applications.

    Science.gov (United States)

    Zirbel, Shannon A; Tolman, Kyler A; Trease, Brian P; Howell, Larry L

    2016-01-01

    Compliant bistable mechanisms are monolithic devices with two stable equilibrium positions separated by an unstable equilibrium position. They show promise in space applications as nonexplosive release mechanisms in deployment systems, thereby eliminating friction and improving the reliability and precision of those mechanical devices. This paper presents both analytical and numerical models that are used to predict bistable behavior and can be used to create bistable mechanisms in materials not previously feasible for compliant mechanisms. Materials compatible with space applications are evaluated for use as bistable mechanisms and prototypes are fabricated in three different materials. Pin-puller and cutter release mechanisms are proposed as potential space applications.

  5. Bistable microelectromechanical actuator

    Science.gov (United States)

    Fleming, James G.

    1999-01-01

    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.

  6. Distributed processing in bistable perception

    NARCIS (Netherlands)

    Knapen, T.H.J.

    2007-01-01

    A very incisive way of studying visual awareness and the mechanisms that underlie it, it to use bistable perception. In bistable perception, an observer's perceptual state alternates between one interpretation and its mutually exclusive counterpart while the stimulus remains the same. This gives us

  7. Lie group model neuromorphic geometric engine for real-time terrain reconstruction from stereoscopic aerial photos

    Science.gov (United States)

    Tsao, Thomas R.; Tsao, Doris

    1997-04-01

    In the 1980's, neurobiologist suggested a simple mechanism in primate visual cortex for maintaining a stable and invariant representation of a moving object. The receptive field of visual neurons has real-time transforms in response to motion, to maintain a stable representation. When the visual stimulus is changed due to motion, the geometric transform of the stimulus triggers a dual transform of the receptive field. This dual transform in the receptive fields compensates geometric variation in the stimulus. This process can be modelled using a Lie group method. The massive array of affine parameter sensing circuits will function as a smart sensor tightly coupled to the passive imaging sensor (retina). Neural geometric engine is a neuromorphic computing device simulating our Lie group model of spatial perception of primate's primal visual cortex. We have developed the computer simulation and experimented on realistic and synthetic image data, and performed a preliminary research of using analog VLSI technology for implementation of the neural geometric engine. We have benchmark tested on DMA's terrain data with their result and have built an analog integrated circuit to verify the computational structure of the engine. When fully implemented on ANALOG VLSI chip, we will be able to accurately reconstruct a 3D terrain surface in real-time from stereoscopic imagery.

  8. VLSI structures for track finding

    International Nuclear Information System (INIS)

    Dell'Orso, M.

    1989-01-01

    We discuss the architecture of a device based on the concept of associative memory designed to solve the track finding problem, typical of high energy physics experiments, in a time span of a few microseconds even for very high multiplicity events. This ''machine'' is implemented as a large array of custom VLSI chips. All the chips are equal and each of them stores a number of ''patterns''. All the patterns in all the chips are compared in parallel to the data coming from the detector while the detector is being read out. (orig.)

  9. The test of VLSI circuits

    Science.gov (United States)

    Baviere, Ph.

    Tests which have proven effective for evaluating VLSI circuits for space applications are described. It is recommended that circuits be examined after each manfacturing step to gain fast feedback on inadequacies in the production system. Data from failure modes which occur during operational lifetimes of circuits also permit redefinition of the manufacturing and quality control process to eliminate the defects identified. Other tests include determination of the operational envelope of the circuits, examination of the circuit response to controlled inputs, and the performance and functional speeds of ROM and RAM memories. Finally, it is desirable that all new circuits be designed with testing in mind.

  10. 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.

  11. A multichip aVLSI system emulating orientation selectivity of primary visual cortical cells.

    Science.gov (United States)

    Shimonomura, Kazuhiro; Yagi, Tetsuya

    2005-07-01

    In this paper, we designed and fabricated a multichip neuromorphic analog very large scale integrated (aVLSI) system, which emulates the orientation selective response of the simple cell in the primary visual cortex. The system consists of a silicon retina and an orientation chip. An image, which is filtered by a concentric center-surround (CS) antagonistic receptive field of the silicon retina, is transferred to the orientation chip. The image transfer from the silicon retina to the orientation chip is carried out with analog signals. The orientation chip selectively aggregates multiple pixels of the silicon retina, mimicking the feedforward model proposed by Hubel and Wiesel. The chip provides the orientation-selective (OS) outputs which are tuned to 0 degrees, 60 degrees, and 120 degrees. The feed-forward aggregation reduces the fixed pattern noise that is due to the mismatch of the transistors in the orientation chip. The spatial properties of the orientation selective response were examined in terms of the adjustable parameters of the chip, i.e., the number of aggregated pixels and size of the receptive field of the silicon retina. The multichip aVLSI architecture used in the present study can be applied to implement higher order cells such as the complex cell of the primary visual cortex.

  12. 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

  13. Optimization of Bistable Viscoelastic Systems

    DEFF Research Database (Denmark)

    Jensen, Kristian Ejlebjærg; Szabo, Peter; Okkels, Fridolin

    2014-01-01

    driving pressure corresponding to the point of bistability, such that the effect is enhanced. The point of bistability is, however, not explicitly contained in the solution, so we opt for a heuristic approach based on the dissipation ratio between the asymmetric and unstable symmetric flow solutions. We...... find a design that significantly reduces the driving pressure required for bistability, and furthermore is in agreement with the approach followed by experimental researchers. Furthermore, by comparing the two asymmetric solutions, we succesfully apply the same approach to a problem with two fluids...

  14. Bistable amphoteric centers in semiconductors

    International Nuclear Information System (INIS)

    Nikitina, A. G.; Zuev, V. V.

    2008-01-01

    It is shown that, at thermodynamic equilibrium, the release of charge carriers from the localized states of bistable amphoteric centers into quasi-free states depends on the degree of compensation. This brings about different functional dependences of the concentration of free charge carriers on temperature. It is found that, in uncompensated semiconductors, the concentration of free charge carriers follows the same dependence in the case of bistable amphoteric centers and bistable amphoteric U - centers, although the distributions of charge carriers over the charge states and configurations are different for these types of centers. The results can be used for interpreting various experimental data insufficiently explained in the context of the traditional approach

  15. 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.

  16. Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

    OpenAIRE

    Giacomo Indiveri

    2008-01-01

    Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computation...

  17. A Miniature Coupled Bistable Vibration Energy Harvester

    International Nuclear Information System (INIS)

    Zhu, D; Arthur, D C; Beeby, S P

    2014-01-01

    This paper reports the design and test of a miniature coupled bistable vibration energy harvester. Operation of a bistable structure largely depends on vibration amplitude rather than frequency, which makes it very promising for wideband vibration energy harvesting applications. A coupled bistable structure consists of a pair of mobile magnets that create two potential wells and thus the bistable phenomenon. It requires lower excitation to trigger bistable operation compared to conventional bistable structures. Based on previous research, this work focused on miniaturisation of the coupled bistable structure for energy harvesting application. The proposed bistable energy harvester is a combination of a Duffing's nonlinear structure and a linear assisting resonator. Experimental results show that the output spectrum of the miniature coupled bistable vibration energy harvester was the superposition of several spectra. It had a higher maximum output power and a much greater bandwidth compared to simply the Duffing's structure without the assisting resonator

  18. Bistability of Cavity Magnon Polaritons

    Science.gov (United States)

    Wang, Yi-Pu; Zhang, Guo-Qiang; Zhang, Dengke; Li, Tie-Fu; Hu, C.-M.; You, J. Q.

    2018-01-01

    We report the first observation of the magnon-polariton bistability in a cavity magnonics system consisting of cavity photons strongly interacting with the magnons in a small yttrium iron garnet (YIG) sphere. The bistable behaviors emerged as sharp frequency switchings of the cavity magnon polaritons (CMPs) and related to the transition between states with large and small numbers of polaritons. In our experiment, we align, respectively, the [100] and [110] crystallographic axes of the YIG sphere parallel to the static magnetic field and find very different bistable behaviors (e.g., clockwise and counter-clockwise hysteresis loops) in these two cases. The experimental results are well fitted and explained as being due to the Kerr nonlinearity with either a positive or negative coefficient. Moreover, when the magnetic field is tuned away from the anticrossing point of CMPs, we observe simultaneous bistability of both magnons and cavity photons by applying a drive field on the lower branch.

  19. Temporal nonlocality in bistable perception

    Science.gov (United States)

    Atmanspacher, Harald; Filk, Thomas

    2012-12-01

    A novel conceptual framework for theoretical psychology is presented and illustrated for the example of bistable perception. A basic formal feature of this framework is the non-commutativity of operations acting on mental states. A corresponding model for the bistable perception of ambiguous stimuli, the Necker-Zeno model, is sketched and some empirical evidence for it so far is described. It is discussed how a temporal nonlocality of mental states, predicted by the model, can be understood and tested.

  20. 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.

  1. Perceptual incongruence influences bistability and cortical activation

    NARCIS (Netherlands)

    Brouwer, G.J.; Tong, F.; Hagoort, P.; van Ee, R.

    2009-01-01

    We employed a parametric psychophysical design in combination with functional imaging to examine the influence of metric changes in perceptual incongruence on perceptual alternation rates and cortical responses. Subjects viewed a bistable stimulus defined by incongruent depth cues; bistability

  2. GABA shapes the dynamics of bistable perception

    NARCIS (Netherlands)

    van Loon, A.M.; Knapen, T.; Scholte, H.S.; St. John-Saaltink, E.; Donner, T.H.; Lamme, V.A.F.

    2013-01-01

    Sometimes, perception fluctuates spontaneously between two distinct interpretations of a constant sensory input. These bistable perceptual phenomena provide a unique window into the neural mechanisms that create the contents of conscious perception. Models of bistable perception posit that mutual

  3. Network-driven design principles for neuromorphic systems

    OpenAIRE

    Partzsch, Johannes; Sch?ffny, Rene

    2015-01-01

    Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures i...

  4. Optical bistability without the rotating wave approximation

    Energy Technology Data Exchange (ETDEWEB)

    Sharaby, Yasser A., E-mail: Yasser_Sharaby@hotmail.co [Physics Department, Faculty of Applied Sciences, Suez Canal University, Suez (Egypt); Joshi, Amitabh, E-mail: ajoshi@eiu.ed [Department of Physics, Eastern Illinois University, Charleston, IL 61920 (United States); Hassan, Shoukry S., E-mail: Shoukryhassan@hotmail.co [Mathematics Department, College of Science, University of Bahrain, P.O. Box 32038 (Bahrain)

    2010-04-26

    Optical bistability for two-level atomic system in a ring cavity is investigated outside the rotating wave approximation (RWA) using non-autonomous Maxwell-Bloch equations with Fourier decomposition up to first harmonic. The first harmonic output field component exhibits reversed or closed loop bistability simultaneously with the usual (anti-clockwise) bistability in the fundamental field component.

  5. Optical bistability without the rotating wave approximation

    International Nuclear Information System (INIS)

    Sharaby, Yasser A.; Joshi, Amitabh; Hassan, Shoukry S.

    2010-01-01

    Optical bistability for two-level atomic system in a ring cavity is investigated outside the rotating wave approximation (RWA) using non-autonomous Maxwell-Bloch equations with Fourier decomposition up to first harmonic. The first harmonic output field component exhibits reversed or closed loop bistability simultaneously with the usual (anti-clockwise) bistability in the fundamental field component.

  6. Fast-prototyping of VLSI

    International Nuclear Information System (INIS)

    Saucier, G.; Read, E.

    1987-01-01

    Fast-prototyping will be a reality in the very near future if both straightforward design methods and fast manufacturing facilities are available. This book focuses, first, on the motivation for fast-prototyping. Economic aspects and market considerations are analysed by European and Japanese companies. In the second chapter, new design methods are identified, mainly for full custom circuits. Of course, silicon compilers play a key role and the introduction of artificial intelligence techniques sheds a new light on the subject. At present, fast-prototyping on gate arrays or on standard cells is the most conventional technique and the third chapter updates the state-of-the art in this area. The fourth chapter concentrates specifically on the e-beam direct-writing for submicron IC technologies. In the fifth chapter, a strategic point in fast-prototyping, namely the test problem is addressed. The design for testability and the interface to the test equipment are mandatory to fulfill the test requirement for fast-prototyping. Finally, the last chapter deals with the subject of education when many people complain about the lack of use of fast-prototyping in higher education for VLSI

  7. Bistable microvalve and microcatheter system

    Science.gov (United States)

    Seward, Kirk Patrick

    2003-05-20

    A bistable microvalve of shape memory material is operatively connected to a microcatheter. The bistable microvalve includes a tip that can be closed off until it is in the desired position. Once it is in position it can opened and closed. The system uses heat and pressure to open and close the microvalve. The shape memory material will change stiffness and shape when heated above a transition temperature. The shape memory material is adapted to move from a first shape to a second shape, either open or closed, where it can perform a desired function.

  8. 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

  9. 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.

  10. Lithography requirements in complex VLSI device fabrication

    International Nuclear Information System (INIS)

    Wilson, A.D.

    1985-01-01

    Fabrication of complex very large scale integration (VLSI) circuits requires continual advances in lithography to satisfy: decreasing minimum linewidths, larger chip sizes, tighter linewidth and overlay control, increasing topography to linewidth ratios, higher yield demands, increased throughput, harsher device processing, lower lithography cost, and a larger part number set with quick turn-around time. Where optical, electron beam, x-ray, and ion beam lithography can be applied to judiciously satisfy the complex VLSI circuit fabrication requirements is discussed and those areas that are in need of major further advances are addressed. Emphasis will be placed on advanced electron beam and storage ring x-ray lithography

  11. 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.

  12. Nonvolatile Memory Materials for Neuromorphic Intelligent Machines.

    Science.gov (United States)

    Jeong, Doo Seok; Hwang, Cheol Seong

    2018-04-18

    Recent progress in deep learning extends the capability of artificial intelligence to various practical tasks, making the deep neural network (DNN) an extremely versatile hypothesis. While such DNN is virtually built on contemporary data centers of the von Neumann architecture, physical (in part) DNN of non-von Neumann architecture, also known as neuromorphic computing, can remarkably improve learning and inference efficiency. Particularly, resistance-based nonvolatile random access memory (NVRAM) highlights its handy and efficient application to the multiply-accumulate (MAC) operation in an analog manner. Here, an overview is given of the available types of resistance-based NVRAMs and their technological maturity from the material- and device-points of view. Examples within the strategy are subsequently addressed in comparison with their benchmarks (virtual DNN in deep learning). A spiking neural network (SNN) is another type of neural network that is more biologically plausible than the DNN. The successful incorporation of resistance-based NVRAM in SNN-based neuromorphic computing offers an efficient solution to the MAC operation and spike timing-based learning in nature. This strategy is exemplified from a material perspective. Intelligent machines are categorized according to their architecture and learning type. Also, the functionality and usefulness of NVRAM-based neuromorphic computing are addressed. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. 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.

  14. Bi-stable optical actuator

    Science.gov (United States)

    Holdener, Fred R.; Boyd, Robert D.

    2000-01-01

    The present invention is a bi-stable optical actuator device that is depowered in both stable positions. A bearing is used to transfer motion and smoothly transition from one state to another. The optical actuator device may be maintained in a stable position either by gravity or a restraining device.

  15. 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.

  16. A Knowledge Based Approach to VLSI CAD

    Science.gov (United States)

    1983-09-01

    Avail-and/or Dist ISpecial L| OI. SEICURITY CLASIIrCATION OP THIS IPA.lErllm S Daene." A KNOwLEDE BASED APPROACH TO VLSI CAD’ Louis L Steinberg and...major issues lies in building up and managing the knowledge base of oesign expertise. We expect that, as with many recent expert systems, in order to

  17. Electro-optic techniques for VLSI interconnect

    Science.gov (United States)

    Neff, J. A.

    1985-03-01

    A major limitation to achieving significant speed increases in very large scale integration (VLSI) lies in the metallic interconnects. They are costly not only from the charge transport standpoint but also from capacitive loading effects. The Defense Advanced Research Projects Agency, in pursuit of the fifth generation supercomputer, is investigating alternatives to the VLSI metallic interconnects, especially the use of optical techniques to transport the information either inter or intrachip. As the on chip performance of VLSI continues to improve via the scale down of the logic elements, the problems associated with transferring data off and onto the chip become more severe. The use of optical carriers to transfer the information within the computer is very appealing from several viewpoints. Besides the potential for gigabit propagation rates, the conversion from electronics to optics conveniently provides a decoupling of the various circuits from one another. Significant gains will also be realized in reducing cross talk between the metallic routings, and the interconnects need no longer be constrained to the plane of a thin film on the VLSI chip. In addition, optics can offer an increased programming flexibility for restructuring the interconnect network.

  18. 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...

  19. Bistability in a laser with injected signal

    International Nuclear Information System (INIS)

    Dorobantu, I.A.; Vlad, V.I.; Ursu, I.

    1987-04-01

    A unified description of bistability is given in free running lasers, optical bistable devices, ring lasers and lasers with an injected signal (LIS). A general review of laser instabilities is also presented in the frame of the theory of elementary catastrophes, emphasizing the apparence of higher order catastrophes in the case of a LIS suggesting thus a possibility to devise from first principles the whole hierarchy of laser instabilities. Experimental results on the bistability in the polarisation of LIS are also discussed. (authors)

  20. A broadband electromagnetic energy harvester with a coupled bistable structure

    International Nuclear Information System (INIS)

    Zhu, D; Beeby, S P

    2013-01-01

    This paper investigates a broadband electromagnetic energy harvester with a coupled bistable structure. Both analytical model and experimental results showed that the coupled bistable structure requires lower excitation force to trigger bistable operation than conventional bistable structures. A compact electromagnetic vibration energy harvester with a coupled bistable structure was implemented and tested. It was excited under white noise vibrations. Experimental results showed that the coupled bistable energy harvester can achieve bistable operation with lower excitation amplitude and generate more output power than both conventional bistable and linear energy harvesters under white noise excitation

  1. A bistable mechanism for directional sensing

    International Nuclear Information System (INIS)

    Beta, C; Amselem, G; Bodenschatz, E

    2008-01-01

    We present a generic mechanism for directional sensing in eukaryotic cells that is based on bistable dynamics. As the key feature of this modeling approach, the velocity of trigger waves in the bistable sensing system changes its sign across cells that are exposed to an external chemoattractant gradient. This is achieved by combining a two-component activator/inhibitor system with a bistable switch that induces an identical symmetry breaking for arbitrary gradient input signals. A simple kinetic example is designed to illustrate the dynamics of a bistable directional sensing mechanism in numerical simulations

  2. 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.

  3. Bistable diverter valve in microfluidics

    Czech Academy of Sciences Publication Activity Database

    Tesař, Václav; Bandulasena, H.C.H.

    2011-01-01

    Roč. 50, č. 5 (2011), s. 1225-1233 ISSN 0723-4864 R&D Projects: GA ČR GA101/07/1499; GA AV ČR IAA200760705 Institutional research plan: CEZ:AV0Z20760514 Keywords : fluidics * bistable diverter valves * pressure-driven microfluidics Subject RIV: BK - Fluid Dynamics Impact factor: 1.735, year: 2011 http://www.springerlink.com/content/x4907p1908151522/

  4. Brain networks underlying bistable perception.

    Science.gov (United States)

    Baker, Daniel H; Karapanagiotidis, Theodoros; Coggan, David D; Wailes-Newson, Kirstie; Smallwood, Jonathan

    2015-10-01

    Bistable stimuli, such as the Necker Cube, demonstrate that experience can change in the absence of changes in the environment. Such phenomena can be used to assess stimulus-independent aspects of conscious experience. The current study used resting state functional magnetic resonance imaging (rs-fMRI) to index stimulus-independent changes in neural activity to understand the neural architecture that determines dominance durations during bistable perception (using binocular rivalry and Necker cube stimuli). Anterior regions of the Superior Parietal Lobule (SPL) exhibited robust connectivity with regions of primary sensorimotor cortex. The strength of this region's connectivity with the striatum predicted shorter dominance durations during binocular rivalry, whereas its connectivity to pre-motor cortex predicted longer dominance durations for the Necker Cube. Posterior regions of the SPL, on the other hand, were coupled to associative cortex in the temporal and frontal lobes. The posterior SPL's connectivity to the temporal lobe predicted longer dominance during binocular rivalry. In conjunction with prior work, these data suggest that the anterior SPL contributes to perceptual rivalry through the inhibition of incongruent bottom up information, whereas the posterior SPL influences rivalry by supporting the current interpretation of a bistable stimulus. Our data suggests that the functional connectivity of the SPL with regions of sensory, motor, and associative cortex allows it to regulate the interpretation of the environment that forms the focus of conscious attention at a specific moment in time. Copyright © 2015. Published by Elsevier Inc.

  5. 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.

  6. An Analogue VLSI Implementation of the Meddis Inner Hair Cell Model

    Science.gov (United States)

    McEwan, Alistair; van Schaik, André

    2003-12-01

    The Meddis inner hair cell model is a widely accepted, but computationally intensive computer model of mammalian inner hair cell function. We have produced an analogue VLSI implementation of this model that operates in real time in the current domain by using translinear and log-domain circuits. The circuit has been fabricated on a chip and tested against the Meddis model for (a) rate level functions for onset and steady-state response, (b) recovery after masking, (c) additivity, (d) two-component adaptation, (e) phase locking, (f) recovery of spontaneous activity, and (g) computational efficiency. The advantage of this circuit, over other electronic inner hair cell models, is its nearly exact implementation of the Meddis model which can be tuned to behave similarly to the biological inner hair cell. This has important implications on our ability to simulate the auditory system in real time. Furthermore, the technique of mapping a mathematical model of first-order differential equations to a circuit of log-domain filters allows us to implement real-time neuromorphic signal processors for a host of models using the same approach.

  7. Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.

    Science.gov (United States)

    Yu, T; Sejnowski, T J; Cauwenberghs, G

    2011-10-01

    We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.

  8. An Analogue VLSI Implementation of the Meddis Inner Hair Cell Model

    Directory of Open Access Journals (Sweden)

    Alistair McEwan

    2003-06-01

    Full Text Available The Meddis inner hair cell model is a widely accepted, but computationally intensive computer model of mammalian inner hair cell function. We have produced an analogue VLSI implementation of this model that operates in real time in the current domain by using translinear and log-domain circuits. The circuit has been fabricated on a chip and tested against the Meddis model for (a rate level functions for onset and steady-state response, (b recovery after masking, (c additivity, (d two-component adaptation, (e phase locking, (f recovery of spontaneous activity, and (g computational efficiency. The advantage of this circuit, over other electronic inner hair cell models, is its nearly exact implementation of the Meddis model which can be tuned to behave similarly to the biological inner hair cell. This has important implications on our ability to simulate the auditory system in real time. Furthermore, the technique of mapping a mathematical model of first-order differential equations to a circuit of log-domain filters allows us to implement real-time neuromorphic signal processors for a host of models using the same approach.

  9. Biophysical synaptic dynamics in an analog VLSI network of Hodgkin-Huxley neurons.

    Science.gov (United States)

    Yu, Theodore; Cauwenberghs, Gert

    2009-01-01

    We study synaptic dynamics in a biophysical network of four coupled spiking neurons implemented in an analog VLSI silicon microchip. The four neurons implement a generalized Hodgkin-Huxley model with individually configurable rate-based kinetics of opening and closing of Na+ and K+ ion channels. The twelve synapses implement a rate-based first-order kinetic model of neurotransmitter and receptor dynamics, accounting for NMDA and non-NMDA type chemical synapses. The implemented models on the chip are fully configurable by 384 parameters accounting for conductances, reversal potentials, and pre/post-synaptic voltage-dependence of the channel kinetics. We describe the models and present experimental results from the chip characterizing single neuron dynamics, single synapse dynamics, and multi-neuron network dynamics showing phase-locking behavior as a function of synaptic coupling strength. The 3mm x 3mm microchip consumes 1.29 mW power making it promising for applications including neuromorphic modeling and neural prostheses.

  10. 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...

  11. 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.

  12. Parallel computation of nondeterministic algorithms in VLSI

    Energy Technology Data Exchange (ETDEWEB)

    Hortensius, P D

    1987-01-01

    This work examines parallel VLSI implementations of nondeterministic algorithms. It is demonstrated that conventional pseudorandom number generators are unsuitable for highly parallel applications. Efficient parallel pseudorandom sequence generation can be accomplished using certain classes of elementary one-dimensional cellular automata. The pseudorandom numbers appear in parallel on each clock cycle. Extensive study of the properties of these new pseudorandom number generators is made using standard empirical random number tests, cycle length tests, and implementation considerations. Furthermore, it is shown these particular cellular automata can form the basis of efficient VLSI architectures for computations involved in the Monte Carlo simulation of both the percolation and Ising models from statistical mechanics. Finally, a variation on a Built-In Self-Test technique based upon cellular automata is presented. These Cellular Automata-Logic-Block-Observation (CALBO) circuits improve upon conventional design for testability circuitry.

  13. Heavy ion tests on programmable VLSI

    International Nuclear Information System (INIS)

    Provost-Grellier, A.

    1989-11-01

    The radiation from space environment induces operation damages in onboard computers systems. The definition of a strategy, for the Very Large Scale Integrated Circuitry (VLSI) qualification and choice, is needed. The 'upset' phenomena is known to be the most critical integrated circuit radiation effect. The strategies for testing integrated circuits are reviewed. A method and a test device were developed and applied to space applications candidate circuits. Cyclotron, synchrotron and Californium source experiments were carried out [fr

  14. Applications of VLSI circuits to medical imaging

    International Nuclear Information System (INIS)

    O'Donnell, M.

    1988-01-01

    In this paper the application of advanced VLSI circuits to medical imaging is explored. The relationship of both general purpose signal processing chips and custom devices to medical imaging is discussed using examples of fabricated chips. In addition, advanced CAD tools for silicon compilation are presented. Devices built with these tools represent a possible alternative to custom devices and general purpose signal processors for the next generation of medical imaging systems

  15. Neuromorphic computing with nanoscale spintronic oscillators.

    Science.gov (United States)

    Torrejon, Jacob; Riou, Mathieu; Araujo, Flavio Abreu; Tsunegi, Sumito; Khalsa, Guru; Querlioz, Damien; Bortolotti, Paolo; Cros, Vincent; Yakushiji, Kay; Fukushima, Akio; Kubota, Hitoshi; Yuasa, Shinji; Stiles, Mark D; Grollier, Julie

    2017-07-26

    Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 10 8 oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals and several candidates, including memristive and superconducting oscillators, a proof of concept of neuromorphic computing using nanoscale oscillators has yet to be demonstrated. Here we show experimentally that a nanoscale spintronic oscillator (a magnetic tunnel junction) can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators.

  16. Serendipitous Offline Learning in a Neuromorphic Robot

    Directory of Open Access Journals (Sweden)

    Terrence C Stewart

    2016-02-01

    Full Text Available We demonstrate a hybrid neuromorphic learning paradigm that learns complex sensorimotor mappings based on a small set of hard-coded reflex behaviours. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviours. 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 he 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 behaviour.

  17. A novel bistable energy harvesting concept

    International Nuclear Information System (INIS)

    Scarselli, G; Nicassio, F; Pinto, F; Ciampa, F; Iervolino, O; Meo, M

    2016-01-01

    Bistable energy harvesting has become a major field of research due to some unique features for converting mechanical energy into electrical power. When properly loaded, bistable structures snap-through from one stable configuration to another, causing large strains and consequently power generation. Moreover, bistable structures can harvest energy across a broad-frequency bandwidth due to their nonlinear characteristics. Despite the fact that snap-through may be triggered regardless of the form or frequency of exciting vibration, the external force must reach a specific snap-through activation threshold value to trigger the transition from one stable state to another. This aspect is a limiting factor for realistic vibration energy harvesting application with bistable devices. This paper presents a novel power harvesting concept for bistable composites based on a ‘lever effect’ aimed at minimising the activation force to cause the snap through by choosing properly the bistable structures’ constraints. The concept was demonstrated with the help of numerical simulation and experimental testing. The results showed that the actuation force is one order of magnitude smaller (3%–6%) than the activation force of conventionally constrained bistable devices. In addition, it was shown that the output voltage was higher than the conventional configuration, leading to a significant increase in power generation. This novel concept could lead to a new generation of more efficient bistable energy harvesters for realistic vibration environments. (paper)

  18. Diversity and functional properties of bistable pigments.

    Science.gov (United States)

    Tsukamoto, Hisao; Terakita, Akihisa

    2010-11-01

    Rhodopsin and related opsin-based pigments, which are photosensitive membrane proteins, have been extensively studied using a wide variety of techniques, with rhodopsin being the most understood G protein-coupled receptor (GPCR). Animals use various opsin-based pigments for vision and a wide variety of non-visual functions. Many functionally varied pigments are roughly divided into two kinds, based on their photoreaction: bistable and monostable pigments. Bistable pigments are thermally stable before and after photo-activation, but monostable pigments are stable only before activation. Here, we review the diversity of bistable pigments and their molecular characteristics. We also discuss the mechanisms underlying different molecular characteristics of bistable and monostable pigments. In addition, the potential of bistable pigments as a GPCR model is proposed.

  19. Neuromorphic Modeling of Moving Target Detection in Insects

    Science.gov (United States)

    2007-12-31

    Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39, 18 Grants FA9550-04-1-0283 and FA9550-04-1-0294 Neuromorphic Modeling of Moving Target Detection...natural for neuromorphic sensory processing. We developed visual motion detection circuitry, including photodetectors, early vision, and models for both...Lincoln Labs 3DM2 run, Tanner Research reserved and utilized space corresponding to two MOSIS ’tiny chips ’ (2mm square each), each with three interconnected

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

    OpenAIRE

    Romeira, B.; Figueiredo, J. M. L.; Javaloyes, J.

    2017-01-01

    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 ...

  1. A broadband electromagnetic energy harvester with a coupled bistable structure

    OpenAIRE

    Zhu, Dibin; Beeby, Steve

    2013-01-01

    This paper investigates a broadband electromagnetic energy harvester with a coupled bistable structure. Both analytical model and experimental results showed that the coupled bistable structure requires lower excitation force to trigger bistable operation than conventional bistable structures. A compact electromagnetic vibration energy harvester with a coupled bistable structure was implemented and tested. It was excited under white noise vibrations. Experimental results showed that the coupl...

  2. Transcriptional delay stabilizes bistable gene networks.

    Science.gov (United States)

    Gupta, Chinmaya; López, José Manuel; Ott, William; Josić, Krešimir; Bennett, Matthew R

    2013-08-02

    Transcriptional delay can significantly impact the dynamics of gene networks. Here we examine how such delay affects bistable systems. We investigate several stochastic models of bistable gene networks and find that increasing delay dramatically increases the mean residence times near stable states. To explain this, we introduce a non-Markovian, analytically tractable reduced model. The model shows that stabilization is the consequence of an increased number of failed transitions between stable states. Each of the bistable systems that we simulate behaves in this manner.

  3. 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

  4. Wavelength-encoded OCDMA system using opto-VLSI processors.

    Science.gov (United States)

    Aljada, Muhsen; Alameh, Kamal

    2007-07-01

    We propose and experimentally demonstrate a 2.5 Gbits/sper user wavelength-encoded optical code-division multiple-access encoder-decoder structure based on opto-VLSI processing. Each encoder and decoder is constructed using a single 1D opto-very-large-scale-integrated (VLSI) processor in conjunction with a fiber Bragg grating (FBG) array of different Bragg wavelengths. The FBG array spectrally and temporally slices the broadband input pulse into several components and the opto-VLSI processor generates codewords using digital phase holograms. System performance is measured in terms of the autocorrelation and cross-correlation functions as well as the eye diagram.

  5. Wavelength-encoded OCDMA system using opto-VLSI processors

    Science.gov (United States)

    Aljada, Muhsen; Alameh, Kamal

    2007-07-01

    We propose and experimentally demonstrate a 2.5 Gbits/sper user wavelength-encoded optical code-division multiple-access encoder-decoder structure based on opto-VLSI processing. Each encoder and decoder is constructed using a single 1D opto-very-large-scale-integrated (VLSI) processor in conjunction with a fiber Bragg grating (FBG) array of different Bragg wavelengths. The FBG array spectrally and temporally slices the broadband input pulse into several components and the opto-VLSI processor generates codewords using digital phase holograms. System performance is measured in terms of the autocorrelation and cross-correlation functions as well as the eye diagram.

  6. Possible hysteresis loops of resonatorless optical bistability

    International Nuclear Information System (INIS)

    Nguyen Ba An; Le Thi Cat Tuong.

    1990-05-01

    We qualitatively show that hysteresis loops of intrinsic optical bistability phenomena without any additional feedback may be of various shapes including those of a butterfly and a three-winged bow. (author). 15 refs, 4 figs

  7. Space charge effects and electronic bistability

    International Nuclear Information System (INIS)

    Ruffini, A.; Strumia, F.; Tommasi, O.

    1996-01-01

    The excitation of metastable states in an atomic beam apparatus by means of electron collision is a widespread technique. The authors have observed a large bistable behaviour in apparatus designed to provide an intense and collimated beam of metastable helium by excitation with orthogonally impinging electrons. This bistable behaviour largely affects the efficiency of the apparatus and is therefore worth of being carefully investigated. The apparatus has an electrode configuration equivalent to that of a tetrode valve with large intergrid distances. The bistability consists in a hysteresis cycle in the curve of the anode current vs. grid voltage. Experimental measurements, supported by a simple theoretical model and by numerical simulation, stress out the crucial role played by space charge effects for the onset of bistability. A comparison with previous observations of this phenomenon is given. Spontaneous current oscillations with various shapes have been recorded in one of the two curves of the hysteresis cycle

  8. Bistable fluidic valve is electrically switched

    Science.gov (United States)

    Fiet, O.; Salvinski, R. J.

    1970-01-01

    Bistable control valve is selectively switched by direct application of an electrical field to divert fluid from one output channel to another. Valve is inexpensive, has no moving parts, and operates on fluids which are relatively poor electrical conductors.

  9. Origami Mechanics: Bistability and Isometries

    Science.gov (United States)

    Adda-Bedia, Mokhtar; Lechenault, Frederic; Morphogenesis; multiscale phenomena Team

    2015-03-01

    Origami structures are usually seen as assemblies of rigid faces articulated around creases with hinge-like behaviour. Their deployment and degrees of freedom are purely kinematic, resulting only from the geometry of the crease network. However, in real folded structures, the base material can deform outside the creases. In such situations, face bending competes with crease actuation in a morphogenetic way. In order to rationalise this interplay, we investigate the mechanical behaviour of an infinite sheet on which one or more straight creases meet at a single vertex. We find that these structures generically exhibit bistability, in the sense that they can snap through from one metastable configuration to another. Furthermore, we uncover a new class of isometry of the plane, which corresponds to metastable states of a creased sheet for which the hoop stress vanishes, an instability mechanism that is also responsible for the wrinkling of thin plates.

  10. Network-driven design principles for neuromorphic systems

    Directory of Open Access Journals (Sweden)

    Johannes ePartzsch

    2015-10-01

    Full Text Available Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures in emulating certain connectivity models. Furthermore, we show step-by-step how to derive a neuromorphic architecture from a given connectivity model. For this, we introduce a generalized description for architectures with a synapse matrix, which takes into account shared use of circuit components for reducing total silicon area. Architectures designed with this approach are fitted to a connectivity model, essentially adapting to its connection density. They are guaranteeing faithful reproduction of the model on chip, while requiring less total silicon area. In total, our methods allow designers to implement more area-efficient neuromorphic systems and verify usability of the connectivity resources in these systems.

  11. Network-driven design principles for neuromorphic systems.

    Science.gov (United States)

    Partzsch, Johannes; Schüffny, Rene

    2015-01-01

    Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures in emulating certain connectivity models. Furthermore, we show step-by-step how to derive a neuromorphic architecture from a given connectivity model. For this, we introduce a generalized description for architectures with a synapse matrix, which takes into account shared use of circuit components for reducing total silicon area. Architectures designed with this approach are fitted to a connectivity model, essentially adapting to its connection density. They are guaranteeing faithful reproduction of the model on chip, while requiring less total silicon area. In total, our methods allow designers to implement more area-efficient neuromorphic systems and verify usability of the connectivity resources in these systems.

  12. GABA shapes the dynamics of bistable perception.

    Science.gov (United States)

    van Loon, Anouk M; Knapen, Tomas; Scholte, H Steven; St John-Saaltink, Elexa; Donner, Tobias H; Lamme, Victor A F

    2013-05-06

    Sometimes, perception fluctuates spontaneously between two distinct interpretations of a constant sensory input. These bistable perceptual phenomena provide a unique window into the neural mechanisms that create the contents of conscious perception. Models of bistable perception posit that mutual inhibition between stimulus-selective neural populations in visual cortex plays a key role in these spontaneous perceptual fluctuations. However, a direct link between neural inhibition and bistable perception has not yet been established experimentally. Here, we link perceptual dynamics in three distinct bistable visual illusions (binocular rivalry, motion-induced blindness, and structure from motion) to measurements of gamma-aminobutyric acid (GABA) concentrations in human visual cortex (as measured with magnetic resonance spectroscopy) and to pharmacological stimulation of the GABAA receptor by means of lorazepam. As predicted by a model of neural interactions underlying bistability, both higher GABA concentrations in visual cortex and lorazepam administration induced slower perceptual dynamics, as reflected in a reduced number of perceptual switches and a lengthening of percept durations. Thus, we show that GABA, the main inhibitory neurotransmitter, shapes the dynamics of bistable perception. These results pave the way for future studies into the competitive neural interactions across the visual cortical hierarchy that elicit conscious perception. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Neuromorphic vision sensors and preprocessors in system applications

    Science.gov (United States)

    Kramer, Joerg; Indiveri, Giacomo

    1998-09-01

    A partial review of neuromorphic vision sensors that are suitable for use in autonomous systems is presented. Interfaces are being developed to multiplex the high- dimensional output signals of arrays of such sensors and to communicate them in standard formats to off-chip devices for higher-level processing, actuation, storage and display. Alternatively, on-chip processing stages may be implemented to extract sparse image parameters, thereby obviating the need for multiplexing. Autonomous robots are used to test neuromorphic vision chips in real-world environments and to explore the possibilities of data fusion from different sensing modalities. Examples of autonomous mobile systems that use neuromorphic vision chips for line tracking and optical flow matching are described.

  14. Finding a Roadmap to achieve Large Neuromorphic Hardware Systems

    Directory of Open Access Journals (Sweden)

    Jennifer eHasler

    2013-09-01

    Full Text Available Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techniques are meeting hard physical limits. These silicon systems mimic extremely energy efficient neural computing structures, potentially both for solving engineering applications as well as understanding neural computation. Towards this end, the authors provide a glimpse at what the technology evolution roadmap looks like for these systems so that Neuromorphic engineers may gain the same benefit of anticipation and foresight that IC designers gained from Moore's law many years ago. Scaling of energy efficiency, performance, and size will be discussed as well as how the implementation and application space of Neuromorphic systems are expected to evolve over time.

  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. 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 ...

  18. 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.

  19. Synthesis algorithm of VLSI multipliers for ASIC

    Science.gov (United States)

    Chua, O. H.; Eldin, A. G.

    1993-01-01

    Multipliers are critical sub-blocks in ASIC design, especially for digital signal processing and communications applications. A flexible multiplier synthesis tool is developed which is capable of generating multiplier blocks for word size in the range of 4 to 256 bits. A comparison of existing multiplier algorithms is made in terms of speed, silicon area, and suitability for automated synthesis and verification of its VLSI implementation. The algorithm divides the range of supported word sizes into sub-ranges and provides each sub-range with a specific multiplier architecture for optimal speed and area. The algorithm of the synthesis tool and the multiplier architectures are presented. Circuit implementation and the automated synthesis methodology are discussed.

  20. 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...

  1. DPL/Daedalus design environment (for VLSI)

    Energy Technology Data Exchange (ETDEWEB)

    Batali, J; Mayle, N; Shrobe, H; Sussman, G; Weise, D

    1981-01-01

    The DPL/Daedalus design environment is an interactive VLSI design system implemented at the MIT Artificial Intelligence Laboratory. The system consists of several components: a layout language called DPL (for design procedure language); an interactive graphics facility (Daedalus); and several special purpose design procedures for constructing complex artifacts such as PLAs and microprocessor data paths. Coordinating all of these is a generalized property list data base which contains both the data representing circuits and the procedures for constructing them. The authors first review the nature of the data base and then turn to DPL and Daedalus, the two most common ways of entering information into the data base. The next two sections review the specialized procedures for constructing PLAs and data paths; the final section describes a tool for hierarchical node extraction. 5 references.

  2. PLA realizations for VLSI state machines

    Science.gov (United States)

    Gopalakrishnan, S.; Whitaker, S.; Maki, G.; Liu, K.

    1990-01-01

    A major problem associated with state assignment procedures for VLSI controllers is obtaining an assignment that produces minimal or near minimal logic. The key item in Programmable Logic Array (PLA) area minimization is the number of unique product terms required by the design equations. This paper presents a state assignment algorithm for minimizing the number of product terms required to implement a finite state machine using a PLA. Partition algebra with predecessor state information is used to derive a near optimal state assignment. A maximum bound on the number of product terms required can be obtained by inspecting the predecessor state information. The state assignment algorithm presented is much simpler than existing procedures and leads to the same number of product terms or less. An area-efficient PLA structure implemented in a 1.0 micron CMOS process is presented along with a summary of the performance for a controller implemented using this design procedure.

  3. Development methods for VLSI-processors

    International Nuclear Information System (INIS)

    Horninger, K.; Sandweg, G.

    1982-01-01

    The aim of this project, which was originally planed for 3 years, was the development of modern system and circuit concepts, for VLSI-processors having a 32 bit wide data path. The result of this first years work is the concept of a general purpose processor. This processor is not only logically but also physically (on the chip) divided into four functional units: a microprogrammable instruction unit, an execution unit in slice technique, a fully associative cache memory and an I/O unit. For the ALU of the execution unit circuits in PLA and slice techniques have been realized. On the basis of regularity, area consumption and achievable performance the slice technique has been prefered. The designs utilize selftesting circuitry. (orig.) [de

  4. 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.

  5. VLSI Design of Trusted Virtual Sensors.

    Science.gov (United States)

    Martínez-Rodríguez, Macarena C; Prada-Delgado, Miguel A; Brox, Piedad; Baturone, Iluminada

    2018-01-25

    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).

  6. Hybrid optoelectronic device with multiple bistable outputs

    Energy Technology Data Exchange (ETDEWEB)

    Costazo-Caso, Pablo A; Jin Yiye; Gelh, Michael; Granieri, Sergio; Siahmakoun, Azad, E-mail: pcostanzo@ing.unlp.edu.are, E-mail: granieri@rose-hulma.edu, E-mail: siahmako@rose-hulma.edu [Department of Physics and Optical Engineering, Rose-Hulman Institute of Technology, 5500 Wabash Avenue, Terre Haute, IN 47803 (United States)

    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.

  7. Bubbling and bistability in two parameter discrete systems

    Indian Academy of Sciences (India)

    The birth of X *. · is concurrent with the ... for bistability viz. a½, and the higher order bistability points a¾, etc. are marked. The quadrilateral marked as ... The characteristics of 2 parameter 1-d maps that exhibit bubbling/bistability related to their ...

  8. 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.

  9. All-memristive neuromorphic computing with level-tuned neurons

    Science.gov (United States)

    Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

    2016-09-01

    In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

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

    Science.gov (United States)

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

    2017-12-01

    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.

  11. All-memristive neuromorphic computing with level-tuned neurons.

    Science.gov (United States)

    Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

    2016-09-02

    In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

  12. Perceptual incongruence influences bistability and cortical activation.

    Directory of Open Access Journals (Sweden)

    Gijs Joost Brouwer

    Full Text Available We employed a parametric psychophysical design in combination with functional imaging to examine the influence of metric changes in perceptual incongruence on perceptual alternation rates and cortical responses. Subjects viewed a bistable stimulus defined by incongruent depth cues; bistability resulted from incongruence between binocular disparity and monocular perspective cues that specify different slants (slant rivalry. Psychophysical results revealed that perceptual alternation rates were positively correlated with the degree of perceived incongruence. Functional imaging revealed systematic increases in activity that paralleled the psychophysical results within anterior intraparietal sulcus, prior to the onset of perceptual alternations. We suggest that this cortical activity predicts the frequency of subsequent alternations, implying a putative causal role for these areas in initiating bistable perception. In contrast, areas implicated in form and depth processing (LOC and V3A were sensitive to the degree of slant, but failed to show increases in activity when these cues were in conflict.

  13. Longitudinal magnetic bistability of electroplated wires

    International Nuclear Information System (INIS)

    Kurlyandskaya, G.V.; Garcia-Miquel, H.; Vazquez, M.; Svalov, A.V.; Vas'kovskiy, V.O.

    2002-01-01

    Fe 20 Ni 74 Co 6 and Fe 20 Ni 64 Co 16 1 μm thick magnetic tubes electroplated onto Cu 98 Be 2 conductive wire have been investigated in as-deposited state, after heat treatment under longitudinal magnetic field for 1 h at 330 deg. C, and after rf-sputtering deposition of the additional 2 μm Fe 19 Ni 81 layer. Heat treatments and an additional layer deposition modify the shape of hysteresis loops. Magnetically bistable behaviour, observed after the field annealing at a temperature of 330 deg. C, is studied as a function of the length of the samples. This is the first report by our knowledge on the bistable behaviour of the electroplated wires. The bistability of these wires is promising for applications such as tagging or pulse generator applications

  14. Balancing bistable perception during self-motion.

    Science.gov (United States)

    van Elk, Michiel; Blanke, Olaf

    2012-10-01

    In two experiments we investigated whether bistable visual perception is influenced by passive own body displacements due to vestibular stimulation. For this we passively rotated our participants around the vertical (yaw) axis while observing different rotating bistable stimuli (bodily or non-bodily) with different ambiguous motion directions. Based on previous work on multimodal effects on bistable perception, we hypothesized that vestibular stimulation should alter bistable perception and that the effects should differ for bodily versus non-bodily stimuli. In the first experiment, it was found that the rotation bias (i.e., the difference between the percentage of time that a CW or CCW rotation was perceived) was selectively modulated by vestibular stimulation: the perceived duration of the bodily stimuli was longer for the rotation direction congruent with the subject's own body rotation, whereas the opposite was true for the non-bodily stimulus (Necker cube). The results found in the second experiment extend the findings from the first experiment and show that these vestibular effects on bistable perception only occur when the axis of rotation of the bodily stimulus matches the axis of passive own body rotation. These findings indicate that the effect of vestibular stimulation on the rotation bias depends on the stimulus that is presented and the rotation axis of the stimulus. Although most studies on vestibular processing have traditionally focused on multisensory signal integration for posture, balance, and heading direction, the present data show that vestibular self-motion influences the perception of bistable bodily stimuli revealing the importance of vestibular mechanisms for visual consciousness.

  15. 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.

  16. Bistable Microvalve For Use With Microcatheter System

    Science.gov (United States)

    Seward, Kirk Patrick

    2003-12-16

    A bistable microvalve of shape memory material is operatively connected to a microcatheter. The bistable microvalve includes a tip that can be closed off until it is in the desired position. Once it is in position it can be opened and closed. The system uses heat and pressure to open and close the microvalve. The shape memory material will change stiffness and shape when heated above a transition temperature. The shape memory material is adapted to move from a first shape to a second shape, either open or closed, where it can perform a desired function.

  17. Unidirectional Transition Waves in Bistable Lattices.

    Science.gov (United States)

    Nadkarni, Neel; Arrieta, Andres F; Chong, Christopher; Kochmann, Dennis M; Daraio, Chiara

    2016-06-17

    We present a model system for strongly nonlinear transition waves generated in a periodic lattice of bistable members connected by magnetic links. The asymmetry of the on-site energy wells created by the bistable members produces a mechanical diode that supports only unidirectional transition wave propagation with constant wave velocity. We theoretically justify the cause of the unidirectionality of the transition wave and confirm these predictions by experiments and simulations. We further identify how the wave velocity and profile are uniquely linked to the double-well energy landscape, which serves as a blueprint for transition wave control.

  18. 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.

  19. Bistable firing properties of soleus motor units in unrestrained rats

    DEFF Research Database (Denmark)

    EKEN, T.; KIEHN, O.

    1989-01-01

    of the motoneuron pool by stimulation of la afferents, or inhibition by stimulation of skin afferents. The shifts were not related to gross limb movements. This phenomenon is referred to as a bistable firing pattern. Bistable firing also occurred spontaneously during quiet standing. Typically the firing frequency...... was unchanged or only phasically influenced. These results demonstrate for the first time a bistable firing pattern during postural activity in the intact animal. The firing pattern closely resembles the bistable behaviour described in spinal motoneurons in reduced preparations, where it is due to the presence...... of a plateau potential. This suggests that the bistable firing is unexplained by plateau potentials also in the intact animal....

  20. 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.

  1. Memristor-Based Synapse Design and Training Scheme for Neuromorphic Computing Architecture

    Science.gov (United States)

    2012-06-01

    system level built upon the conventional Von Neumann computer architecture [2][3]. Developing the neuromorphic architecture at chip level by...SCHEME FOR NEUROMORPHIC COMPUTING ARCHITECTURE 5a. CONTRACT NUMBER FA8750-11-2-0046 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62788F 6...creation of memristor-based neuromorphic computing architecture. Rather than the existing crossbar-based neuron network designs, we focus on memristor

  2. 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.

  3. An electron undulating ring for VLSI lithography

    International Nuclear Information System (INIS)

    Tomimasu, T.; Mikado, T.; Noguchi, T.; Sugiyama, S.; Yamazaki, T.

    1985-01-01

    The development of the ETL storage ring ''TERAS'' as an undulating ring has been continued to achieve a wide area exposure of synchrotron radiation (SR) in VLSI lithography. Stable vertical and horizontal undulating motions of stored beams are demonstrated around a horizontal design orbit of TERAS, using two small steering magnets of which one is used for vertical undulating and another for horizontal one. Each steering magnet is inserted into one of the periodic configulation of guide field elements. As one of useful applications of undulaing electron beams, a vertically wide exposure of SR has been demonstrated in the SR lithography. The maximum vertical deviation from the design orbit nCcurs near the steering magnet. The maximum vertical tilt angle of the undulating beam near the nodes is about + or - 2mrad for a steering magnetic field of 50 gauss. Another proposal is for hith-intensity, uniform and wide exposure of SR from a wiggler installed in TERAS, using vertical and horizontal undulating motions of stored beams. A 1.4 m long permanent magnet wiggler has been installed for this purpose in this April

  4. Convolving optically addressed VLSI liquid crystal SLM

    Science.gov (United States)

    Jared, David A.; Stirk, Charles W.

    1994-03-01

    We designed, fabricated, and tested an optically addressed spatial light modulator (SLM) that performs a 3 X 3 kernel image convolution using ferroelectric liquid crystal on VLSI technology. The chip contains a 16 X 16 array of current-mirror-based convolvers with a fixed kernel for finding edges. The pixels are located on 75 micron centers, and the modulators are 20 microns on a side. The array successfully enhanced edges in illumination patterns. We developed a high-level simulation tool (CON) for analyzing the performance of convolving SLM designs. CON has a graphical interface and simulates SLM functions using SPICE-like device models. The user specifies the pixel function along with the device parameters and nonuniformities. We discovered through analysis, simulation and experiment that the operation of current-mirror-based convolver pixels is degraded at low light levels by the variation of transistor threshold voltages inherent to CMOS chips. To function acceptable, the test SLM required the input image to have an minimum irradiance of 10 (mu) W/cm2. The minimum required irradiance can be further reduced by adding a photodarlington near the photodetector or by increasing the size of the transistors used to calculate the convolution.

  5. Metastable and bistable defects in silicon

    International Nuclear Information System (INIS)

    Mukashev, Bulat N; Abdullin, Kh A; Gorelkinskii, Yurii V

    2000-01-01

    Existing data on the properties and structure of metastable and bistable defects in silicon are analyzed. Primary radiation-induced defects (vacancies, self-interstitial atoms, and Frenkel pairs), complexes of oxygen, carbon, hydrogen, and other impurity atoms and defects with negative correlation energy are considered. (reviews of topical problems)

  6. 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.

  7. A CW Gunn diode bistable switching element.

    Science.gov (United States)

    Hurtado, M.; Rosenbaum, F. J.

    1972-01-01

    Experiments with a current-controlled bistable switching element using a CW Gunn diode are reported. Switching rates of the order of 10 MHz have been obtained. Switching is initiated by current pulses of short duration (5-10 ns). Rise times of the order of several nanoseconds could be obtained.

  8. A bistable model of cell polarity.

    Directory of Open Access Journals (Sweden)

    Matteo Semplice

    Full Text Available Ultrasensitivity, as described by Goldbeter and Koshland, has been considered for a long time as a way to realize bistable switches in biological systems. It is not as well recognized that when ultrasensitivity and reinforcing feedback loops are present in a spatially distributed system such as the cell plasmamembrane, they may induce bistability and spatial separation of the system into distinct signaling phases. Here we suggest that bistability of ultrasensitive signaling pathways in a diffusive environment provides a basic mechanism to realize cell membrane polarity. Cell membrane polarization is a fundamental process implicated in several basic biological phenomena, such as differentiation, proliferation, migration and morphogenesis of unicellular and multicellular organisms. We describe a simple, solvable model of cell membrane polarization based on the coupling of membrane diffusion with bistable enzymatic dynamics. The model can reproduce a broad range of symmetry-breaking events, such as those observed in eukaryotic directional sensing, the apico-basal polarization of epithelium cells, the polarization of budding and mating yeast, and the formation of Ras nanoclusters in several cell types.

  9. Multi-valued LSI/VLSI logic design

    Science.gov (United States)

    Santrakul, K.

    A procedure for synthesizing any large complex logic system, such as LSI and VLSI integrated circuits is described. This scheme uses Multi-Valued Multi-plexers (MVMUX) as the basic building blocks and the tree as the structure of the circuit realization. Simple built-in test circuits included in the network (the main current), provide a thorough functional checking of the network at any time. In brief, four major contributions are made: (1) multi-valued Algorithmic State Machine (ASM) chart for describing an LSI/VLSI behavior; (2) a tree-structured multi-valued multiplexer network which can be obtained directly from an ASM chart; (3) a heuristic tree-structured synthesis method for realizing any combinational logic with minimal or nearly-minimal MVMUX; and (4) a hierarchical design of LSI/VLSI with built-in parallel testing capability.

  10. Triggered Snap-Through of Bistable Shells

    Science.gov (United States)

    Cai, Yijie; Huang, Shicheng; Trase, Ian; Hu, Nan; Chen, Zi

    Elastic bistable shells are common structures in nature and engineering, such as the lobes of the Venus flytrap or the surface of a toy jumping poppers. Despite their ubiquity, the parameters that control the bistability of such structures are not well understood. In this study, we explore how the geometrical features of radially symmetric elastic shells affect the shape and potential energy of a shell's stable states, and how to tune certain parameters in order to generate a snap-through transition from a convex semi-stable state to concave stable state. We fabricated a series of elastic shells with varying geometric parameters out of silicone rubber and measured the resulting potential energy in the semi-stable state. Finite element simulations were also conducted in order to determine the deformation and stress in the shells during snap-through. It was found that the energy of the semi-stable state is controlled by only two geometric parameters and a dimensionless ratio. We also noted two distinct transitions during snap-through, one between monostability and semi-bistability (the state a popper toy is in before it snaps-through and jumps), and a second transition between semi-bistability and true bistability. This work shows that it is possible to use a set of simple parameters to tailor the energy landscape of an elastic shell in order to generate complex trigger motions for their potential use in smart applications. Z.C. acknowledge support from Society in Science-Branco Weiss Fellowship, administered by ETH Zurich.

  11. NASA Space Engineering Research Center for VLSI systems design

    Science.gov (United States)

    1991-01-01

    This annual review reports the center's activities and findings on very large scale integration (VLSI) systems design for 1990, including project status, financial support, publications, the NASA Space Engineering Research Center (SERC) Symposium on VLSI Design, research results, and outreach programs. Processor chips completed or under development are listed. Research results summarized include a design technique to harden complementary metal oxide semiconductors (CMOS) memory circuits against single event upset (SEU); improved circuit design procedures; and advances in computer aided design (CAD), communications, computer architectures, and reliability design. Also described is a high school teacher program that exposes teachers to the fundamentals of digital logic design.

  12. 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.

  13. 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

  14. Neuromorphic photonic networks using silicon photonic weight banks.

    Science.gov (United States)

    Tait, Alexander N; de Lima, Thomas Ferreira; Zhou, Ellen; Wu, Allie X; Nahmias, Mitchell A; Shastri, Bhavin J; Prucnal, Paul R

    2017-08-07

    Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate processing functions that vastly exceed the capabilities of electronics. We report first observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks. A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis. Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using "neural compiler" to solve a differential system emulation task. A 294-fold acceleration against a conventional benchmark is predicted. We also propose and derive power consumption analysis for modulator-class neurons that, as opposed to laser-class neurons, are compatible with silicon photonic platforms. At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.

  15. Flexible Sensory Platform Based on Oxide-based Neuromorphic Transistors.

    Science.gov (United States)

    Liu, Ning; Zhu, Li Qiang; Feng, Ping; Wan, Chang Jin; Liu, Yang Hui; Shi, Yi; Wan, Qing

    2015-12-11

    Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuromorphic transistors with multiple input gates are fabricated on flexible plastic substrates for pH sensor applications. When such device is operated in a quasi-static dual-gate synergic sensing mode, it shows a high pH sensitivity of ~105 mV/pH. Our results also demonstrate that single-spike dynamic mode can remarkably improve pH sensitivity and reduce response/recover time and power consumption. Moreover, we find that an appropriate negative bias applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuromorphic transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption.

  16. Six networks on a universal neuromorphic computing substrate

    Directory of Open Access Journals (Sweden)

    Thomas ePfeil

    2013-02-01

    Full Text Available 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.

  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.

  18. A neuromorphic circuit mimicking biological short-term memory.

    Science.gov (United States)

    Barzegarjalali, Saeid; Parker, Alice C

    2016-08-01

    Research shows that the way we remember things for a few seconds is a different mechanism from the way we remember things for a longer time. Short-term memory is based on persistently firing neurons, whereas storing information for a longer time is based on strengthening the synapses or even forming new neural connections. Information about location and appearance of an object is segregated and processed by separate neurons. Furthermore neurons can continue firing using different mechanisms. Here, we have designed a biomimetic neuromorphic circuit that mimics short-term memory by firing neurons, using biological mechanisms to remember location and shape of an object. Our neuromorphic circuit has a hybrid architecture. Neurons are designed with CMOS 45nm technology and synapses are designed with carbon nanotubes (CNT).

  19. Neuromorphic adaptive plastic scalable electronics: analog learning systems.

    Science.gov (United States)

    Srinivasa, Narayan; Cruz-Albrecht, Jose

    2012-01-01

    Decades of research to build programmable intelligent machines have demonstrated limited utility in complex, real-world environments. Comparing their performance with biological systems, these machines are less efficient by a factor of 1 million1 billion in complex, real-world environments. The Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program is a multifaceted Defense Advanced Research Projects Agency (DARPA) project that seeks to break the programmable machine paradigm and define a new path for creating useful, intelligent machines. Since real-world systems exhibit infinite combinatorial complexity, electronic neuromorphic machine technology would be preferable in a host of applications, but useful and practical implementations still do not exist. HRL Laboratories LLC has embarked on addressing these challenges, and, in this article, we provide an overview of our project and progress made thus far.

  20. 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.

  1. Integrated neuron circuit for implementing neuromorphic system with synaptic device

    Science.gov (United States)

    Lee, Jeong-Jun; Park, Jungjin; Kwon, Min-Woo; Hwang, Sungmin; Kim, Hyungjin; Park, Byung-Gook

    2018-02-01

    In this paper, we propose and fabricate Integrate & Fire neuron circuit for implementing neuromorphic system. Overall operation of the circuit is verified by measuring discrete devices and the output characteristics of the circuit. Since the neuron circuit shows asymmetric output characteristic that can drive synaptic device with Spike-Timing-Dependent-Plasticity (STDP) characteristic, the autonomous weight update process is also verified by connecting the synaptic device and the neuron circuit. The timing difference of the pre-neuron and the post-neuron induce autonomous weight change of the synaptic device. Unlike 2-terminal devices, which is frequently used to implement neuromorphic system, proposed scheme of the system enables autonomous weight update and simple configuration by using 4-terminal synapse device and appropriate neuron circuit. Weight update process in the multi-layer neuron-synapse connection ensures implementation of the hardware-based artificial intelligence, based on Spiking-Neural- Network (SNN).

  2. Flexible Sensory Platform Based on Oxide-based Neuromorphic Transistors

    Science.gov (United States)

    Liu, Ning; Zhu, Li Qiang; Feng, Ping; Wan, Chang Jin; Liu, Yang Hui; Shi, Yi; Wan, Qing

    2015-01-01

    Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuromorphic transistors with multiple input gates are fabricated on flexible plastic substrates for pH sensor applications. When such device is operated in a quasi-static dual-gate synergic sensing mode, it shows a high pH sensitivity of ~105 mV/pH. Our results also demonstrate that single-spike dynamic mode can remarkably improve pH sensitivity and reduce response/recover time and power consumption. Moreover, we find that an appropriate negative bias applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuromorphic transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption. PMID:26656113

  3. 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.

  4. 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.

  5. Regenerative memory in time-delayed neuromorphic photonic resonators

    OpenAIRE

    Romeira, B.; Avó, R.; Figueiredo, José M. L.; Barland, S.; Javaloyes, J.

    2016-01-01

    We investigate a photonic regenerative memory based upon a neuromorphic oscillator with a delayed self-feedback (autaptic) connection. We disclose the existence of a unique temporal response characteristic of localized structures enabling an ideal support for bits in an optical buffer memory for storage and reshaping of data information. We link our experimental implementation, based upon a nanoscale nonlinear resonant tunneling diode driving a laser, to the paradigm of neuronal activity, the...

  6. High performance VLSI telemetry data systems

    Science.gov (United States)

    Chesney, J.; Speciale, N.; Horner, W.; Sabia, S.

    1990-01-01

    NASA's deployment of major space complexes such as Space Station Freedom (SSF) and the Earth Observing System (EOS) will demand increased functionality and performance from ground based telemetry acquisition systems well above current system capabilities. Adaptation of space telemetry data transport and processing standards such as those specified by the Consultative Committee for Space Data Systems (CCSDS) standards and those required for commercial ground distribution of telemetry data, will drive these functional and performance requirements. In addition, budget limitations will force the requirement for higher modularity, flexibility, and interchangeability at lower cost in new ground telemetry data system elements. At NASA's Goddard Space Flight Center (GSFC), the design and development of generic ground telemetry data system elements, over the last five years, has resulted in significant solutions to these problems. This solution, referred to as the functional components approach includes both hardware and software components ready for end user application. The hardware functional components consist of modern data flow architectures utilizing Application Specific Integrated Circuits (ASIC's) developed specifically to support NASA's telemetry data systems needs and designed to meet a range of data rate requirements up to 300 Mbps. Real-time operating system software components support both embedded local software intelligence, and overall system control, status, processing, and interface requirements. These components, hardware and software, form the superstructure upon which project specific elements are added to complete a telemetry ground data system installation. This paper describes the functional components approach, some specific component examples, and a project example of the evolution from VLSI component, to basic board level functional component, to integrated telemetry data system.

  7. Convolutional networks for fast, energy-efficient neuromorphic computing.

    Science.gov (United States)

    Esser, Steven K; Merolla, Paul A; Arthur, John V; Cassidy, Andrew S; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J; McKinstry, Jeffrey L; Melano, Timothy; Barch, Davis R; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D; Modha, Dharmendra S

    2016-10-11

    Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.

  8. Convolutional networks for fast, energy-efficient neuromorphic computing

    Science.gov (United States)

    Esser, Steven K.; Merolla, Paul A.; Arthur, John V.; Cassidy, Andrew S.; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J.; McKinstry, Jeffrey L.; Melano, Timothy; Barch, Davis R.; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D.; Modha, Dharmendra S.

    2016-01-01

    Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. PMID:27651489

  9. Bistable scattering in graphene-coated dielectric nanowires.

    Science.gov (United States)

    Li, Rujiang; Wang, Huaping; Zheng, Bin; Dehdashti, Shahram; Li, Erping; Chen, Hongsheng

    2017-06-22

    In nonlinear plasmonics, the switching threshold of optical bistability is limited by the weak nonlinear responses from the conventional Kerr dielectric media. Considering the giant nonlinear susceptibility of graphene, here we develop a nonlinear scattering model under the mean field approximation and study the bistable scattering in graphene-coated dielectric nanowires based on the semi-analytical solutions. We find that the switching intensities of bistable scattering can be smaller than 1 MW cm -2 at the working frequency. To further decrease the switching intensities, we show that the most important factor that restricts the bistable scattering is the relaxation time of graphene. Our work not only reveals some general characteristics of graphene-based bistable scattering, but also provides a guidance to further applications of optical bistability in the high speed all-optical signal processing.

  10. Bistable perception modeled as competing stochastic integrations at two levels.

    Science.gov (United States)

    Gigante, Guido; Mattia, Maurizio; Braun, Jochen; Del Giudice, Paolo

    2009-07-01

    We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics - which is largely uncoupled from the time-scales that govern individual populations or neurons - explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons.

  11. 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.

  12. An efficient interpolation filter VLSI architecture for HEVC standard

    Science.gov (United States)

    Zhou, Wei; Zhou, Xin; Lian, Xiaocong; Liu, Zhenyu; Liu, Xiaoxiang

    2015-12-01

    The next-generation video coding standard of High-Efficiency Video Coding (HEVC) is especially efficient for coding high-resolution video such as 8K-ultra-high-definition (UHD) video. Fractional motion estimation in HEVC presents a significant challenge in clock latency and area cost as it consumes more than 40 % of the total encoding time and thus results in high computational complexity. With aims at supporting 8K-UHD video applications, an efficient interpolation filter VLSI architecture for HEVC is proposed in this paper. Firstly, a new interpolation filter algorithm based on the 8-pixel interpolation unit is proposed in this paper. It can save 19.7 % processing time on average with acceptable coding quality degradation. Based on the proposed algorithm, an efficient interpolation filter VLSI architecture, composed of a reused data path of interpolation, an efficient memory organization, and a reconfigurable pipeline interpolation filter engine, is presented to reduce the implement hardware area and achieve high throughput. The final VLSI implementation only requires 37.2k gates in a standard 90-nm CMOS technology at an operating frequency of 240 MHz. The proposed architecture can be reused for either half-pixel interpolation or quarter-pixel interpolation, which can reduce the area cost for about 131,040 bits RAM. The processing latency of our proposed VLSI architecture can support the real-time processing of 4:2:0 format 7680 × 4320@78fps video sequences.

  13. Numerical analysis of electromigration in thin film VLSI interconnections

    NARCIS (Netherlands)

    Petrescu, V.; Mouthaan, A.J.; Schoenmaker, W.; Angelescu, S.; Vissarion, R.; Dima, G.; Wallinga, Hans; Profirescu, M.D.

    1995-01-01

    Due to the continuing downscaling of the dimensions in VLSI circuits, electromigration is becoming a serious reliability hazard. A software tool based on finite element analysis has been developed to solve the two partial differential equations of the two particle vacancy/imperfection model.

  14. Hybrid VLSI/QCA Architecture for Computing FFTs

    Science.gov (United States)

    Fijany, Amir; Toomarian, Nikzad; Modarres, Katayoon; Spotnitz, Matthew

    2003-01-01

    A data-processor architecture that would incorporate elements of both conventional very-large-scale integrated (VLSI) circuitry and quantum-dot cellular automata (QCA) has been proposed to enable the highly parallel and systolic computation of fast Fourier transforms (FFTs). The proposed circuit would complement the QCA-based circuits described in several prior NASA Tech Briefs articles, namely Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), Vol. 25, No. 10 (October 2001), page 42; Compact Interconnection Networks Based on Quantum Dots (NPO-20855) Vol. 27, No. 1 (January 2003), page 32; and Bit-Serial Adder Based on Quantum Dots (NPO-20869), Vol. 27, No. 1 (January 2003), page 35. The cited prior articles described the limitations of very-large-scale integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCAbased signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes.

  15. Optical bistability and multistability in polaritonic materials doped with nanoparticles

    International Nuclear Information System (INIS)

    Wang, Zhiping; Yu, Benli

    2014-01-01

    We investigate the optical bistability and multistability in polaritonic materials doped with nanoparticles inside an optical ring cavity. It is found that the optical bistability and multistability can be easily controlled by adjusting the corresponding parameters of the system properly. The effect of the dipole–dipole interaction has also been included in the formulation, which leads to interesting phenomena. Our scheme opens up the possibility of controling the optical bistability and multistability in polaritonic materials doped with nanoparticles. (letter)

  16. Understanding a Deep Learning Technique through a Neuromorphic System a Case Study with SpiNNaker Neuromorphic Platform

    Directory of Open Access Journals (Sweden)

    Sugiarto Indar

    2018-01-01

    Full Text Available Deep learning (DL has been considered as a breakthrough technique in the field of artificial intelligence and machine learning. Conceptually, it relies on a many-layer network that exhibits a hierarchically non-linear processing capability. Some DL architectures such as deep neural networks, deep belief networks and recurrent neural networks have been developed and applied to many fields with incredible results, even comparable to human intelligence. However, many researchers are still sceptical about its true capability: can the intelligence demonstrated by deep learning technique be applied for general tasks? This question motivates the emergence of another research discipline: neuromorphic computing (NC. In NC, researchers try to identify the most fundamental ingredients that construct intelligence behaviour produced by the brain itself. To achieve this, neuromorphic systems are developed to mimic the brain functionality down to cellular level. In this paper, a neuromorphic platform called SpiNNaker is described and evaluated in order to understand its potential use as a platform for a deep learning approach. This paper is a literature review that contains comparative study on algorithms that have been implemented in SpiNNaker.

  17. Durable bistable auxetics made of rigid solids

    Science.gov (United States)

    Shang, Xiao; Liu, Lu; Rafsanjani, Ahmad; Pasini, Damiano

    2018-02-01

    Bistable Auxetic Metamaterials (BAMs) are a class of monolithic perforated periodic structures with negative Poisson's ratio. Under tension, a BAM can expand and reach a second state of equilibrium through a globally large shape transformation that is ensured by the flexibility of its elastomeric base material. However, if made from a rigid polymer, or metal, BAM ceases to function due to the inevitable rupture of its ligaments. The goal of this work is to extend the unique functionality of the original kirigami architecture of BAM to a rigid solid base material. We use experiments and numerical simulations to assess performance, bistability and durability of rigid BAMs at 10,000 cycles. Geometric maps are presented to elucidate the role of the main descriptors of BAM architecture. The proposed design enables the realization of BAM from a large palette of materials, including elastic-perfectly plastic materials and potentially brittle materials.

  18. Two Bistable Switches Govern M Phase Entry.

    Science.gov (United States)

    Mochida, Satoru; Rata, Scott; Hino, Hirotsugu; Nagai, Takeharu; Novák, Béla

    2016-12-19

    The abrupt and irreversible transition from interphase to M phase is essential to separate DNA replication from chromosome segregation. This transition requires the switch-like phosphorylation of hundreds of proteins by the cyclin-dependent kinase 1 (Cdk1):cyclin B (CycB) complex. Previous studies have ascribed these switch-like phosphorylations to the auto-activation of Cdk1:CycB through the removal of inhibitory phosphorylations on Cdk1-Tyr15 [1, 2]. The positive feedback in Cdk1 activation creates a bistable switch that makes mitotic commitment irreversible [2-4]. Here, we surprisingly find that Cdk1 auto-activation is dispensable for irreversible, switch-like mitotic entry due to a second mechanism, whereby Cdk1:CycB inhibits its counteracting phosphatase (PP2A:B55). We show that the PP2A:B55-inhibiting Greatwall (Gwl)-endosulfine (ENSA) pathway is both necessary and sufficient for switch-like phosphorylations of mitotic substrates. Using purified components of the Gwl-ENSA pathway in a reconstituted system, we found a sharp Cdk1 threshold for phosphorylation of a luminescent mitotic substrate. The Cdk1 threshold to induce mitotic phosphorylation is distinctly higher than the Cdk1 threshold required to maintain these phosphorylations-evidence for bistability. A combination of mathematical modeling and biochemical reconstitution show that the bistable behavior of the Gwl-ENSA pathway emerges from its mutual antagonism with PP2A:B55. Our results demonstrate that two interlinked bistable mechanisms provide a robust solution for irreversible and switch-like mitotic entry. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Bistable (latching) solenoid actuated propellant isolation valve

    Science.gov (United States)

    Wichmann, H.; Deboi, H. H.

    1979-01-01

    The design, fabrication, assembly and test of a development configuration bistable (latching) solenoid actuated propellant isolation valve suitable for the control hydrazine and liquid fluorine to an 800 pound thrust rocket engine is described. The valve features a balanced poppet, utilizing metal bellows, a hard poppet/seat interface and a flexure support system for the internal moving components. This support system eliminates sliding surfaces, thereby rendering the valve free of self generated particles.

  20. Interlinked bistable mechanisms generate robust mitotic transitions.

    Science.gov (United States)

    Hutter, Lukas H; Rata, Scott; Hochegger, Helfrid; Novák, Béla

    2017-10-18

    The transitions between phases of the cell cycle have evolved to be robust and switch-like, which ensures temporal separation of DNA replication, sister chromatid separation, and cell division. Mathematical models describing the biochemical interaction networks of cell cycle regulators attribute these properties to underlying bistable switches, which inherently generate robust, switch-like, and irreversible transitions between states. We have recently presented new mathematical models for two control systems that regulate crucial transitions in the cell cycle: mitotic entry and exit, 1 and the mitotic checkpoint. 2 Each of the two control systems is characterized by two interlinked bistable switches. In the case of mitotic checkpoint control, these switches are mutually activating, whereas in the case of the mitotic entry/exit network, the switches are mutually inhibiting. In this Perspective we describe the qualitative features of these regulatory motifs and show that having two interlinked bistable mechanisms further enhances robustness and irreversibility. We speculate that these network motifs also underlie other cell cycle transitions and cellular transitions between distinct biochemical states.

  1. Dynamics of unidirectionally coupled bistable Henon maps

    International Nuclear Information System (INIS)

    Sausedo-Solorio, J.M.; Pisarchik, A.N.

    2011-01-01

    We study dynamics of two bistable Henon maps coupled in a master-slave configuration. In the case of coexistence of two periodic orbits, the slave map evolves into the master map state after transients, which duration determines synchronization time and obeys a -1/2 power law with respect to the coupling strength. This scaling law is almost independent of the map parameter. In the case of coexistence of chaotic and periodic attractors, very complex dynamics is observed, including the emergence of new attractors as the coupling strength is increased. The attractor of the master map always exists in the slave map independently of the coupling strength. For a high coupling strength, complete synchronization can be achieved only for the attractor similar to that of the master map. -- Highlights: → We study dynamics of two bistable Henon maps coupled in a master-slave configuration. → Synchronization time for periodic orbits obeys a -1/2 power law with respect to coupling. → For a high coupling strength, the slave map remains bistable. → Complete synchronization can be achieved only when both maps stay at the same attractor.

  2. Steady state statistical correlations predict bistability in reaction motifs.

    Science.gov (United States)

    Chakravarty, Suchana; Barik, Debashis

    2017-03-28

    Various cellular decision making processes are regulated by bistable switches that take graded input signals and convert them to binary all-or-none responses. Traditionally, a bistable switch generated by a positive feedback loop is characterized either by a hysteretic signal response curve with two distinct signaling thresholds or by characterizing the bimodality of the response distribution in the bistable region. To identify the intrinsic bistability of a feedback regulated network, here we propose that bistability can be determined by correlating higher order moments and cumulants (≥2) of the joint steady state distributions of two components connected in a positive feedback loop. We performed stochastic simulations of four feedback regulated models with intrinsic bistability and we show that for a bistable switch with variation of the signal dose, the steady state variance vs. covariance adopts a signatory cusp-shaped curve. Further, we find that the (n + 1)th order cross-cumulant vs. nth order cross-cumulant adopts a closed loop structure for at least n = 3. We also propose that our method is capable of identifying systems without intrinsic bistability even though the system may show bimodality in the marginal response distribution. The proposed method can be used to analyze single cell protein data measured at steady state from experiments such as flow cytometry.

  3. Bubbling and bistability in two parameter discrete systems

    OpenAIRE

    Ambika, G.; Sujatha, N. V.

    2000-01-01

    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 derivative at the inflection point of the map function.

  4. Bistable polarization switching in a continuous wave ruby laser

    Science.gov (United States)

    Lawandy, N. M.; Afzal, R. Sohrab

    1988-01-01

    Bistability in the output power, polarization state, and mode volume of an argon-ion laser pumped single mode ruby laser at 6943 A has been observed. The laser operates in a radially confined mode which exhibits hysteresis and bistability only when the pump polarization is parallel to the c-axis.

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

    Indian Academy of Sciences (India)

    Dec. 2001 physics pp. 969–979. Bistable soliton states and switching in doubly inhomogeneously doped fiber couplers. AJIT KUMAR. Department of Physics, Indian Institute of Technology, Hauz Khas, New Delhi 110 016, India. Abstract. Switching between the bistable soliton states in a doubly and inhomogeneously doped.

  6. 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

  7. 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.

  8. Regenerative memory in time-delayed neuromorphic photonic resonators

    Science.gov (United States)

    Romeira, B.; Avó, R.; Figueiredo, José M. L.; Barland, S.; Javaloyes, J.

    2016-01-01

    We investigate a photonic regenerative memory based upon a neuromorphic oscillator with a delayed self-feedback (autaptic) connection. We disclose the existence of a unique temporal response characteristic of localized structures enabling an ideal support for bits in an optical buffer memory for storage and reshaping of data information. We link our experimental implementation, based upon a nanoscale nonlinear resonant tunneling diode driving a laser, to the paradigm of neuronal activity, the FitzHugh-Nagumo model with delayed feedback. This proof-of-concept photonic regenerative memory might constitute a building block for a new class of neuron-inspired photonic memories that can handle high bit-rate optical signals.

  9. 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.

  10. Optical bistability using quantum interference in V-type atoms

    International Nuclear Information System (INIS)

    Anton, M A; Calderon, Oscar G

    2002-01-01

    The behaviour of a V-type three-level atomic system in a ring cavity driven by a coherent field is studied. We consider a V configuration under conditions such that interference between decay channels is important. We find that when quantum interference is taken into account, optical bistability can be realized with a considerable decrease in the threshold intensity and the cooperative parameter. On the other hand, we also include the finite bandwidth of the driving field and study its role in the optical bistable response. It is found that at certain linewidths of the driving field optical bistability is obtained even if the system satisfies the trapping condition and the threshold intensity can be controlled. Furthermore, a change from the optical bistability due to quantum interference to the usual bistable behaviour based on saturation occurs as the driving field linewidth increases

  11. 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...

  12. 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...

  13. Emerging Applications for High K Materials in VLSI Technology

    Science.gov (United States)

    Clark, Robert D.

    2014-01-01

    The current status of High K dielectrics in Very Large Scale Integrated circuit (VLSI) manufacturing for leading edge Dynamic Random Access Memory (DRAM) and Complementary Metal Oxide Semiconductor (CMOS) applications is summarized along with the deposition methods and general equipment types employed. Emerging applications for High K dielectrics in future CMOS are described as well for implementations in 10 nm and beyond nodes. Additional emerging applications for High K dielectrics include Resistive RAM memories, Metal-Insulator-Metal (MIM) diodes, Ferroelectric logic and memory devices, and as mask layers for patterning. Atomic Layer Deposition (ALD) is a common and proven deposition method for all of the applications discussed for use in future VLSI manufacturing. PMID:28788599

  14. Emerging Applications for High K Materials in VLSI Technology

    Directory of Open Access Journals (Sweden)

    Robert D. Clark

    2014-04-01

    Full Text Available The current status of High K dielectrics in Very Large Scale Integrated circuit (VLSI manufacturing for leading edge Dynamic Random Access Memory (DRAM and Complementary Metal Oxide Semiconductor (CMOS applications is summarized along with the deposition methods and general equipment types employed. Emerging applications for High K dielectrics in future CMOS are described as well for implementations in 10 nm and beyond nodes. Additional emerging applications for High K dielectrics include Resistive RAM memories, Metal-Insulator-Metal (MIM diodes, Ferroelectric logic and memory devices, and as mask layers for patterning. Atomic Layer Deposition (ALD is a common and proven deposition method for all of the applications discussed for use in future VLSI manufacturing.

  15. A VLSI image processor via pseudo-mersenne transforms

    International Nuclear Information System (INIS)

    Sei, W.J.; Jagadeesh, J.M.

    1986-01-01

    The computational burden on image processing in medical fields where a large amount of information must be processed quickly and accurately has led to consideration of special-purpose image processor chip design for some time. The very large scale integration (VLSI) resolution has made it cost-effective and feasible to consider the design of special purpose chips for medical imaging fields. This paper describes a VLSI CMOS chip suitable for parallel implementation of image processing algorithms and cyclic convolutions by using Pseudo-Mersenne Number Transform (PMNT). The main advantages of the PMNT over the Fast Fourier Transform (FFT) are: (1) no multiplications are required; (2) integer arithmetic is used. The design and development of this processor, which operates on 32-point convolution or 5 x 5 window image, are described

  16. VLSI Design with Alliance Free CAD Tools: an Implementation Example

    Directory of Open Access Journals (Sweden)

    Chávez-Bracamontes Ramón

    2015-07-01

    Full Text Available This paper presents the methodology used for a digital integrated circuit design that implements the communication protocol known as Serial Peripheral Interface, using the Alliance CAD System. The aim of this paper is to show how the work of VLSI design can be done by graduate and undergraduate students with minimal resources and experience. The physical design was sent to be fabricated using the CMOS AMI C5 process that features 0.5 micrometer in transistor size, sponsored by the MOSIS Educational Program. Tests were made on a platform that transfers data from inertial sensor measurements to the designed SPI chip, which in turn sends the data back on a parallel bus to a common microcontroller. The results show the efficiency of the employed methodology in VLSI design, as well as the feasibility of ICs manufacturing from school projects that have insufficient or no source of funding

  17. 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.

  18. 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

  19. A hierarchical stochastic model for bistable perception.

    Science.gov (United States)

    Albert, Stefan; Schmack, Katharina; Sterzer, Philipp; Schneider, Gaby

    2017-11-01

    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 differences to

  20. 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.

  1. The AMchip: A VLSI associative memory for track finding

    International Nuclear Information System (INIS)

    Morsani, F.; Galeotti, S.; Passuello, D.; Amendolia, S.R.; Ristori, L.; Turini, N.

    1992-01-01

    An associative memory to be used for super-fast track finding in future high energy physics experiments, has been implemented on silicon as a full-custom CMOS VLSI chip (the AMchip). The first prototype has been designed and successfully tested at INFN in Pisa. It is implemented in 1.6 μm, double metal, silicon gate CMOS technology and contains about 140 000 MOS transistors on a 1x1 cm 2 silicon chip. (orig.)

  2. Drift chamber tracking with a VLSI neural network

    International Nuclear Information System (INIS)

    Lindsey, C.S.; Denby, B.; Haggerty, H.; Johns, K.

    1992-10-01

    We have tested a commercial analog VLSI neural network chip for finding in real time the intercept and slope of charged particles traversing a drift chamber. Voltages proportional to the drift times were input to the Intel ETANN chip and the outputs were recorded and later compared off line to conventional track fits. We will discuss the chamber and test setup, the chip specifications, and results of recent tests. We'll briefly discuss possible applications in high energy physics detector triggers

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

    Science.gov (United States)

    1985-01-01

    with the complexity lev- els inherent in VLSI design, in that they can capitalize on their foundations in discrete mathemat- ics and the theory of...basis, rather than globally. Such a partitioning of module semantics makes the specification easier to construct and verify intelectual !y; it also...access function definitions. A standard language improves executability characteristics by capitalizing on portable, optimized system software developed

  4. VLSI scaling methods and low power CMOS buffer circuit

    International Nuclear Information System (INIS)

    Sharma Vijay Kumar; Pattanaik Manisha

    2013-01-01

    Device scaling is an important part of the very large scale integration (VLSI) design to boost up the success path of VLSI industry, which results in denser and faster integration of the devices. As technology node moves towards the very deep submicron region, leakage current and circuit reliability become the key issues. Both are increasing with the new technology generation and affecting the performance of the overall logic circuit. The VLSI designers must keep the balance in power dissipation and the circuit's performance with scaling of the devices. In this paper, different scaling methods are studied first. These scaling methods are used to identify the effects of those scaling methods on the power dissipation and propagation delay of the CMOS buffer circuit. For mitigating the power dissipation in scaled devices, we have proposed a reliable leakage reduction low power transmission gate (LPTG) approach and tested it on complementary metal oxide semiconductor (CMOS) buffer circuit. All simulation results are taken on HSPICE tool with Berkeley predictive technology model (BPTM) BSIM4 bulk CMOS files. The LPTG CMOS buffer reduces 95.16% power dissipation with 84.20% improvement in figure of merit at 32 nm technology node. Various process, voltage and temperature variations are analyzed for proving the robustness of the proposed approach. Leakage current uncertainty decreases from 0.91 to 0.43 in the CMOS buffer circuit that causes large circuit reliability. (semiconductor integrated circuits)

  5. 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).

  6. 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.

  7. 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.

  8. A robust sound perception model suitable for neuromorphic implementation.

    Science.gov (United States)

    Coath, Martin; Sheik, Sadique; Chicca, Elisabetta; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas

    2013-01-01

    We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analog/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity. Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems. We analyze the variability of the response of the network to "noisy" stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

  9. An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator.

    Science.gov (United States)

    Wang, Runchun M; Thakur, Chetan S; van Schaik, André

    2018-01-01

    This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF) neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons). This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.

  10. A Robust Sound Perception Model Suitable for Neuromorphic Implementation

    Directory of Open Access Journals (Sweden)

    Martin eCoath

    2014-01-01

    Full Text Available We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analogue/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity.Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems.We analyse the variability of the response of the network to `noisy' stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

  11. Event-driven contrastive divergence for spiking neuromorphic systems.

    Science.gov (United States)

    Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

    2013-01-01

    Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a 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 recurrent 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.

  12. 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.…

  13. On the bistable zone of milling processes.

    Science.gov (United States)

    Dombovari, Zoltan; Stepan, Gabor

    2015-09-28

    A modal-based model of milling machine tools subjected to time-periodic nonlinear cutting forces is introduced. The model describes the phenomenon of bistability for certain cutting parameters. In engineering, these parameter domains are referred to as unsafe zones, where steady-state milling may switch to chatter for certain perturbations. In mathematical terms, these are the parameter domains where the periodic solution of the corresponding nonlinear, time-periodic delay differential equation is linearly stable, but its domain of attraction is limited due to the existence of an unstable quasi-periodic solution emerging from a secondary Hopf bifurcation. A semi-numerical method is presented to identify the borders of these bistable zones by tracking the motion of the milling tool edges as they might leave the surface of the workpiece during the cutting operation. This requires the tracking of unstable quasi-periodic solutions and the checking of their grazing to a time-periodic switching surface in the infinite-dimensional phase space. As the parameters of the linear structural behaviour of the tool/machine tool system can be obtained by means of standard modal testing, the developed numerical algorithm provides efficient support for the design of milling processes with quick estimates of those parameter domains where chatter can still appear in spite of setting the parameters into linearly stable domains. © 2015 The Authors.

  14. Single coil bistable, bidirectional micromechanical actuator

    Science.gov (United States)

    Tabat, Ned; Guckel, Henry

    1998-09-15

    Micromechanical actuators capable of bidirectional and bistable operation can be formed on substrates using lithographic processing techniques. Bistable operation of the microactuator is obtained using a single coil and a magnetic core with a gap. A plunger having two magnetic heads is supported for back and forth linear movement with respect to the gap in the magnetic core, and is spring biased to a neutral position in which the two heads are on each side of the gap in the core. The single electrical coil is coupled to the core and is provided with electrical current to attract one of the heads toward the core by reluctance action to drive the plunger to a limit of travel in one direction. The current is then cut off and the plunger returns by spring action toward the gap, whereafter the current is reapplied to the coil to attract the other head of the plunger by reluctance action to drive the plunger to its other limit of travel. This process can be repeated at a time when switching of the actuator is required.

  15. Deployable structures using bistable reeled composites

    Science.gov (United States)

    Daton-Lovett, Andrew J.; Compton-Bishop, Quentin M.; Curry, Richard G.

    2000-06-01

    This paper describes an innovative, patented use of composite materials developed by RolaTube Technology Ltd. to make smart deployable structures. Bi-stable reeled composites (BRCs) can alternate between two stable forms; that of a strong, rigid structure and that of a compact coil of flat-wound material. Bi-stability arises as a result of the manipulation of Poisson's ratio and isotropy in the various layers of the material. BRCs are made of fiber- reinforced composite materials, most often with a thermoplastic matrix. A range of fibers and polymer matrices can be used according to the requirements of the operating environment. Samples of a BRC structure were constructed using layers of unidirectional, fiber-reinforced thermoplastic sheet with the layers at different angles. The whole assembly was then consolidated under conditions of elevated temperature and pressure. The properties of the BRC are described and the result of a series of experiments performed on the sample to determine the tensile strength of the BRC structure are reported. A full analysis using finite element methods is being undertaken in collaboration with the University of Cambridge, England. The first commercial use has been to fabricate boom and drive mechanisms for the remote inspection of industrial plant.

  16. 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...

  17. Ca++ dependent bistability induced by serotonin in spinal motoneurons

    DEFF Research Database (Denmark)

    Hounsgaard, J.; Kiehn, O.

    1985-01-01

    The plateau potential, responsible for the bistable state of spinal motoneurons, recently described in the decerebrate cat, was suggested to depend on serotonin (Hounsgaard et al. 1984). In an in vitro preparation of the spinal cord of the turtle we now show that serotonin, applied directly...... to the bath, transforms the intrinsic response properties of motoneurons, uncovering a plateau potential and voltage sensitive bistability. The changes induced by serotonin were blocked by Mn++, while the plateau potential and the bistability remained after application of tetrodotoxin. We conclude...... that serotonin controls the expression of a Ca++ dependent plateau potential in motoneurons....

  18. A neuromorphic controller for a robotic vehicle equipped with a dynamic vision sensor

    OpenAIRE

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

    2017-01-01

    Neuromorphic electronic systems exhibit advantageous characteristics, in terms of low energy consumption and low response latency, which can be useful in robotic applications that require compact and low power embedded computing resources. However, these neuromorphic circuits still face significant limitations that make their usage challenging: these include low precision, variability of components, sensitivity to noise and temperature drifts, as well as the currently limited number of neuron...

  19. 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.

  20. Neuromodulated Synaptic Plasticity on the SpiNNaker Neuromorphic System

    Directory of Open Access Journals (Sweden)

    Mantas Mikaitis

    2018-02-01

    Full Text Available SpiNNaker is a digital neuromorphic architecture, designed specifically for the low power simulation of large-scale spiking neural networks at speeds close to biological real-time. Unlike other neuromorphic systems, SpiNNaker allows users to develop their own neuron and synapse models as well as specify arbitrary connectivity. As a result SpiNNaker has proved to be a powerful tool for studying different neuron models as well as synaptic plasticity—believed to be one of the main mechanisms behind learning and memory in the brain. A number of Spike-Timing-Dependent-Plasticity(STDP rules have already been implemented on SpiNNaker and have been shown to be capable of solving various learning tasks in real-time. However, while STDP is an important biological theory of learning, it is a form of Hebbian or unsupervised learning and therefore does not explain behaviors that depend on feedback from the environment. Instead, learning rules based on neuromodulated STDP (three-factor learning rules have been shown to be capable of solving reinforcement learning tasks in a biologically plausible manner. In this paper we demonstrate for the first time how a model of three-factor STDP, with the third-factor representing spikes from dopaminergic neurons, can be implemented on the SpiNNaker neuromorphic system. Using this learning rule we first show how reward and punishment signals can be delivered to a single synapse before going on to demonstrate it in a larger network which solves the credit assignment problem in a Pavlovian conditioning experiment. Because of its extra complexity, we find that our three-factor learning rule requires approximately 2× as much processing time as the existing SpiNNaker STDP learning rules. However, we show that it is still possible to run our Pavlovian conditioning model with up to 1 × 104 neurons in real-time, opening up new research opportunities for modeling behavioral learning on SpiNNaker.

  1. A forecast-based STDP rule suitable for neuromorphic implementation.

    Science.gov (United States)

    Davies, S; Galluppi, F; Rast, A D; Furber, S B

    2012-08-01

    Artificial neural networks increasingly involve spiking dynamics to permit greater computational efficiency. This becomes especially attractive for on-chip implementation using dedicated neuromorphic hardware. However, both spiking neural networks and neuromorphic hardware have historically found difficulties in implementing efficient, effective learning rules. The best-known spiking neural network learning paradigm is Spike Timing Dependent Plasticity (STDP) which adjusts the strength of a connection in response to the time difference between the pre- and post-synaptic spikes. Approaches that relate learning features to the membrane potential of the post-synaptic neuron have emerged as possible alternatives to the more common STDP rule, with various implementations and approximations. Here we use a new type of neuromorphic hardware, SpiNNaker, which represents the flexible "neuromimetic" architecture, to demonstrate a new approach to this problem. Based on the standard STDP algorithm with modifications and approximations, a new rule, called STDP TTS (Time-To-Spike) relates the membrane potential with the Long Term Potentiation (LTP) part of the basic STDP rule. Meanwhile, we use the standard STDP rule for the Long Term Depression (LTD) part of the algorithm. We show that on the basis of the membrane potential it is possible to make a statistical prediction of the time needed by the neuron to reach the threshold, and therefore the LTP part of the STDP algorithm can be triggered when the neuron receives a spike. In our system these approximations allow efficient memory access, reducing the overall computational time and the memory bandwidth required. The improvements here presented are significant for real-time applications such as the ones for which the SpiNNaker system has been designed. We present simulation results that show the efficacy of this algorithm using one or more input patterns repeated over the whole time of the simulation. On-chip results show that

  2. Bistable responses in bacterial genetic networks: Designs and dynamical consequences

    Science.gov (United States)

    Tiwari, Abhinav; Ray, J. Christian J.; Narula, Jatin; Igoshin, Oleg A.

    2011-01-01

    A key property of living cells is their ability to react to stimuli with specific biochemical responses. These responses can be understood through the dynamics of underlying biochemical and genetic networks. Evolutionary design principles have been well studied in networks that display graded responses, with a continuous relationship between input signal and system output. Alternatively, biochemical networks can exhibit bistable responses so that over a range of signals the network possesses two stable steady states. In this review, we discuss several conceptual examples illustrating network designs that can result in a bistable response of the biochemical network. Next, we examine manifestations of these designs in bacterial master-regulatory genetic circuits. In particular, we discuss mechanisms and dynamic consequences of bistability in three circuits: two-component systems, sigma-factor networks, and a multistep phosphorelay. Analyzing these examples allows us to expand our knowledge of evolutionary design principles for networks with bistable responses. PMID:21385588

  3. Bistable luminescence of trivalent rare-earth ions in crystals

    International Nuclear Information System (INIS)

    Sole, Jose Garcia; Ramirez O, Maria de la; Rodenas, Airan; Jaque, Daniel; Bausa, Luisa; Bettinelli, Marco; Speghini, Adolfo; Cavalli, Enrico; Ivleva, Lioudmila

    2006-01-01

    In this work, we have examined three new bistable systems based on the luminescence of three different crystals activated with trivalent rare earth ions. We have focussed our attention on Yb 3+ ions activators, for which the most relevant results are obtained. The first crystal, Sr 0.6 Ba 0.4 Nb 2 O 6 , is a ferroelectric material with a relatively low phase transition temperature (∼370 K), which provides bistability in the luminescence of Yb 3+ ions due to the thermal hysteresis associated with phase transition. The second crystal, LiNbO 3 , provides an intrinsic bistability in the luminescence of Yb 3+ ions, which is driven by changes in the excitation intensity. In the third crystal, NdPO 4 , a new mechanism of excitation intensity driven bistability is obtained when activated with Yb 3+ ions, due to a interplay between the Nd 3+ ↔Yb 3+ energy transfer and back transfer processes

  4. Bifurcation of transition paths induced by coupled bistable systems.

    Science.gov (United States)

    Tian, Chengzhe; Mitarai, Namiko

    2016-06-07

    We discuss the transition paths in a coupled bistable system consisting of interacting multiple identical bistable motifs. We propose a simple model of coupled bistable gene circuits as an example and show that its transition paths are bifurcating. We then derive a criterion to predict the bifurcation of transition paths in a generalized coupled bistable system. We confirm the validity of the theory for the example system by numerical simulation. We also demonstrate in the example system that, if the steady states of individual gene circuits are not changed by the coupling, the bifurcation pattern is not dependent on the number of gene circuits. We further show that the transition rate exponentially decreases with the number of gene circuits when the transition path does not bifurcate, while a bifurcation facilitates the transition by lowering the quasi-potential energy barrier.

  5. Nanotube devices based crossbar architecture: toward neuromorphic computing

    International Nuclear Information System (INIS)

    Zhao, W S; Gamrat, C; Agnus, G; Derycke, V; Filoramo, A; Bourgoin, J-P

    2010-01-01

    Nanoscale devices such as carbon nanotube and nanowires based transistors, memristors and molecular devices are expected to play an important role in the development of new computing architectures. While their size represents a decisive advantage in terms of integration density, it also raises the critical question of how to efficiently address large numbers of densely integrated nanodevices without the need for complex multi-layer interconnection topologies similar to those used in CMOS technology. Two-terminal programmable devices in crossbar geometry seem particularly attractive, but suffer from severe addressing difficulties due to cross-talk, which implies complex programming procedures. Three-terminal devices can be easily addressed individually, but with limited gain in terms of interconnect integration. We show how optically gated carbon nanotube devices enable efficient individual addressing when arranged in a crossbar geometry with shared gate electrodes. This topology is particularly well suited for parallel programming or learning in the context of neuromorphic computing architectures.

  6. 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.

  7. 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.

  8. Neuromorphic model of magnocellular and parvocellular visual paths: spatial resolution

    International Nuclear Information System (INIS)

    Aguirre, Rolando C; Felice, Carmelo J; Colombo, Elisa M

    2007-01-01

    Physiological studies of the human retina show the existence of at least two visual information processing channels, the magnocellular and the parvocellular ones. Both have different spatial, temporal and chromatic features. This paper focuses on the different spatial resolution of these two channels. We propose a neuromorphic model, so that they match the retina's physiology. Considering the Deutsch and Deutsch model (1992), we propose two configurations (one for each visual channel) of the connection between the retina's different cell layers. The responses of the proposed model have similar behaviour to those of the visual cells: each channel has an optimum response corresponding to a given stimulus size which decreases for larger or smaller stimuli. This size is bigger for the magno path than for the parvo path and, in the end, both channels produce a magnifying of the borders of a stimulus

  9. Stochastic learning in oxide binary synaptic device for neuromorphic computing.

    Science.gov (United States)

    Yu, Shimeng; Gao, Bin; Fang, Zheng; Yu, Hongyu; Kang, Jinfeng; Wong, H-S Philip

    2013-01-01

    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 resistive 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.

  10. Neuromorphic function learning with carbon nanotube based synapses

    International Nuclear Information System (INIS)

    Gacem, Karim; Filoramo, Arianna; Derycke, Vincent; Retrouvey, Jean-Marie; Chabi, Djaafar; Zhao, Weisheng; Klein, Jacques-Olivier

    2013-01-01

    The principle of using nanoscale memory devices as artificial synapses in neuromorphic circuits is recognized as a promising way to build ground-breaking circuit architectures tolerant to defects and variability. Yet, actual experimental demonstrations of the neural network type of circuits based on non-conventional/non-CMOS memory devices and displaying function learning capabilities remain very scarce. We show here that carbon-nanotube-based memory elements can be used as artificial synapses, combined with conventional neurons and trained to perform functions through the application of a supervised learning algorithm. The same ensemble of eight devices can notably be trained multiple times to code successively any three-input linearly separable Boolean logic function despite device-to-device variability. This work thus represents one of the very few demonstrations of actual function learning with synapses based on nanoscale building blocks. The potential of such an approach for the parallel learning of multiple and more complex functions is also evaluated. (paper)

  11. Interaction of multiarmed spirals in bistable media.

    Science.gov (United States)

    He, Ya-feng; Ai, Bao-quan; Liu, Fu-cheng

    2013-05-01

    We study the interaction of both dense and sparse multiarmed spirals in bistable media modeled by equations of the FitzHugh-Nagumo type. A dense one-armed spiral is characterized by its fixed tip. For dense multiarmed spirals, when the initial distance between tips is less than a critical value, the arms collide, connect, and disconnect continuously as the spirals rotate. The continuous reconstruction between the front and the back drives the tips to corotate along a rough circle and to meander zigzaggedly. The rotation frequency of tip, the frequency of zigzagged displacement, the frequency of spiral, the oscillation frequency of media, and the number of arms satisfy certain relations as long as the control parameters of the model are fixed. When the initial distance between tips is larger than the critical value, the behaviors of individual arms within either dense or sparse multiarmed spirals are identical to that of corresponding one-armed spirals.

  12. Lattice stretching bistability and dynamic heterogeneity

    DEFF Research Database (Denmark)

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

    2012-01-01

    A simple one-dimensional lattice model is suggested to describe the experimentally observed plateau in force-stretching diagrams for some macromolecules. This chain model involves the nearest-neighbor interaction of a Morse-like potential (required to have a saturation branch) and a harmonic second......-neighbor coupling. Under an external stretching applied to the chain ends, the intersite Morse-like potential results in the appearance of a double-well potential within each chain monomer, whereas the interaction between the second neighbors provides a homogeneous bistable (degenerate) ground state, at least...... stretched bonds with a double-well potential. This case allows us to explain the existence of a plateau in the force-extension diagram for DNA and α-helix protein. Finally, the soliton dynamics are studied in detail....

  13. A bistable electromagnetically actuated rotary gate microvalve

    International Nuclear Information System (INIS)

    Luharuka, Rajesh; Hesketh, Peter J

    2008-01-01

    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

  14. Cops or Robbers — a Bistable Society

    Science.gov (United States)

    Kułakowski, K.

    The norm game described by Axelrod in 1985 was recently treated with the master equation formalism. Here we discuss the equations, where (i) those who break the norm cannot punish and those who punish cannot break the norm, (ii) the tendency to punish is suppressed if the majority breaks the norm. The second mechanism is new. For some values of the parameters the solution shows the saddle-point bifurcation. Then, two stable solutions are possible, where the majority breaks the norm or the majority punishes. This means, that the norm breaking can be discontinuous, when measured in the social scale. The bistable character is reproduced also with new computer simulations on the Erdös-Rényi directed network.

  15. Asymmetric Effects on Escape Rates of Bistable System

    International Nuclear Information System (INIS)

    Wang Canjun; Mei Dongcheng; Dai Zucheng

    2011-01-01

    The asymmetric effects on the escape rates from the stable states x ± in the bistable system are analyzed. The results indicate that the multiplicative noise and the additive noise always enhance the particle escape from stable states x ± of bistable. However, the asymmetric parameter r enhances the particle escape from stable state x + , and holds back the particle escape from stable state x - . (general)

  16. Analytic descriptions of stochastic bistable systems under force ramp.

    Science.gov (United States)

    Friddle, Raymond W

    2016-05-01

    Solving the two-state master equation with time-dependent rates, the ubiquitous driven bistable system, is a long-standing problem that does not permit a complete solution for all driving rates. Here we show an accurate approximation to this problem by considering the system in the control parameter regime. The results are immediately applicable to a diverse range of bistable systems including single-molecule mechanics.

  17. An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator

    Directory of Open Access Journals (Sweden)

    Runchun M. Wang

    2018-04-01

    Full Text Available This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons. This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.

  18. Proprioceptive Feedback through a Neuromorphic Muscle Spindle Model

    Directory of Open Access Journals (Sweden)

    Lorenzo Vannucci

    2017-06-01

    Full Text Available Connecting biologically inspired neural simulations to physical or simulated embodiments can be useful both in robotics, for the development of a new kind of bio-inspired controllers, and in neuroscience, to test detailed brain models in complete action-perception loops. The aim of this work is to develop a fully spike-based, biologically inspired mechanism for the translation of proprioceptive feedback. The translation is achieved by implementing a computational model of neural activity of type Ia and type II afferent fibers of muscle spindles, the primary source of proprioceptive information, which, in mammals is regulated through fusimotor activation and provides necessary adjustments during voluntary muscle contractions. As such, both static and dynamic γ-motoneurons activities are taken into account in the proposed model. Information from the actual proprioceptive sensors (i.e., motor encoders is then used to simulate the spindle contraction and relaxation, and therefore drive the neural activity. To assess the feasibility of this approach, the model is implemented on the NEST spiking neural network simulator and on the SpiNNaker neuromorphic hardware platform and tested on simulated and physical robotic platforms. The results demonstrate that the model can be used in both simulated and real-time robotic applications to translate encoder values into a biologically plausible neural activity. Thus, this model provides a completely spike-based building block, suitable for neuromorphic platforms, that will enable the development of sensory-motor closed loops which could include neural simulations of areas of the central nervous system or of low-level reflexes.

  19. Point DCT VLSI Architecture for Emerging HEVC Standard

    OpenAIRE

    Ahmed, Ashfaq; Shahid, Muhammad Usman; Rehman, Ata ur

    2012-01-01

    This work presents a flexible VLSI architecture to compute the -point DCT. Since HEVC supports different block sizes for the computation of the DCT, that is, 4 × 4 up to 3 2 × 3 2 , the design of a flexible architecture to support them helps reducing the area overhead of hardware implementations. The hardware proposed in this work is partially folded to save area and to get speed for large video sequences sizes. The proposed architecture relies on the decomposition of the DCT matrices into ...

  20. 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

  1. Power efficient and high performance VLSI architecture for AES algorithm

    Directory of Open Access Journals (Sweden)

    K. Kalaiselvi

    2015-09-01

    Full Text Available Advanced encryption standard (AES algorithm has been widely deployed in cryptographic applications. This work proposes a low power and high throughput implementation of AES algorithm using key expansion approach. We minimize the power consumption and critical path delay using the proposed high performance architecture. It supports both encryption and decryption using 256-bit keys with a throughput of 0.06 Gbps. The VHDL language is utilized for simulating the design and an FPGA chip has been used for the hardware implementations. Experimental results reveal that the proposed AES architectures offer superior performance than the existing VLSI architectures in terms of power, throughput and critical path delay.

  2. 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

  3. Does visual attention drive the dynamics of bistable perception?

    Science.gov (United States)

    Dieter, Kevin C; Brascamp, Jan; Tadin, Duje; Blake, Randolph

    2016-10-01

    How does attention interact with incoming sensory information to determine what we perceive? One domain in which this question has received serious consideration is that of bistable perception: a captivating class of phenomena that involves fluctuating visual experience in the face of physically unchanging sensory input. Here, some investigations have yielded support for the idea that attention alone determines what is seen, while others have implicated entirely attention-independent processes in driving alternations during bistable perception. We review the body of literature addressing this divide and conclude that in fact both sides are correct-depending on the form of bistable perception being considered. Converging evidence suggests that visual attention is required for alternations in the type of bistable perception called binocular rivalry, while alternations during other types of bistable perception appear to continue without requiring attention. We discuss some implications of this differential effect of attention for our understanding of the mechanisms underlying bistable perception, and examine how these mechanisms operate during our everyday visual experiences.

  4. A genetic bistable switch utilizing nonlinear protein degradation.

    Science.gov (United States)

    Huang, Daniel; Holtz, William J; Maharbiz, Michel M

    2012-07-09

    Bistability is a fundamental property in engineered and natural systems, conferring the ability to switch and retain states. Synthetic bistable switches in prokaryotes have mainly utilized transcriptional components in their construction. Using both transcriptional and enzymatic components, creating a hybrid system, allows for wider bistable parameter ranges in a circuit. In this paper, we demonstrate a tunable family of hybrid bistable switches in E. coli using both transcriptional components and an enzymatic component. The design contains two linked positive feedback loops. The first loop utilizes the lambda repressor, CI, and the second positive feedback loop incorporates the Lon protease found in Mesoplasma florum (mf-Lon). We experimentally tested for bistable behavior in exponential growth phase, and found that our hybrid bistable switch was able to retain its state in the absence of an input signal throughout 40 cycles of cell division. We also tested the transient behavior of our switch and found that switching speeds can be tuned by changing the expression rate of mf-Lon. To our knowledge, this work demonstrates the first use of dynamic expression of an orthogonal and heterologous protease to tune a nonlinear protein degradation circuit. The hybrid switch is potentially a more robust and tunable topology for use in prokaryotic systems.

  5. Genes contribute to the switching dynamics of bistable perception.

    Science.gov (United States)

    Shannon, Robert W; Patrick, Christopher J; Jiang, Yi; Bernat, Edward; He, Sheng

    2011-03-09

    Ordinarily, the visual system provides an unambiguous representation of the world. However, at times alternative plausible interpretations of a given stimulus arise, resulting in a dynamic perceptual alternation of the differing interpretations, commonly referred to as bistable or rivalrous perception. Recent research suggests that common neural mechanisms may be involved in the dynamics of very different types of bistable phenomena. Further, evidence has emerged that genetic factors may be involved in determining the rate of switch for at least one form of bistable perception, known as binocular rivalry. The current study evaluated whether genetic factors contribute to the switching dynamics for distinctly different variants of bistable perception in the same participant sample. Switching rates were recorded for MZ and DZ twin participants in two different bistable perception tasks, binocular rivalry and the Necker Cube. Strong concordance in switching rates across both tasks was evident for MZ but not DZ twins, indicating that genetic factors indeed contribute to the dynamics of multiple forms of bistable perception.

  6. 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....

  7. VLSI architecture and design for the Fermat Number Transform implementation

    Energy Technology Data Exchange (ETDEWEB)

    Pajayakrit, A.

    1987-01-01

    A new technique of sectioning a pipelined transformer, using the Fermat Number Transform (FNT), is introduced. Also, a novel VLSI design which overcomes the problems of implementing FNTs, for use in fast convolution/correlation, is described. The design comprises one complete section of a pipelined transformer and may be programmed to function at any point in a forward or inverse pipeline, so allowing the construction of a pipelined convolver or correlator using identical chips, thus the favorable properties of the transform can be exploited. This overcomes the difficulty of fitting a complete pipeline onto one chip without resorting to the use of several different designs. The implementation of high-speed convolver/correlator using the VLSI chips has been successfully developed and tested. For impulse response lengths of up to 16 points the sampling rates of 0.5 MHz can be achieved. Finally, the filter speed performance using the FNT chips is compared to other designs and conclusions drawn on the merits of the FNT for this application. Also, the advantages and limitations of the FNT are analyzed, with respect to the more conventional FFT, and the results are provided.

  8. Development of Radhard VLSI electronics for SSC calorimeters

    International Nuclear Information System (INIS)

    Dawson, J.W.; Nodulman, L.J.

    1989-01-01

    A new program of development of integrated electronics for liquid argon calorimeters in the SSC detector environment is being started at Argonne National Laboratory. Scientists from Brookhaven National Laboratory and Vanderbilt University together with an industrial participants are expected to collaborate in this work. Interaction rates, segmentation, and the radiation environment dictate that front-end electronics of SSC calorimeters must be implemented in the form of highly integrated, radhard, analog, low noise, VLSI custom monolithic devices. Important considerations are power dissipation, choice of functions integrated on the front-end chips, and cabling requirements. An extensive level of expertise in radhard electronics exists within the industrial community, and a primary objective of this work is to bring that expertise to bear on the problems of SSC detector design. Radiation hardness measurements and requirements as well as calorimeter design will be primarily the responsibility of Argonne scientists and our Brookhaven and Vanderbilt colleagues. Radhard VLSI design and fabrication will be primarily the industrial participant's responsibility. The rapid-cycling synchrotron at Argonne will be used for radiation damage studies involving response to neutrons and charged particles, while damage from gammas will be investigated at Brookhaven. 10 refs., 6 figs., 2 tabs

  9. Design of two easily-testable VLSI array multipliers

    Energy Technology Data Exchange (ETDEWEB)

    Ferguson, J.; Shen, J.P.

    1983-01-01

    Array multipliers are well-suited to VLSI implementation because of the regularity in their iterative structure. However, most VLSI circuits are very difficult to test. This paper shows that, with appropriate cell design, array multipliers can be designed to be very easily testable. An array multiplier is called c-testable if all its adder cells can be exhaustively tested while requiring only a constant number of test patterns. The testability of two well-known array multiplier structures are studied. The conventional design of the carry-save array multipler is shown to be not c-testable. However, a modified design, using a modified adder cell, is generated and shown to be c-testable and requires only 16 test patterns. Similar results are obtained for the baugh-wooley two's complement array multiplier. A modified design of the baugh-wooley array multiplier is shown to be c-testable and requires 55 test patterns. The implementation of a practical c-testable 16*16 array multiplier is also presented. 10 references.

  10. Bistable energy harvesting enhancement with an auxiliary linear oscillator

    Science.gov (United States)

    Harne, R. L.; Thota, M.; Wang, K. W.

    2013-12-01

    Recent work has indicated that linear vibrational energy harvesters with an appended degree-of-freedom (DOF) may be advantageous for introducing new dynamic forms to extend the operational bandwidth. Given the additional interest in bistable harvester designs, which exhibit a propitious snap through effect from one stable state to the other, it is a logical extension to explore the influence of an added DOF to a bistable system. However, bistable snap through is not a resonant phenomenon, which tempers the presumption that the dynamics induced by an additional DOF on bistable designs would inherently be beneficial as for linear systems. This paper presents two analytical formulations to assess the fundamental and superharmonic steady-state dynamics of an excited bistable energy harvester to which is attached an auxiliary linear oscillator. From an energy harvesting perspective, the model predicts that the additional linear DOF uniformly amplifies the bistable harvester response magnitude and generated power for excitation frequencies less than the attachment’s resonance while improved power density spans a bandwidth below this frequency. Analyses predict bandwidths having co-existent responses composed of a unique proportion of fundamental and superharmonic dynamics. Experiments validate key analytical predictions and observe the ability for the coupled system to develop an advantageous multi-harmonic interwell response when the initial conditions are insufficient for continuous high-energy orbit at the excitation frequency. Overall, the addition of an auxiliary linear oscillator to a bistable harvester is found to be an effective means of enhancing the energy harvesting performance and robustness.

  11. An analog VLSI chip emulating polarization vision of Octopus retina.

    Science.gov (United States)

    Momeni, Massoud; Titus, Albert H

    2006-01-01

    Biological systems provide a wealth of information which form the basis for human-made artificial systems. In this work, the visual system of Octopus is investigated and its polarization sensitivity mimicked. While in actual Octopus retina, polarization vision is mainly based on the orthogonal arrangement of its photoreceptors, our implementation uses a birefringent micropolarizer made of YVO4 and mounted on a CMOS chip with neuromorphic circuitry to process linearly polarized light. Arranged in an 8 x 5 array with two photodiodes per pixel, each consuming typically 10 microW, this circuitry mimics both the functionality of individual Octopus retina cells by computing the state of polarization and the interconnection of these cells through a bias-controllable resistive network.

  12. Bistable behaviour of biexciton population in a dense exciton-biexciton system in semiconductors

    International Nuclear Information System (INIS)

    Nguyen Ba An.

    1986-05-01

    The steady state bistable behaviour of biexciton population in a dense exciton-biexciton semiconductor is considered. The intrinsic optical feedback is provided by the recombination mechanism. The exciton-biexciton and biexciton-biexciton interactions play the role of non-linearity responsible for biexciton bistability to occur. The conditions leading to the effect of bistability are obtained and two-parameter phase transition diagrams are drawn for both intensity and frequency bistable phenomena. (author)

  13. Optical bistability induced by quantum coherence in a negative index atomic medium

    International Nuclear Information System (INIS)

    Zhang Hong-Jun; Sun Hui; Li Jin-Ping; Yin Bao-Yin; Guo Hong-Ju

    2013-01-01

    Bistability behaviors in an optical ring cavity filled with a dense V-type four-level atomic medium are theoretically investigated. It is found that the optical bistability can appear in the negative refraction frequency band, while both the bistability and multi-stability can occur in the positive refraction frequency bands. Therefore, optical bistability can be realized from conventional material to negative index material due to quantum coherence in our scheme. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  14. Evaluation of bistable systems versus matched filters in detecting bipolar pulse signals

    OpenAIRE

    Duan, Fabing; Abbott, Derek; Gao, Qisheng

    2004-01-01

    This paper presents a thorough evaluation of a bistable system versus a matched filter in detecting bipolar pulse signals. The detectability of the bistable system can be optimized by adding noise, i.e. the stochastic resonance (SR) phenomenon. This SR effect is also demonstrated by approximate statistical detection theory of the bistable system and corresponding numerical simulations. Furthermore, the performance comparison results between the bistable system and the matched filter show that...

  15. 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 ...

  16. 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...

  17. Bistability and Biofilm Formation in Bacillus subtilis

    Science.gov (United States)

    Chai, Yunrong; Chu, Frances; Kolter, Roberto; Losick, Richard

    2008-01-01

    Summary Biofilms of Bacillus subtilis consist of long chains of cells that are held together in bundles by an extracellular matrix of exopolysaccharide and the protein TasA. The exopolysaccharide is produced by enzymes encoded by the epsA-O operon and the gene encoding TasA is located in the yqxM-sipW-tasA operon. Both operons are under the control of the repressor SinR. Derepression is mediated by the antirepressor SinI, which binds to SinR with a 1:1 stoichiometry. Paradoxically, in medium promoting derepression of the matrix operons, the overall concentration of SinR in the culture greatly exceeded that of SinI. We show that under biofilm-promoting conditions sinI, which is under the control of the response regulator Spo0A, was expressed only in a small subpopulation of cells, whereas sinR was expressed in almost all cells. Activation of Spo0A is known to be subject to a bistable switch, and we infer that SinI reaches levels sufficient to trigger matrix production only in the subpopulation of cells in which Spo0A is active. Additionally, evidence suggests that sinI is expressed at intermediate, but not low or high, levels of Spo0A activity, which may explain why certain nutritional conditions are more effective in promoting biofilm formation than others. PMID:18047568

  18. 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.

  19. Fundamental role of bistability in optimal homeostatic control

    Science.gov (United States)

    Wang, Guanyu

    2013-03-01

    Bistability is a fundamental phenomenon in nature and has a number of fine properties. However, these properties are consequences of bistability at the physiological level, which do not explain why it had to emerge during evolution. Using optimal homeostasis as the first principle and Pontryagin's Maximum Principle as the optimization approach, I find that bistability emerges as an indispensable control mechanism. Because the mathematical model is general and the result is independent of parameters, it is likely that most biological systems use bistability to control homeostasis. Glucose homeostasis represents a good example. It turns out that bistability is the only solution to a dilemma in glucose homeostasis: high insulin efficiency is required for rapid plasma glucose clearance, whereas an insulin sparing state is required to guarantee the brain's safety during fasting. This new perspective can illuminate studies on the twin epidemics of obesity and diabetes and the corresponding intervening strategies. For example, overnutrition and sedentary lifestyle may represent sudden environmental changes that cause the lose of optimality, which may contribute to the marked rise of obesity and diabetes in our generation.

  20. Dynamic control of a bistable wing under aerodynamic loading

    International Nuclear Information System (INIS)

    Bilgen, Onur; Arrieta, Andres F; Friswell, Michael I; Hagedorn, Peter

    2013-01-01

    The aerodynamic evaluation of a dynamic control technique applied to a bistable unsymmetrical cross-ply composite plate with surface bonded piezoelectric actuators is presented. The plate is clamped on one end to form a low-aspect-ratio wing. A previously proposed dynamic control method, utilizing bending resonance in different stable equilibrium positions, is used to induce snap-through between the two equilibrium states. Compared to quasi-static actuation, driving the bistable plate near resonance using surface bonded piezoelectric materials requires, theoretically, a lower peak excitation voltage to achieve snap-through. First, a set of extensive wind tunnel experiments are conducted on the passive bistable wing to understand the change in the dynamic behavior under various aerodynamic conditions. The passive wing demonstrated sufficient bending stiffness to sustain its shape under aerodynamic loading while preserving the desired bistable behavior. Next, by the use of the resonant control technique, the plate is turned into an effectively monostable structure, or alternatively, both stable equilibrium positions can be reached actively from the other stable equilibrium. Dynamic forward and reverse snap-through is demonstrated in the wind tunnel which shows both the effectiveness of the piezoelectric actuation as well as the load carrying capability of both states of the bistable wing. (paper)

  1. 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.

  2. Non-resonant energy harvesting via an adaptive bistable potential

    International Nuclear Information System (INIS)

    Hosseinloo, Ashkan Haji; Turitsyn, Konstantin

    2016-01-01

    Narrow bandwidth and easy detuning, inefficiency in broadband and non-stationary excitations, and difficulties in matching a linear harvester’s resonance frequency to low-frequency excitations at small scales, have convinced researchers to investigate nonlinear, and in particular bistable, energy harvesters in recent years. However, bistable harvesters suffer from co-existing low and high energy orbits, and sensitivity to initial conditions, and have recently been proven inefficient when subjected to many real-world random and non-stationary excitations. Here, we propose a novel non-resonant buy-low-sell-high strategy that can significantly improve the harvester’s effectiveness at low frequencies in a much more robust fashion. This strategy could be realized by a passive adaptive bistable system. Simulation results confirm the high effectiveness of the adaptive bistable system following a buy-low-sell-high logic when subjected to harmonic and random non-stationary walking excitations compared to its conventional bistable and linear counterparts. (paper)

  3. Chaos in a new bistable rotating electromechanical system

    International Nuclear Information System (INIS)

    Tsapla Fotsa, R.; Woafo, P.

    2016-01-01

    Highlights: • A new electromechanical system with rotating arm and bistable potential energy is studied. • The bistability is generated by the interaction of three permanent magnets, one fixed at the end of the arm and two other fixed at equal distance relative to the central position of the arm. • It exhibits dissipative and Hamiltonian chaos. • Such a bistable electromechanical system can be used as the actuation part of chaotic sieves and mixers. - Abstract: A device consisting of an induction motor activating a rotating rigid arm is designed and comprises a bistable potential due to the presence of three permanent magnets. Its mathematical equations are established and the numerical results both in the absence and in the presence of magnets are compared. The generation of chaotic behavior is achieved using two different external excitations: sinewave and square wave. In the presence of magnets, the system presents periodic and dissipative chaotic dynamics. Approximating the global potential energy to a bistable quartic potential, the Melnikov method is used to derive the conditions for the appearance of Hamiltonian chaos. Such a device can be used for industrial and domestic applications for mixing and sieving activities.

  4. Frontoparietal cortex mediates perceptual transitions in bistable perception.

    Science.gov (United States)

    Weilnhammer, Veith A; Ludwig, Karin; Hesselmann, Guido; Sterzer, Philipp

    2013-10-02

    During bistable vision, perception oscillates between two mutually exclusive percepts despite constant sensory input. Greater BOLD responses in frontoparietal cortex have been shown to be associated with endogenous perceptual transitions compared with "replay" transitions designed to closely match bistability in both perceptual quality and timing. It has remained controversial, however, whether this enhanced activity reflects causal influences of these regions on processing at the sensory level or, alternatively, an effect of stimulus differences that result in, for example, longer durations of perceptual transitions in bistable perception compared with replay conditions. Using a rotating Lissajous figure in an fMRI experiment on 15 human participants, we controlled for potential confounds of differences in transition duration and confirmed previous findings of greater activity in frontoparietal areas for transitions during bistable perception. In addition, we applied dynamic causal modeling to identify the neural model that best explains the observed BOLD signals in terms of effective connectivity. We found that enhanced activity for perceptual transitions is associated with a modulation of top-down connectivity from frontal to visual cortex, thus arguing for a crucial role of frontoparietal cortex in perceptual transitions during bistable perception.

  5. 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.

  6. A bistable mechanism for chord extension morphing rotors

    Science.gov (United States)

    Johnson, Terrence; Frecker, Mary; Gandhi, Farhan

    2009-03-01

    Research efforts have shown that helicopter rotor blade morphing is an effective means to improve flight performance. Previous example of rotor blade morphing include using smart-materials for trailing deflection and rotor blade twist and tip twist, the development of a comfortable airfoil using compliant mechanisms, the use of a Gurney flap for air-flow deflection and centrifugal force actuated device to increase the span of the blade. In this paper we explore the use of a bistable mechanism for rotor morphing, specifically, blade chord extension using a bistable arc. Increasing the chord of the rotor blade is expected to generate more lift-load and improve helicopter performance. Bistable or "snap through" mechanisms have multiple stable equilibrium states and are a novel way to achieve large actuation output stroke. Bistable mechanisms do not require energy input to maintain a stable equilibrium state as both states do not require locking. In this work, we introduce a methodology for the design of bistable arcs for chord morphing using the finite element analysis and pseudo-rigid body model, to study the effect of different arc types, applied loads and rigidity on arc performance.

  7. The derivation of a bistable criterion for double V-beam mechanisms

    International Nuclear Information System (INIS)

    Wu, Cho-Chun; Chen, Rongshun; Lin, Meng-Ju

    2013-01-01

    This study presents the theoretical derivation of the discriminant D as a structural and material criterion for determining whether bistability can occur in micromechanically bistable mechanisms. When D < 0, the mechanism displays bistable behavior if an appropriate force is applied to push the bistable mechanism, whereas when D > 0, bistable behavior cannot occur. The proposed V-beam bistable mechanism was successfully fabricated with various beam lengths and tilted angles. The experiments conducted in this study validated the theoretical study of bistability. A comparison of the theoretical solutions and experimental results shows good agreement. Results further show that to design a bistable V-beam mechanism, the tilted angle should be larger for the same beam length, whereas the beam length should be longer for the same tilted angle. The developed discriminant D can be used to predict if a bistable mechanism can achieve bistable behavior based on structural sizes and material properties. Consequently, researchers can reduce trial-and-error experiments when designing a bistable mechanism. A V-beam with a larger tilted angle of up to 5° was successfully fabricated to act as a bistable mechanism, compared to a 3.5° tilted angle in existing studies. Consequently, the proposed method has the advantages of shorter beam lengths and smaller device areas. (paper)

  8. VLSI Architectures for the Multiplication of Integers Modulo a Fermat Number

    Science.gov (United States)

    Chang, J. J.; Truong, T. K.; Reed, I. S.; Hsu, I. S.

    1984-01-01

    Multiplication is central in the implementation of Fermat number transforms and other residue number algorithms. There is need for a good multiplication algorithm that can be realized easily on a very large scale integration (VLSI) chip. The Leibowitz multiplier is modified to realize multiplication in the ring of integers modulo a Fermat number. This new algorithm requires only a sequence of cyclic shifts and additions. The designs developed for this new multiplier are regular, simple, expandable, and, therefore, suitable for VLSI implementation.

  9. 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.

  10. 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

    2009-01-01

    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.

  11. Neuromorphic computing enabled by physics of electron spins: Prospects and perspectives

    Science.gov (United States)

    Sengupta, Abhronil; Roy, Kaushik

    2018-03-01

    “Spintronics” refers to the understanding of the physics of electron spin-related phenomena. While most of the significant advancements in this field has been driven primarily by memory, recent research has demonstrated that various facets of the underlying physics of spin transport and manipulation can directly mimic the functionalities of the computational primitives in neuromorphic computation, i.e., the neurons and synapses. Given the potential of these spintronic devices to implement bio-mimetic computations at very low terminal voltages, several spin-device structures have been proposed as the core building blocks of neuromorphic circuits and systems to implement brain-inspired computing. Such an approach is expected to play a key role in circumventing the problems of ever-increasing power dissipation and hardware requirements for implementing neuro-inspired algorithms in conventional digital CMOS technology. Perspectives on spin-enabled neuromorphic computing, its status, and challenges and future prospects are outlined in this review article.

  12. VLSI and system architecture-the new development of system 5G

    Energy Technology Data Exchange (ETDEWEB)

    Sakamura, K.; Sekino, A.; Kodaka, T.; Uehara, T.; Aiso, H.

    1982-01-01

    A research and development proposal is presented for VLSI CAD systems and for a hardware environment called system 5G on which the VLSI CAD systems run. The proposed CAD systems use a hierarchically organized design language to enable design of anything from basic architectures of VLSI to VLSI mask patterns in a uniform manner. The cad systems will eventually become intelligent cad systems that acquire design knowledge and perform automatic design of VLSI chips when the characteristic requirements of VLSI chip is given. System 5G will consist of superinference machines and the 5G communication network. The superinference machine will be built based on a functionally distributed architecture connecting inferommunication network. The superinference machine will be built based on a functionally distributed architecture connecting inference machines and relational data base machines via a high-speed local network. The transfer rate of the local network will be 100 mbps at the first stage of the project and will be improved to 1 gbps. Remote access to the superinference machine will be possible through the 5G communication network. Access to system 5G will use the 5G network architecture protocol. The users will access the system 5G using standardized 5G personal computers. 5G personal logic programming stations, very high intelligent terminals providing an instruction set that supports predicate logic and input/output facilities for audio and graphical information.

  13. 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.

  14. A Dataset for Visual Navigation with Neuromorphic Methods

    Directory of Open Access Journals (Sweden)

    Francisco eBarranco

    2016-02-01

    Full Text Available Standardized benchmarks in Computer Vision have greatly contributed to the advance of approaches to many problems in the field. If we want to enhance the visibility of event-driven vision and increase its impact, we will need benchmarks that allow comparison among different neuromorphic methods as well as comparison to Computer Vision conventional approaches. We present datasets to evaluate the accuracy of frame-free and frame-based approaches for tasks of visual navigation. Similar to conventional Computer Vision datasets, we provide synthetic and real scenes, with the synthetic data created with graphics packages, and the real data recorded using a mobile robotic platform carrying a dynamic and active pixel vision sensor (DAVIS and an RGB+Depth sensor. For both datasets the cameras move with a rigid motion in a static scene, and the data includes the images, events, optic flow, 3D camera motion, and the depth of the scene, along with calibration procedures. Finally, we also provide simulated event data generated synthetically from well-known frame-based optical flow datasets.

  15. Bistable near field and bistable transmittance in 2D composite slab consisting of nonlocal core-Kerr shell inclusions.

    Science.gov (United States)

    Huang, Yang; Wu, Ya Min; Gao, Lei

    2017-01-23

    We carry out a theoretical study on optical bistability of near field intensity and transmittance in two-dimensional nonlinear composite slab. This kind of 2D composite is composed of nonlocal metal/Kerr-type dielectric core-shell inclusions randomly embedded in the host medium, and we derivate the nonlinear relation between the field intensity in the shell of inclusions and the incident field intensity with self-consistent mean field approximation. Numerical demonstration has been performed to show the viable parameter space for the bistable near field. We show that nonlocality can provide broader region in geometric parameter space for bistable near field as well as bistable transmittance of the nonlocal composite slab compared to local case. Furthermore, we investigate the bistable transmittance in wavelength spectrum, and find that besides the input intensity, the wavelength operation could as well make the transmittance jump from a high value to a low one. This kind of self-tunable nano-composite slab might have potential application in optical switching devices.

  16. Point DCT VLSI Architecture for Emerging HEVC Standard

    Directory of Open Access Journals (Sweden)

    Ashfaq Ahmed

    2012-01-01

    Full Text Available This work presents a flexible VLSI architecture to compute the -point DCT. Since HEVC supports different block sizes for the computation of the DCT, that is, 4×4 up to 32×32, the design of a flexible architecture to support them helps reducing the area overhead of hardware implementations. The hardware proposed in this work is partially folded to save area and to get speed for large video sequences sizes. The proposed architecture relies on the decomposition of the DCT matrices into sparse submatrices in order to reduce the multiplications. Finally, multiplications are completely eliminated using the lifting scheme. The proposed architecture sustains real-time processing of 1080P HD video codec running at 150 MHz.

  17. PERFORMANCE OF LEAKAGE POWER MINIMIZATION TECHNIQUE FOR CMOS VLSI TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    T. Tharaneeswaran

    2012-06-01

    Full Text Available Leakage power of CMOS VLSI Technology is a great concern. To reduce leakage power in CMOS circuits, a Leakage Power Minimiza-tion Technique (LPMT is implemented in this paper. Leakage cur-rents are monitored and compared. The Comparator kicks the charge pump to give body voltage (Vbody. Simulations of these circuits are done using TSMC 0.35µm technology with various operating temper-atures. Current steering Digital-to-Analog Converter (CSDAC is used as test core to validate the idea. The Test core (eg.8-bit CSDAC had power consumption of 347.63 mW. LPMT circuit alone consumes power of 6.3405 mW. This technique results in reduction of leakage power of 8-bit CSDAC by 5.51mW and increases the reliability of test core. Mentor Graphics ELDO and EZ-wave are used for simulations.

  18. VLSI-based video event triggering for image data compression

    Science.gov (United States)

    Williams, Glenn L.

    1994-02-01

    Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.

  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. Optical Bistability in Graded Core-Shell Granular Composites

    International Nuclear Information System (INIS)

    Wu Ya-Min; Chen Guo-Qing; Xue Si-Zhong; Zhu Zhuo-Wei; Ma Chao-Qun

    2012-01-01

    The intrinsic optical bistability (OB) of graded core-shell granular composites is investigated. The coated particles are made of cores with gradient dielectric function in c (r) = A(r/a) k and nonlinear shells. In view of the exponential distribution of the core dielectric constant, the potential functions of each region are obtained by solving the Maxwell equations, and the mathematical expressions of electric field in the shells and cores are determined. Numerical study reveals that the optical bistable threshold and the threshold width of the composite medium are dependent on the shell thickness, core dielectric exponent, and power function coefficient. The optical bistable width increases with the decreasing shell thickness and the power exponent and with the increasing power function coefficient

  1. Bistable cholesteric liquid crystal light shutter with multielectrode driving.

    Science.gov (United States)

    Li, Cheng-Chang; Tseng, Heng-Yi; Pai, Tsung-Wei; Wu, Yu-Ching; Hsu, Wen-Hao; Jau, Hung-Chang; Chen, Chun-Wei; Lin, Tsung-Hsien

    2014-08-01

    An electrically activated bistable light shutter that exploits polymer-stabilized cholesteric liquid crystal film was developed. Under double-sided three-terminal electrode driving, the device can be bistable and switched between focal conic and homeotropic textures with a uniform in-plane and vertical electrical field. The transparent state with a transmittance of 80% and the opaque/scattering state with a transmittance of 13% can be realized without any optical compensation film, and each can be simply switched to the other by applying a pulse voltage. Also, gray-scale selection can be performed by varying the applied voltage. The designed energy-saving bistable light shutter can be utilized to preserve privacy and control illumination and the flow of energy.

  2. Neuromorphic transistor achieved by redox reaction of WO3 thin film

    Science.gov (United States)

    Tsuchiya, Takashi; Jayabalan, Manikandan; Kawamura, Kinya; Takayanagi, Makoto; Higuchi, Tohru; Jayavel, Ramasamy; Terabe, Kazuya

    2018-04-01

    An all-solid-state neuromorphic transistor composed of a WO3 thin film and a proton-conducting electrolyte was fabricated for application to next-generation information and communication technology including artificial neural networks. The drain current exhibited a 4-order-of-magnitude increment by redox reaction of the WO3 thin film owing to proton migration. Learning and forgetting characteristics were well tuned by the gate control of WO3 redox reactions owing to the separation of the current reading path and pulse application path in the transistor structure. This technique should lead to the development of versatile and low-power-consumption neuromorphic devices.

  3. Design of a bistable switch to control cellular uptake.

    Science.gov (United States)

    Oyarzún, Diego A; Chaves, Madalena

    2015-12-06

    Bistable switches are widely used in synthetic biology to trigger cellular functions in response to environmental signals. All bistable switches developed so far, however, control the expression of target genes without access to other layers of the cellular machinery. Here, we propose a bistable switch to control the rate at which cells take up a metabolite from the environment. An uptake switch provides a new interface to command metabolic activity from the extracellular space and has great potential as a building block in more complex circuits that coordinate pathway activity across cell cultures, allocate metabolic tasks among different strains or require cell-to-cell communication with metabolic signals. Inspired by uptake systems found in nature, we propose to couple metabolite import and utilization with a genetic circuit under feedback regulation. Using mathematical models and analysis, we determined the circuit architectures that produce bistability and obtained their design space for bistability in terms of experimentally tuneable parameters. We found an activation-repression architecture to be the most robust switch because it displays bistability for the largest range of design parameters and requires little fine-tuning of the promoters' response curves. Our analytic results are based on on-off approximations of promoter activity and are in excellent qualitative agreement with simulations of more realistic models. With further analysis and simulation, we established conditions to maximize the parameter design space and to produce bimodal phenotypes via hysteresis and cell-to-cell variability. Our results highlight how mathematical analysis can drive the discovery of new circuits for synthetic biology, as the proposed circuit has all the hallmarks of a toggle switch and stands as a promising design to control metabolic phenotypes across cell cultures. © 2015 The Author(s).

  4. Excitonic bistabilities, instabilities and chaos in laser-pumped semiconductor

    International Nuclear Information System (INIS)

    Nguyen Ba An; Nguyen Trung Dan; Hoang Xuan Nguyen

    1992-07-01

    The Hurwitz criteria are used for a stability analysis of the steady state excitonic optical bistability curves in a semiconductor pumped by an external laser resonant with the exciton level. Besides the middle branch of the bistability curves which is unstable in the sense of the linear stability theory, we have found other domains of instability in the upper and lower branches of the steady state curves. Numerical results show that a possible route to chaos in the photon-exciton system is period-doubling self-oscillation process. The influence of the presence of free carriers that coexist with the excitons is also discussed. (author). 16 refs, 6 figs

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

    Science.gov (United States)

    Shiraishi, Tetsuya; Matsuyama, Shinako; Kitano, Hiroaki

    2010-01-01

    Protein–protein interaction and gene regulatory networks are likely to be locked in a state corresponding to a disease by the behavior of one or more bistable circuits exhibiting switch-like behavior. Sets of genes could be over-expressed or repressed when anomalies due to disease appear, and the circuits responsible for this over- or under-expression might persist for as long as the disease state continues. This paper shows how a large-scale analysis of network bistability for various human cancers can identify genes that can potentially serve as drug targets or diagnosis biomarkers. PMID:20628618

  6. An Optically Driven Bistable Janus Rotor with Patterned Metal Coatings.

    Science.gov (United States)

    Zong, Yiwu; Liu, Jing; Liu, Rui; Guo, Honglian; Yang, Mingcheng; Li, Zhiyuan; Chen, Ke

    2015-11-24

    Bistable rotation is realized for a gold-coated Janus colloidal particle in an infrared optical trap. The metal coating on the Janus particles are patterned by sputtering gold on a monolayer of closely packed polystyrene particles. The Janus particle is observed to stably rotate in an optical trap. Both the direction and the rate of rotation can be experimentally controlled. Numerical calculations reveal that the bistable rotation is the result of spontaneous symmetry breaking induced by the uneven curvature of the coating patterns on the Janus sphere. Our results thus provide a simple method to construct large quantities of fully functional rotary motors for nano- or microdevices.

  7. Excitonic optical bistability in n-type doped semiconductors

    International Nuclear Information System (INIS)

    Nguyen Ba An; Le Thi Cat Tuong

    1991-07-01

    A resonant monochromatic pump laser generates coherent excitons in an n-type doped semiconductor. Both exciton-exciton and exciton-donor interactions come into play. The former interaction can give rise to the appearance of optical bistability which is heavily influenced by the latter one. When optical bistability occurs at a fixed laser frequency both its holding intensity and hysteresis loop size are shown to decrease with increasing donor concentration. Two possibilities are suggested for experimentally determining one of the two parameters of the system - the exciton-donor coupling constant and the donor concentration, if the other parameter is known beforehand. (author). 36 refs, 2 figs

  8. The Necker-Zeno model for bistable perception.

    Science.gov (United States)

    Atmanspacher, Harald; Filk, Thomas

    2013-10-01

    A novel conceptual framework for theoretical psychology is presented and illustrated for the example of bistable perception. A basic formal feature of this framework is the non-commutativity of operations acting on mental states. A corresponding model for the bistable perception of ambiguous stimuli, the Necker-Zeno model, is sketched and some empirical evidence for it so far is described. It is discussed how a temporal non-locality of mental states, predicted by the model, can be understood and tested. © 2013 Cognitive Science Society, Inc.

  9. THE DENSITY DISTRIBUTION IN TURBULENT BISTABLE FLOWS

    International Nuclear Information System (INIS)

    Gazol, Adriana; Kim, Jongsoo

    2013-01-01

    We numerically study the volume density probability distribution function (n-PDF) and the column density probability distribution function (Σ-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 ∼ –3 ), the n-PDF is well described by a lognormal distribution for an average local Mach number ranging from ∼0.2 to ∼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 ∼> 7.1 cm –3 ) goes from ∼1.1 to ∼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 Σ-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.

  10. Electrical bistabilities and memory stabilities of nonvolatile bistable devices fabricated utilizing C60 molecules embedded in a polymethyl methacrylate layer

    International Nuclear Information System (INIS)

    Cho, Sung Hwan; Lee, Dong Ik; Jung, Jae Hun; Kim, Tae Whan

    2009-01-01

    Current-voltage (I-V) measurements on Al/fullerene (C 60 ) molecules embedded in polymethyl methacrylate/Al devices at 300 K showed a current bistability due to the existence of the C 60 molecules. The on/off ratio of the current bistability for the memory devices was as large as 10 3 . The retention time of the devices was above 2.5 x 10 4 s at room temperature, and cycling endurance tests on these devices indicated that the ON and OFF currents showed no degradation until 50 000 cycles. Carrier transport mechanisms for the nonvolatile bistable devices are described on the basis of the I-V experimental and fitting results.

  11. Bistable flow spectral analysis. Repercussions on jet pumps

    International Nuclear Information System (INIS)

    Gavilan Moreno, C.J.

    2011-01-01

    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

  12. Two optical bistability domains in composites of metal nanoparticles with nonlinear dielectric core

    Energy Technology Data Exchange (ETDEWEB)

    Shewamare, Sisay, E-mail: sisayshewa20@yahoo.com [Department of Physics, Addis Ababa University, P.O. Box 1176, Addis Ababa (Ethiopia); Mal' nev, V.N., E-mail: vadimnmalnev@yahoo.com [Department of Physics, Addis Ababa University, P.O. Box 1176, Addis Ababa (Ethiopia)

    2012-12-15

    It is shown that the local field in metal spherical particles with a dielectric core in an external varying electric field has two maxima at two different frequencies. The second maximum becomes more important with an increment in the metal fraction. Due to the nonlinear dielectric function of the core, the composite of these inclusions may have two optically induced bistability domains at different frequencies. At rather high metal fraction, two bistability domains merge and form one entire bistability domain. The parameters of these domains are studied numerically. The paper focuses on the second bistability domain, which has not been discussed in the literature so far. This domain exists in a comparatively narrow frequency range and its onset fields are lower than those of the first bistability domain. The lowest bistability onset fields are obtained in the entire domain. This peculiarity of the optical induced bistability in the metal composite with small dielectric cores can be attractive for possible applications.

  13. Controllable optical bistability in a three-mode optomechanical system with atom-cavity-mirror couplings

    Science.gov (United States)

    Chen, Bin; Wang, Xiao-Fang; Yan, Jia-Kai; Zhu, Xiao-Fei; Jiang, Cheng

    2018-01-01

    We theoretically investigate the optical bistable behavior in a three-mode optomechanical system with atom-cavity-mirror couplings. The effects of the cavity-pump detuning and the pump power on the bistable behavior are discussed detailedly, the impacts of the atom-pump detuning and the atom-cavity coupling strength on the bistability of the system are also explored, and the influences of the cavity-resonator coupling strength and the cavity decay rate are also taken into consideration. The numerical results demonstrate that by tuning these parameters the bistable behavior of the system can be freely switched on or off, and the threshold of the pump power for the bistability as well as the bistable region width can also be effectively controlled. These results can find potential applications in optical bistable switch in the quantum information processing.

  14. Two optical bistability domains in composites of metal nanoparticles with nonlinear dielectric core

    International Nuclear Information System (INIS)

    Shewamare, Sisay; Mal'nev, V.N.

    2012-01-01

    It is shown that the local field in metal spherical particles with a dielectric core in an external varying electric field has two maxima at two different frequencies. The second maximum becomes more important with an increment in the metal fraction. Due to the nonlinear dielectric function of the core, the composite of these inclusions may have two optically induced bistability domains at different frequencies. At rather high metal fraction, two bistability domains merge and form one entire bistability domain. The parameters of these domains are studied numerically. The paper focuses on the second bistability domain, which has not been discussed in the literature so far. This domain exists in a comparatively narrow frequency range and its onset fields are lower than those of the first bistability domain. The lowest bistability onset fields are obtained in the entire domain. This peculiarity of the optical induced bistability in the metal composite with small dielectric cores can be attractive for possible applications.

  15. Using neuromorphic optical sensors for spacecraft absolute and relative navigation

    Science.gov (United States)

    Shake, Christopher M.

    We develop a novel attitude determination system (ADS) for use on nano spacecraft using neuromorphic optical sensors. The ADS intends to support nano-satellite operations by providing low-cost, low-mass, low-volume, low-power, and redundant attitude determination capabilities with quick and straightforward onboard programmability for real time spacecraft operations. The ADS is experimentally validated with commercial-off-the-shelf optical devices that perform sensing and image processing on the same circuit board and are biologically inspired by insects' vision systems, which measure optical flow while navigating in the environment. The firmware on the devices is modified to both perform the additional biologically inspired task of tracking objects and communicate with a PC/104 form-factor embedded computer running Real Time Application Interface Linux used on a spacecraft simulator. Algorithms are developed for operations using optical flow, point tracking, and hybrid modes with the sensors, and the performance of the system in all three modes is assessed using a spacecraft simulator in the Advanced Autonomous Multiple Spacecraft (ADAMUS) laboratory at Rensselaer. An existing relative state determination method is identified to be combined with the novel ADS to create a self-contained navigation system for nano spacecraft. The performance of the method is assessed in simulation and found not to match the results from its authors using only conditions and equations already published. An improved target inertia tensor method is proposed as an update to the existing relative state method, but found not to perform as expected, but is presented for others to build upon.

  16. Pattern formation in the bistable Gray-Scott model

    DEFF Research Database (Denmark)

    Mazin, W.; Rasmussen, K.E.; Mosekilde, Erik

    1996-01-01

    The paper presents a computer simulation study of a variety of far-from-equilibrium phenomena that can arise in a bistable chemical reaction-diffusion system which also displays Turing and Hopf instabilities. The Turing bifurcation curve and the wave number for the patterns of maximum linear grow...

  17. 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.

  18. 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.

  19. Reversal Negativity and Bistable Stimuli: Attention, Awareness, or Something Else?

    Science.gov (United States)

    Intaite, Monika; Koivisto, Mika; Ruksenas, Osvaldas; Revonsuo, Antti

    2010-01-01

    Ambiguous (or bistable) figures are visual stimuli that have two mutually exclusive perceptual interpretations that spontaneously alternate with each other. Perceptual reversals, as compared with non-reversals, typically elicit a negative difference called reversal negativity (RN), peaking around 250 ms from stimulus onset. The cognitive…

  20. Kerr nonlinearity and plasmonic bistability in graphene nanoribbons

    DEFF Research Database (Denmark)

    Christensen, Thomas; Yan, Wei; Jauho, Antti-Pekka

    2015-01-01

    due to field enhancement, and the total nonlinearity is significantly affected by the field inhomogeneity of the plasmonic excitation. Finally, we discuss the emergence of a plasmonic bistability which exists for energies red-shifted relative to the linear resonance. Our results offer insights...

  1. Drag force actuated bistable microswitches for flow sensing

    NARCIS (Netherlands)

    Kuipers, W.J.; van Baar, J.J.J.; Dijkstra, Marcel; Wiegerink, Remco J.; Lammerink, Theodorus S.J.; de Boer, J.H.; Krijnen, Gijsbertus J.M.

    2006-01-01

    This paper presents bistable microswitches with Au contacts with the aim to combine them with artificial hairs for flow sensing. The Au contacts are applied on both ends of a silicon nitride beam, suspended by a torsional bar at its center. The beam is provided with electrodes for electrostatic

  2. Bistable minimum energy structures (BiMES) for binary robotics

    International Nuclear Information System (INIS)

    Follador, M; Conn, A T; Rossiter, J

    2015-01-01

    Bistable minimum energy structures (BiMES) are devices derived from the union of the concepts of dielectric elastomer minimum energy structures and bistable systems. This article presents this novel approach to active, elastic and bistable structures. BiMES are based on dielectric elastomer actuators (DEAs), which act as antagonists and provide the actuation for switching between the two equilibrium positions. A central elastic beam is the backbone of the structure and is buckled into the minimum energy configurations by the action of the two DEAs. The theory and the model of the device are presented, and also its fabrication process. BiMES are considered as fundamental units for more complex structures, which are presented and fabricated as proof of concept. Two different ways of combining the multiple units are proposed: a parallel configuration, to make a simple gripper, and a serial configuration, to generate a binary device. The possibility of using the bistable system as a continuous bender actuator, by modulating the actuation voltage of the two DEAs, was also investigated. (paper)

  3. Phenomenological approach to bistable behavior of Josephson junctions

    International Nuclear Information System (INIS)

    Nishi, K.; Nara, S.; Hamanaka, K.

    1985-01-01

    The interaction of unbiased Josephson junction with external electromagnetic field in the presence of externally applied uniform magnetic field is theoretically examined by means of phenomenological treatment. It is proposed that an irradiated junction with suitably chosen parameters shows a bistable behavior of voltage across the junction as a function of the radiation intensity

  4. Flexible Metal Oxide/Graphene Oxide Hybrid Neuromorphic Devices on Flexible Conducting Graphene Substrates

    OpenAIRE

    Wan, Chang Jin; Wang, Wei; Zhu, Li Qiang; Liu, Yang Hui; Feng, Ping; Liu, Zhao Ping; Shi, Yi; Wan, Qing

    2016-01-01

    Flexible metal oxide/graphene oxide hybrid multi-gate neuron transistors were fabricated on flexible graphene substrates. Dendritic integrations in both spatial and temporal modes were successfully emulated, and spatiotemporal correlated logics were obtained. A proof-of-principle visual system model for emulating lobula giant motion detector neuron was investigated. Our results are of great interest for flexible neuromorphic cognitive systems.

  5. 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.

  6. Programming time-multiplexed reconfigurable hardware using a scalable neuromorphic compiler.

    Science.gov (United States)

    Minkovich, Kirill; Srinivasa, Narayan; Cruz-Albrecht, Jose M; Cho, Youngkwan; Nogin, Aleksey

    2012-06-01

    Scalability and connectivity are two key challenges in designing neuromorphic hardware that can match biological levels. In this paper, we describe a neuromorphic system architecture design that addresses an approach to meet these challenges using traditional complementary metal-oxide-semiconductor (CMOS) hardware. A key requirement in realizing such neural architectures in hardware is the ability to automatically configure the hardware to emulate any neural architecture or model. The focus for this paper is to describe the details of such a programmable front-end. This programmable front-end is composed of a neuromorphic compiler and a digital memory, and is designed based on the concept of synaptic time-multiplexing (STM). The neuromorphic compiler automatically translates any given neural architecture to hardware switch states and these states are stored in digital memory to enable desired neural architectures. STM enables our proposed architecture to address scalability and connectivity using traditional CMOS hardware. We describe the details of the proposed design and the programmable front-end, and provide examples to illustrate its capabilities. We also provide perspectives for future extensions and potential applications.

  7. 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.

  8. Full Wafer Redistribution and Wafer Embedding as Key Technologies for a Multi-Scale Neuromorphic Hardware Cluster

    OpenAIRE

    Zoschke, Kai; Güttler, Maurice; Böttcher, Lars; Grübl, Andreas; Husmann, Dan; Schemmel, Johannes; Meier, Karlheinz; Ehrmann, Oswin

    2018-01-01

    Together with the Kirchhoff-Institute for Physics(KIP) the Fraunhofer IZM has developed a full wafer redistribution and embedding technology as base for a large-scale neuromorphic hardware system. The paper will give an overview of the neuromorphic computing platform at the KIP and the associated hardware requirements which drove the described technological developments. In the first phase of the project standard redistribution technologies from wafer level packaging were adapted to enable a ...

  9. A High Performance VLSI Computer Architecture For Computer Graphics

    Science.gov (United States)

    Chin, Chi-Yuan; Lin, Wen-Tai

    1988-10-01

    A VLSI computer architecture, consisting of multiple processors, is presented in this paper to satisfy the modern computer graphics demands, e.g. high resolution, realistic animation, real-time display etc.. All processors share a global memory which are partitioned into multiple banks. Through a crossbar network, data from one memory bank can be broadcasted to many processors. Processors are physically interconnected through a hyper-crossbar network (a crossbar-like network). By programming the network, the topology of communication links among processors can be reconfigurated to satisfy specific dataflows of different applications. Each processor consists of a controller, arithmetic operators, local memory, a local crossbar network, and I/O ports to communicate with other processors, memory banks, and a system controller. Operations in each processor are characterized into two modes, i.e. object domain and space domain, to fully utilize the data-independency characteristics of graphics processing. Special graphics features such as 3D-to-2D conversion, shadow generation, texturing, and reflection, can be easily handled. With the current high density interconnection (MI) technology, it is feasible to implement a 64-processor system to achieve 2.5 billion operations per second, a performance needed in most advanced graphics applications.

  10. Monolithic active pixel sensors (MAPS) in a VLSI CMOS technology

    CERN Document Server

    Turchetta, R; Manolopoulos, S; Tyndel, M; Allport, P P; Bates, R; O'Shea, V; Hall, G; Raymond, M

    2003-01-01

    Monolithic Active Pixel Sensors (MAPS) designed in a standard VLSI CMOS technology have recently been proposed as a compact pixel detector for the detection of high-energy charged particle in vertex/tracking applications. MAPS, also named CMOS sensors, are already extensively used in visible light applications. With respect to other competing imaging technologies, CMOS sensors have several potential advantages in terms of low cost, low power, lower noise at higher speed, random access of pixels which allows windowing of region of interest, ability to integrate several functions on the same chip. This brings altogether to the concept of 'camera-on-a-chip'. In this paper, we review the use of CMOS sensors for particle physics and we analyse their performances in term of the efficiency (fill factor), signal generation, noise, readout speed and sensor area. In most of high-energy physics applications, data reduction is needed in the sensor at an early stage of the data processing before transfer of the data to ta...

  11. CAPCAL, 3-D Capacitance Calculator for VLSI Purposes

    International Nuclear Information System (INIS)

    Seidl, Albert; Klose, Helmut; Svoboda, Mildos

    2004-01-01

    1 - Description of program or function: CAPCAL is devoted to the calculation of capacitances of three-dimensional wiring configurations are typically used in VLSI circuits. Due to analogies in the mathematical description also conductance and heat transport problems can be treated by CAPCAL. To handle the problem using CAPCAL same approximations have to be applied to the structure under investigation: - the overall geometry has to be confined to a finite domain by using symmetry-properties of the problem - Non-rectangular structures have to be simplified into an artwork of multiple boxes. 2 - Method of solution: The electrical field is described by the Laplace-equation. The differential equation is discretized by using the finite difference method. NEA-1327/01: The linear equation system is solved by using a combined ADI-multigrid method. NEA-1327/04: The linear equation system is solved by using a conjugate gradient method for CAPCAL V1.3. NEA-1327/05: The linear equation system is solved by using a conjugate gradient method for CAPCAL V1.3. 3 - Restrictions on the complexity of the problem: NEA-1327/01: Certain restrictions of use may arise from the dimensioning of arrays. Field lengths are defined via PARAMETER-statements which can easily by modified. If the geometry of the problem is defined such that Neumann boundaries are dominating the convergence of the iterative equation system solver is affected

  12. 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

  13. A second generation 50 Mbps VLSI level zero processing system prototype

    Science.gov (United States)

    Harris, Jonathan C.; Shi, Jeff; Speciale, Nick; Bennett, Toby

    1994-01-01

    Level Zero Processing (LZP) generally refers to telemetry data processing functions performed at ground facilities to remove all communication artifacts from instrument data. These functions typically include frame synchronization, error detection and correction, packet reassembly and sorting, playback reversal, merging, time-ordering, overlap deletion, and production of annotated data sets. The Data Systems Technologies Division (DSTD) at Goddard Space Flight Center (GSFC) has been developing high-performance Very Large Scale Integration Level Zero Processing Systems (VLSI LZPS) since 1989. The first VLSI LZPS prototype demonstrated 20 Megabits per second (Mbp's) capability in 1992. With a new generation of high-density Application-specific Integrated Circuits (ASIC) and a Mass Storage System (MSS) based on the High-performance Parallel Peripheral Interface (HiPPI), a second prototype has been built that achieves full 50 Mbp's performance. This paper describes the second generation LZPS prototype based upon VLSI technologies.

  14. Design of a Low-Power VLSI Macrocell for Nonlinear Adaptive Video Noise Reduction

    Directory of Open Access Journals (Sweden)

    Sergio Saponara

    2004-09-01

    Full Text Available A VLSI macrocell for edge-preserving video noise reduction is proposed in the paper. It is based on a nonlinear rational filter enhanced by a noise estimator for blind and dynamic adaptation of the filtering parameters to the input signal statistics. The VLSI filter features a modular architecture allowing the extension of both mask size and filtering directions. Both spatial and spatiotemporal algorithms are supported. Simulation results with monochrome test videos prove its efficiency for many noise distributions with PSNR improvements up to 3.8 dB with respect to a nonadaptive solution. The VLSI macrocell has been realized in a 0.18 μm CMOS technology using a standard-cells library; it allows for real-time processing of main video formats, up to 30 fps (frames per second 4CIF, with a power consumption in the order of few mW.

  15. 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......-chip control circuit design and (iii) the integration of on-chip control in the placement and routing design tasks. In this paper we present a design methodology for logic synthesis and physical synthesis of mVLSI biochips that use on-chip control. We show how the proposed methodology can be successfully...... applied to generate biochip layouts with integrated on-chip pneumatic control....

  16. The GLUEchip: A custom VLSI chip for detectors readout and associative memories circuits

    International Nuclear Information System (INIS)

    Amendolia, S.R.; Galeotti, S.; Morsani, F.; Passuello, D.; Ristori, L.; Turini, N.

    1993-01-01

    An associative memory full-custom VLSI chip for pattern recognition has been designed and tested in the past years. It's the AMchip, that contains 128 patterns of 60 bits each. To expand the pattern capacity of an Associative Memory bank, the custom VLSI GLUEchip has been developed. The GLUEchip allows the interconnection of up to 16 AMchips or up to 16 GLUEchips: the resulting tree-like structure works like a single AMchip with an output pipelined structure and a pattern capacity increased by a factor 16 for each GLUEchip used

  17. Digital VLSI design with Verilog a textbook from Silicon Valley Technical Institute

    CERN Document Server

    Williams, John

    2008-01-01

    This unique textbook is structured as a step-by-step course of study along the lines of a VLSI IC design project. In a nominal schedule of 12 weeks, two days and about 10 hours per week, 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. Digital VLSI Design With Verilog is all 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 on the

  18. Controlling the optical bistability and multistability in a two-level pumped-probe system

    International Nuclear Information System (INIS)

    Mahmoudi, Mohammad; Sahrai, Mostafa; Masoumeh Mousavi, Seyede

    2010-01-01

    We study the behavior of the optical bistability (OB) and multistability (OM) in a two-level pumped-probe atomic system by means of a unidirectional ring cavity. We show that the optical bistability in a two-level atomic system can be controlled by adjusting the intensity of the pump field and the detuning between two fields. We find that applying the pumping field decreases the threshold of the optical bistability.

  19. Bistability and self-oscillations effects in a polariton-laser semiconductor microcavity

    International Nuclear Information System (INIS)

    Cotta, E A; Matinaga, F M

    2007-01-01

    We report an experimental observation of polaritonic optical bistability of the laser emission in a planar semiconductor microcavity with a 100 0 A GaAs single quantum well in the strong-coupling regime. The bistability curves show crossings that indicate a competition between a Kerr-like effect induced by the polariton population and thermal effects. Associated with the bistability, laser-like emission occurs at the bare cavity mode

  20. Modeling bistable behaviors in morphing structures through finite element simulations.

    Science.gov (United States)

    Guo, Qiaohang; Zheng, Huang; Chen, Wenzhe; Chen, Zi

    2014-01-01

    Bistable structures, exemplified by the Venus flytrap and slap bracelets, can transit between different configurations upon certain external stimulation. Here we study, through three-dimensional finite element simulations, the bistable behaviors in elastic plates in the absence of terminate loads, but with pre-strains in one (or both) of the two composite layers. Both the scenarios with and without a given geometric mis-orientation angle are investigated, the results of which are consistent with recent theoretical and experimental studies. This work can open ample venues for programmable designs of plant/shell structures with large deformations, with applications in designing bio-inspired robotics for biomedical research and morphing/deployable structures in aerospace engineering.

  1. Coupling-induced oscillations in nonhomogeneous, overdamped, bistable systems

    International Nuclear Information System (INIS)

    Hernandez, Mayra; In, Visarath; Longhini, Patrick; Palacios, Antonio; Bulsara, Adi; Kho, Andy

    2008-01-01

    Coupling-induced oscillations in a homogeneous network of overdamped bistable systems have been previously studied both theoretically and experimentally for a system of N (odd) elements, unidirectionally coupled in a ring topology. In this work, we extend the analysis of this system to include a network of nonhomogeneous elements with respect to the parameter that controls the topology of the potential function and the bistability of each element. In particular, we quantify the effects of the nonhomogeneity on the onset of oscillations and the response of the network to external (assumed to be constant and very small) perturbations, using our (recently developed) coupled core fluxgate magnetometer as a representative system. The potential applications of this work include signal detection and characterization for a large class of sensor systems

  2. Coupling-induced oscillations in nonhomogeneous, overdamped, bistable systems

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez, Mayra [Nonlinear Dynamical Systems Group, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182 (United States)], E-mail: mayra.alina@yahoo.com; In, Visarath [Space and Naval Warfare Systems Center, Code 71730, 53560 Hull Street, San Diego, CA 92152-5001 (United States)], E-mail: visarath.in@navy.mil; Longhini, Patrick [Space and Naval Warfare Systems Center, Code 71730, 53560 Hull Street, San Diego, CA 92152-5001 (United States)], E-mail: longhini@navy.mil; Palacios, Antonio [Nonlinear Dynamical Systems Group, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182 (United States)], E-mail: palacios@euler.sdsu.edu; Bulsara, Adi [Space and Naval Warfare Systems Center, Code 71730, 53560 Hull Street, San Diego, CA 92152-5001 (United States)], E-mail: bulsara@spawar.navy.mil; Kho, Andy [Space and Naval Warfare Systems Center, Code 71730, 53560 Hull Street, San Diego, CA 92152-5001 (United States)], E-mail: kho@spawar.navy.mil

    2008-06-09

    Coupling-induced oscillations in a homogeneous network of overdamped bistable systems have been previously studied both theoretically and experimentally for a system of N (odd) elements, unidirectionally coupled in a ring topology. In this work, we extend the analysis of this system to include a network of nonhomogeneous elements with respect to the parameter that controls the topology of the potential function and the bistability of each element. In particular, we quantify the effects of the nonhomogeneity on the onset of oscillations and the response of the network to external (assumed to be constant and very small) perturbations, using our (recently developed) coupled core fluxgate magnetometer as a representative system. The potential applications of this work include signal detection and characterization for a large class of sensor systems.

  3. A minimal model of burst-noise induced bistability.

    Directory of Open Access Journals (Sweden)

    Johannes Falk

    Full Text Available We investigate the influence of intrinsic noise on stable states of a one-dimensional dynamical system that shows in its deterministic version a saddle-node bifurcation between monostable and bistable behaviour. The system is a modified version of the Schlögl model, which is a chemical reaction system with only one type of molecule. The strength of the intrinsic noise is varied without changing the deterministic description by introducing bursts in the autocatalytic production step. We study the transitions between monostable and bistable behavior in this system by evaluating the number of maxima of the stationary probability distribution. We find that changing the size of bursts can destroy and even induce saddle-node bifurcations. This means that a bursty production of molecules can qualitatively change the dynamics of a chemical reaction system even when the deterministic description remains unchanged.

  4. Mathematical modeling of Myosin induced bistability of Lamellipodial fragments.

    Science.gov (United States)

    Hirsch, S; Manhart, A; Schmeiser, C

    2017-01-01

    For various cell types and for lamellipodial fragments on flat surfaces, externally induced and spontaneous transitions between symmetric nonmoving states and polarized migration have been observed. This behavior is indicative of bistability of the cytoskeleton dynamics. In this work, the Filament Based Lamellipodium Model (FBLM), a two-dimensional, anisotropic, two-phase continuum model for the dynamics of the actin filament network in lamellipodia, is extended by a new description of actin-myosin interaction. For appropriately chosen parameter values, the resulting model has bistable dynamics with stable states showing the qualitative features observed in experiments. This is demonstrated by numerical simulations and by an analysis of a strongly simplified version of the FBLM with rigid filaments and planar lamellipodia at the cell front and rear.

  5. Waterbomb base: a symmetric single-vertex bistable origami mechanism

    International Nuclear Information System (INIS)

    Hanna, Brandon H; Lund, Jason M; Magleby, Spencer P; Howell, Larry L; Lang, Robert J

    2014-01-01

    The origami waterbomb base is a single-vertex bistable origami mechanism that has unique properties which may prove useful in a variety of applications. It also shows promise as a test bed for smart materials and actuation because of its straightforward geometry and multiple phases of motion, ranging from simple to more complex. This study develops a quantitative understanding of the symmetric waterbomb base's kinetic behavior. This is done by completing kinematic and potential energy analyses to understand and predict bistable behavior. A physical prototype is constructed and tested to validate the results of the analyses. Finite element and virtual work analyses based on the prototype are used to explore the locations of the stable equilibrium positions and the force–deflection response. The model results are verified through comparisons to measurements on a physical prototype. The resulting models describe waterbomb base behavior and provide an engineering tool for application development. (paper)

  6. Novel piezoelectric bistable oscillator architecture for wideband vibration energy harvesting

    International Nuclear Information System (INIS)

    Liu, W Q; Badel, A; Formosa, F; Wu, Y P; Agbossou, A

    2013-01-01

    Bistable vibration energy harvesters are attracting more and more interest because of their capability to scavenge energy over a large frequency band. The bistable effect is usually based on magnetic interaction or buckled beams. This paper presents a novel architecture based on amplified piezoelectric structures. This buckled spring–mass architecture allows the energy of the dynamic mass to be converted into electrical energy in the piezoelectric materials as efficiently as possible. Modeling and design are performed and a normalized expression of the harvester behavior is given. Chirp and band-limited noise excitations are used to evaluate the proposed harvester’s performances. Simulation and experimental results are in good agreement. A method of using a spectrum plot for investigating the interwell motion is presented. The effect of the electric load impedance matching strategy is also studied. Results and comparisons with the literature show that the proposed device combines a large bandwidth and a high power density. (paper)

  7. Bistable dark solitons of a cubic-quintic Helmholtz equation

    International Nuclear Information System (INIS)

    Christian, J. M.; McDonald, G. S.; Chamorro-Posada, P.

    2010-01-01

    We provide a report on exact analytical bistable dark spatial solitons of a nonlinear Helmholtz equation with a cubic-quintic refractive-index model. Our analysis begins with an investigation of the modulational instability characteristics of Helmholtz plane waves. We then derive a dark soliton by mapping the desired asymptotic form onto a uniform background field and obtain a more general solution by deploying rotational invariance laws in the laboratory frame. The geometry of the new soliton is explored in detail, and a range of new physical predictions is uncovered. Particular attention is paid to the unified phenomena of arbitrary-angle off-axis propagation and nondegenerate bistability. Crucially, the corresponding solution of paraxial theory emerges in a simultaneous multiple limit. We conclude with a set of computer simulations that examine the role of Helmholtz dark solitons as robust attractors.

  8. Internal optical bistability of quasi-two-dimensional semiconductor nanoheterostructures

    Science.gov (United States)

    Derevyanchuk, Oleksandr V.; Kramar, Natalia K.; Kramar, Valeriy M.

    2018-01-01

    We represent the results of numerical computations of the frequency and temperature domains of possible realization of internal optical bistability in flat quasi-two-dimensional semiconductor nanoheterostructures with a single quantum well (i.e., nanofilms). Particular computations have been made for a nanofilm of layered semiconductor PbI2 embedded in dielectric medium, i.e. ethylene-methacrylic acid (E-MAA) copolymer. It is shown that an increase in the nanofilm's thickness leads to a long-wave shift of the frequency range of the manifestation the phenomenon of bistability, to increase the size of the hysteresis loop, as well as to the expansion of the temperature interval at which the realization of this phenomenon is possible.

  9. Controllable optical bistability and multistability in asymmetric double quantum wells via spontaneously generated coherence

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Yuan; Deng, Li [Department of Applied Physics, East China Jiaotong University, Nanchang, 330013 (China); Chen, Aixi, E-mail: aixichen@ecjtu.jx.cn [Department of Applied Physics, East China Jiaotong University, Nanchang, 330013 (China); Institute for Quantum Computing, University of Waterloo, Ontario N2L 3G1 (Canada)

    2015-02-15

    We investigate the nonlinear optical phenomena of the optical bistability and multistability via spontaneously generated coherence in an asymmetric double quantum well structure coupled by a weak probe field and a controlling field. It is shown that the threshold and hysteresis cycle of the optical bistability can be conveniently controlled only by adjusting the intensity of the SGC or the controlling field. Moreover, switching between optical bistability and multistability can be achieved. These studies may have practical significance for the preparation of optical bistable switching device.

  10. Controllable optical bistability and multistability in asymmetric double quantum wells via spontaneously generated coherence

    International Nuclear Information System (INIS)

    Chen, Yuan; Deng, Li; Chen, Aixi

    2015-01-01

    We investigate the nonlinear optical phenomena of the optical bistability and multistability via spontaneously generated coherence in an asymmetric double quantum well structure coupled by a weak probe field and a controlling field. It is shown that the threshold and hysteresis cycle of the optical bistability can be conveniently controlled only by adjusting the intensity of the SGC or the controlling field. Moreover, switching between optical bistability and multistability can be achieved. These studies may have practical significance for the preparation of optical bistable switching device

  11. A Redox-Active Bistable Molecular Switch Mounted inside a Metal-Organic Framework.

    Science.gov (United States)

    Chen, Qishui; Sun, Junling; Li, Peng; Hod, Idan; Moghadam, Peyman Z; Kean, Zachary S; Snurr, Randall Q; Hupp, Joseph T; Farha, Omar K; Stoddart, J Fraser

    2016-11-02

    We describe the incorporation of a bistable mechanically interlocked molecule (MIM) into a robust Zr-based metal-organic framework (MOF), NU-1000, by employing a post-synthetic functionalization protocol. On average, close to two bistable [2]catenanes can be incorporated per repeating unit of the hexagonal channels of NU-1000. The reversible redox-switching of the bistable [2]catenanes is retained inside the MOF, as evidenced by solid-state UV-vis-NIR reflectance spectroscopy and cyclic voltammetry. This research demonstrates that bistable MIMs are capable of exhibiting robust dynamics inside the nanopores of a MOF.

  12. Modeling Bistable Composite Laminates for Piezoelectric Morphing Structures

    OpenAIRE

    Darryl V. Murray; Oliver J. Myers

    2013-01-01

    A sequential modeling effort for bistable composite laminates for piezoelectric morphing structures is presented. Thin unsymmetric carbon fiber composite laminates are examined for use of morphing structures using piezoelectric actuation. When cooling from the elevated cure temperature to room temperature, these unsymmetric composite laminates will deform. These postcure room temperature deformation shapes can be used as morphing structures. Applying a force to these deformed laminates will c...

  13. Spatial effect on stochastic dynamics of bistable evolutionary games

    International Nuclear Information System (INIS)

    So, Kohaku H Z; Ohtsuki, Hisashi; Kato, Takeo

    2014-01-01

    We consider the lifetimes of metastable states in bistable evolutionary games (coordination games), and examine how they are affected by spatial structure. A semiclassical approximation based on a path integral method is applied to stochastic evolutionary game dynamics with and without spatial structure, and the lifetimes of the metastable states are evaluated. It is shown that the population dependence of the lifetimes is qualitatively different in these two models. Our result indicates that spatial structure can accelerate the transitions between metastable states. (paper)

  14. Dynamic optical bistability in resonantly enhanced Raman generation

    International Nuclear Information System (INIS)

    Novikova, I.; Phillips, D.F.; Zibrov, A.S.; Andre, A.; Walsworth, R.L.

    2004-01-01

    We report observations of novel dynamic behavior in resonantly enhanced stimulated Raman scattering in Rb vapor. In particular, we demonstrate a dynamic hysteresis of the Raman scattered optical field in response to changes of the drive laser field intensity and/or frequency. This effect may be described as a dynamic form of optical bistability resulting from the formation and decay of atomic coherence. We have applied this phenomenon to the realization of an all-optical switch

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

    Science.gov (United States)

    Nuss, Aaron Mischa; Schuster, Franziska; Roselius, Louisa; Klein, Johannes; Bücker, René; Herbst, Katharina; Heroven, Ann Kathrin; Pisano, Fabio; Wittmann, Christoph; Münch, Richard; Müller, Johannes; Jahn, Dieter; Dersch, Petra

    2016-12-01

    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.

  16. 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.

  17. Stochastic dynamics of a delayed bistable system with multiplicative noise

    Energy Technology Data Exchange (ETDEWEB)

    Dung, Nguyen Tien, E-mail: dung-nguyentien10@yahoo.com, E-mail: dungnt@fpt.edu.vn [Department of Mathematics, FPT University, No 8 Ton That Thuyet, My Dinh, Tu Liem, Hanoi (Viet Nam)

    2014-05-15

    In this paper we investigate the properties of a delayed bistable system under the effect of multiplicative noise. We first prove the existence and uniqueness of the positive solution and show that its moments are uniformly bounded. Then, we study stochastic dynamics of the solution in long time, the lower and upper bounds for the paths and an estimate for the average value are provided.

  18. Traveling waves in the discrete fast buffered bistable system.

    Science.gov (United States)

    Tsai, Je-Chiang; Sneyd, James

    2007-11-01

    We study the existence and uniqueness of traveling wave solutions of the discrete buffered bistable equation. Buffered excitable systems are used to model, among other things, the propagation of waves of increased calcium concentration, and discrete models are often used to describe the propagation of such waves across multiple cells. We derive necessary conditions for the existence of waves, and, under some restrictive technical assumptions, we derive sufficient conditions. When the wave exists it is unique and stable.

  19. Bistable flapping of flexible flyers in oscillatory flow

    Science.gov (United States)

    Huang, Yangyang; Kanso, Eva

    2016-11-01

    Biological and bio-inspired flyers move by shape actuation. The direct control of shape variables for locomotory purposes is well studied. Less is known about indirect shape actuation via the fluid medium. Here, we consider a flexible Λ-flyer in oscillatory flow that is free to flap and rotate around its fixed apex. We study its motion in the context of the inviscid vortex sheet model. We first analyze symmetric flapping about the vertical axis of gravity. We find that there is a finite value of the flexibility that maximizes both the flapping amplitude and elastic energy storage. Our results show that rather than resonance, the flyer relies on fluidic effects to optimize these two quantities. We then perturb the flyer away from the vertical and analyze its stability. Four distinct types of rolling behavior are identified: mono-stable, bistable, bistable oscillatory rotations and chaotic dynamics. We categorize these types of behavior in terms of the flyer's and flow parameters. In particular, the transition from mono-stable to bistable behavior occurs at a constant value of the product of the flow amplitude and acceleration. This product can be interpreted as the ratio of fluidic drag to gravity, confirming the fluid role in this transition.

  20. Interplay of bistable kinetics of gene expression during cellular growth

    International Nuclear Information System (INIS)

    Zhdanov, Vladimir P

    2009-01-01

    In cells, the bistable kinetics of gene expression can be observed on the level of (i) one gene with positive feedback between protein and mRNA production, (ii) two genes with negative mutual feedback between protein and mRNA production, or (iii) in more complex cases. We analyse the interplay of two genes of type (ii) governed by a gene of type (i) during cellular growth. In particular, using kinetic Monte Carlo simulations, we show that in the case where gene 1, operating in the bistable regime, regulates mutually inhibiting genes 2 and 3, also operating in the bistable regime, the latter genes may eventually be trapped either to the state with high transcriptional activity of gene 2 and low activity of gene 3 or to the state with high transcriptional activity of gene 3 and low activity of gene 2. The probability to get to one of these states depends on the values of the model parameters. If genes 2 and 3 are kinetically equivalent, the probability is equal to 0.5. Thus, our model illustrates how different intracellular states can be chosen at random with predetermined probabilities. This type of kinetics of gene expression may be behind complex processes occurring in cells, e.g., behind the choice of the fate by stem cells

  1. Bistable switches control memory and plasticity in cellular differentiation

    Science.gov (United States)

    Wang, Lei; Walker, Brandon L.; Iannaccone, Stephen; Bhatt, Devang; Kennedy, Patrick J.; Tse, William T.

    2009-01-01

    Development of stem and progenitor cells into specialized tissues in multicellular organisms involves a series of cell fate decisions. Cellular differentiation in higher organisms is generally considered irreversible, and the idea of developmental plasticity in postnatal tissues is controversial. Here, we show that inhibition of mitogen-activated protein kinase (MAPK) in a human bone marrow stromal cell-derived myogenic subclone suppresses their myogenic ability and converts them into satellite cell-like precursors that respond to osteogenic stimulation. Clonal analysis of the induced osteogenic response reveals ultrasensitivity and an “all-or-none” behavior, hallmarks of a bistable switch mechanism with stochastic noise. The response demonstrates cellular memory, which is contingent on the accumulation of an intracellular factor and can be erased by factor dilution through cell divisions or inhibition of protein synthesis. The effect of MAPK inhibition also exhibits memory and appears to be controlled by another bistable switch further upstream that determines cell fate. Once the memory associated with osteogenic differentiation is erased, the cells regain their myogenic ability. These results support a model of cell fate decision in which a network of bistable switches controls inducible production of lineage-specific differentiation factors. A competitive balance between these factors determines cell fate. Our work underscores the dynamic nature of cellular differentiation and explains mechanistically the dual properties of stability and plasticity associated with the process. PMID:19366677

  2. Brain mechanisms for simple perception and bistable perception.

    Science.gov (United States)

    Wang, Megan; Arteaga, Daniel; He, Biyu J

    2013-08-27

    When faced with ambiguous sensory inputs, subjective perception alternates between the different interpretations in a stochastic manner. Such multistable perception phenomena have intrigued scientists and laymen alike for over a century. Despite rigorous investigations, the underlying mechanisms of multistable perception remain elusive. Recent studies using multivariate pattern analysis revealed that activity patterns in posterior visual areas correlate with fluctuating percepts. However, increasing evidence suggests that vision--and perception at large--is an active inferential process involving hierarchical brain systems. We applied searchlight multivariate pattern analysis to functional magnetic resonance imaging signals across the human brain to decode perceptual content during bistable perception and simple unambiguous perception. Although perceptually reflective activity patterns during simple perception localized predominantly to posterior visual regions, bistable perception involved additionally many higher-order frontoparietal and temporal regions. Moreover, compared with simple perception, both top-down and bottom-up influences were dramatically enhanced during bistable perception. We further studied the intermittent presentation of ambiguous images--a condition that is known to elicit perceptual memory. Compared with continuous presentation, intermittent presentation recruited even more higher-order regions and was accompanied by further strengthened top-down influences but relatively weakened bottom-up influences. Taken together, these results strongly support an active top-down inferential process in perception.

  3. Compact modeling of CRS devices based on ECM cells for memory, logic and neuromorphic applications

    International Nuclear Information System (INIS)

    Linn, E; Ferch, S; Waser, R; Menzel, S

    2013-01-01

    Dynamic physics-based models of resistive switching devices are of great interest for the realization of complex circuits required for memory, logic and neuromorphic applications. Here, we apply such a model of an electrochemical metallization (ECM) cell to complementary resistive switches (CRSs), which are favorable devices to realize ultra-dense passive crossbar arrays. Since a CRS consists of two resistive switching devices, it is straightforward to apply the dynamic ECM model for CRS simulation with MATLAB and SPICE, enabling study of the device behavior in terms of sweep rate and series resistance variations. Furthermore, typical memory access operations as well as basic implication logic operations can be analyzed, revealing requirements for proper spike and level read operations. This basic understanding facilitates applications of massively parallel computing paradigms required for neuromorphic applications. (paper)

  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. 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.

  6. An Adaptable Neuromorphic Model of Orientation Selectivity Based On Floating Gate Dynamics

    Directory of Open Access Journals (Sweden)

    Priti eGupta

    2014-04-01

    Full Text Available 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

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

    OpenAIRE

    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 net...

  8. 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.

  9. 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. PMID:25232314

  10. 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

  11. Optimized pulsed write schemes improve linearity and write speed for low-power organic neuromorphic devices

    Science.gov (United States)

    Keene, Scott T.; Melianas, Armantas; Fuller, Elliot J.; van de Burgt, Yoeri; Talin, A. Alec; Salleo, Alberto

    2018-06-01

    Neuromorphic devices are becoming increasingly appealing as efficient emulators of neural networks used to model real world problems. However, no hardware to date has demonstrated the necessary high accuracy and energy efficiency gain over CMOS in both (1) training via backpropagation and (2) in read via vector matrix multiplication. Such shortcomings are due to device non-idealities, particularly asymmetric conductance tuning in response to uniform voltage pulse inputs. Here, by formulating a general circuit model for capacitive ion-exchange neuromorphic devices, we show that asymmetric nonlinearity in organic electrochemical neuromorphic devices (ENODes) can be suppressed by an appropriately chosen write scheme. Simulations based upon our model suggest that a nonlinear write-selector could reduce the switching voltage and energy, enabling analog tuning via a continuous set of resistance states (100 states) with extremely low switching energy (~170 fJ · µm‑2). This work clarifies the pathway to neural algorithm accelerators capable of parallelism during both read and write operations.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. MemFlash device: floating gate transistors as memristive devices for neuromorphic computing

    Science.gov (United States)

    Riggert, C.; Ziegler, M.; Schroeder, D.; Krautschneider, W. H.; Kohlstedt, H.

    2014-10-01

    Memristive devices are promising candidates for future non-volatile memory applications and mixed-signal circuits. In the field of neuromorphic engineering these devices are especially interesting to emulate neuronal functionality. Therefore, new materials and material combinations are currently investigated, which are often not compatible with Si-technology processes. The underlying mechanisms of the device often remain unclear and are paired with low device endurance and yield. These facts define the current most challenging development tasks towards a reliable memristive device technology. In this respect, the MemFlash concept is of particular interest. A MemFlash device results from a diode configuration wiring scheme of a floating gate transistor, which enables the persistent device resistance to be varied according to the history of the charge flow through the device. In this study, we investigate the scaling conditions of the floating gate oxide thickness with respect to possible applications in the field of neuromorphic engineering. We show that MemFlash cells exhibit essential features with respect to neuromorphic applications. In particular, cells with thin floating gate oxides show a limited synaptic weight growth together with low energy dissipation. MemFlash cells present an attractive alternative for state-of-art memresitive devices. The emulation of associative learning is discussed by implementing a single MemFlash cell in an analogue circuit.

  20. MemFlash device: floating gate transistors as memristive devices for neuromorphic computing

    International Nuclear Information System (INIS)

    Riggert, C; Ziegler, M; Kohlstedt, H; Schroeder, D; Krautschneider, W H

    2014-01-01

    Memristive devices are promising candidates for future non-volatile memory applications and mixed-signal circuits. In the field of neuromorphic engineering these devices are especially interesting to emulate neuronal functionality. Therefore, new materials and material combinations are currently investigated, which are often not compatible with Si-technology processes. The underlying mechanisms of the device often remain unclear and are paired with low device endurance and yield. These facts define the current most challenging development tasks towards a reliable memristive device technology. In this respect, the MemFlash concept is of particular interest. A MemFlash device results from a diode configuration wiring scheme of a floating gate transistor, which enables the persistent device resistance to be varied according to the history of the charge flow through the device. In this study, we investigate the scaling conditions of the floating gate oxide thickness with respect to possible applications in the field of neuromorphic engineering. We show that MemFlash cells exhibit essential features with respect to neuromorphic applications. In particular, cells with thin floating gate oxides show a limited synaptic weight growth together with low energy dissipation. MemFlash cells present an attractive alternative for state-of-art memresitive devices. The emulation of associative learning is discussed by implementing a single MemFlash cell in an analogue circuit. (paper)

  1. High-energy heavy ion testing of VLSI devices for single event ...

    Indian Academy of Sciences (India)

    Unknown

    per describes the high-energy heavy ion radiation testing of VLSI devices for single event upset (SEU) ... The experimental set up employed to produce low flux of heavy ions viz. silicon ... through which they pass, leaving behind a wake of elec- ... for use in Bus Management Unit (BMU) and bulk CMOS ... was scheduled.

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

    KAUST Repository

    Shobak, Hosam; Ghoneim, Mohamed T.; El Boghdady, Nawal; Halawa, Sarah; Iskander, Sophinese M.; Anis, Mohab H.

    2011-01-01

    -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

  3. Implementation of a VLSI Level Zero Processing system utilizing the functional component approach

    Science.gov (United States)

    Shi, Jianfei; Horner, Ward P.; Grebowsky, Gerald J.; Chesney, James R.

    1991-01-01

    A high rate Level Zero Processing system is currently being prototyped at NASA/Goddard Space Flight Center (GSFC). Based on state-of-the-art VLSI technology and the functional component approach, the new system promises capabilities of handling multiple Virtual Channels and Applications with a combined data rate of up to 20 Megabits per second (Mbps) at low cost.

  4. An area-efficient path memory structure for VLSI Implementation of high speed Viterbi decoders

    DEFF Research Database (Denmark)

    Paaske, Erik; Pedersen, Steen; Sparsø, Jens

    1991-01-01

    Path storage and selection methods for Viterbi decoders are investigated with special emphasis on VLSI implementations. Two well-known algorithms, the register exchange, algorithm, REA, and the trace back algorithm, TBA, are considered. The REA requires the smallest number of storage elements...

  5. 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

  6. 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

  7. 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

  8. Take it of leave it : Mechanisms underlying bacterial bistable regulatory networks

    NARCIS (Netherlands)

    Siebring, Jeroen; Sorg, Robin; Herber, Martijn; Kuipers, Oscar; Filloux, Alain A.M.

    2012-01-01

    Bistable switches occur in regulatory networks that can exist in two distinct stable states. Such networks allow distinct switching of individual cells. In bacteria these switches coexist with regulatory networks that respond gradually to environmental input. Bistable switches play key roles in high

  9. Configurational rearrangements of bistable centers in covalent semiconductors - phase transitions of the second type

    International Nuclear Information System (INIS)

    Ivanyukovich, V.A.; Karas', V.I.; Lomako, V.M.

    1989-01-01

    A new radiation configurational-bistable defect diffring from the known similar defects by the fact that it possessestemperature inversion of states is detected in gallium arsenide. Configurational-bistable rearrangements are shown to be considered as phase transitions of the second type

  10. Bistable traveling waves for a competitive-cooperative system with nonlocal delays

    Science.gov (United States)

    Tian, Yanling; Zhao, Xiao-Qiang

    2018-04-01

    This paper is devoted to the study of bistable traveling waves for a competitive-cooperative reaction and diffusion system with nonlocal time delays. The existence of bistable waves is established by appealing to the theory of monotone semiflows and the finite-delay approximations. Then the global stability of such traveling waves is obtained via a squeezing technique and a dynamical systems approach.

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

    Science.gov (United States)

    1983-01-01

    ThB16-1 SELF-BEATING INSTABILITIES IN BISTABLE DEVICES J.A. MARTIN-PEREDA .. M.A. MURIEL DEPARTAMENTO DE ELECTRONICA CUANTICA E.T.S. ING...OPTICAL BISTABLL SYSTEMS J.A. MARTIN PEREDA M.A. MURIEL ; DEPARTAMENIO DE ELECTRONICA CUANTICA E.T.S. ING. TELLCOMUNICACION UNIVERSIDAD POLITECNICA DE

  12. CMOS VLSI Active-Pixel Sensor for Tracking

    Science.gov (United States)

    Pain, Bedabrata; Sun, Chao; Yang, Guang; Heynssens, Julie

    2004-01-01

    An architecture for a proposed active-pixel sensor (APS) and a design to implement the architecture in a complementary metal oxide semiconductor (CMOS) very-large-scale integrated (VLSI) circuit provide for some advanced features that are expected to be especially desirable for tracking pointlike features of stars. The architecture would also make this APS suitable for robotic- vision and general pointing and tracking applications. CMOS imagers in general are well suited for pointing and tracking because they can be configured for random access to selected pixels and to provide readout from windows of interest within their fields of view. However, until now, the architectures of CMOS imagers have not supported multiwindow operation or low-noise data collection. Moreover, smearing and motion artifacts in collected images have made prior CMOS imagers unsuitable for tracking applications. The proposed CMOS imager (see figure) would include an array of 1,024 by 1,024 pixels containing high-performance photodiode-based APS circuitry. The pixel pitch would be 9 m. The operations of the pixel circuits would be sequenced and otherwise controlled by an on-chip timing and control block, which would enable the collection of image data, during a single frame period, from either the full frame (that is, all 1,024 1,024 pixels) or from within as many as 8 different arbitrarily placed windows as large as 8 by 8 pixels each. A typical prior CMOS APS operates in a row-at-a-time ( grolling-shutter h) readout mode, which gives rise to exposure skew. In contrast, the proposed APS would operate in a sample-first/readlater mode, suppressing rolling-shutter effects. In this mode, the analog readout signals from the pixels corresponding to the windows of the interest (which windows, in the star-tracking application, would presumably contain guide stars) would be sampled rapidly by routing them through a programmable diagonal switch array to an on-chip parallel analog memory array. The

  13. Design Implementation and Testing of a VLSI High Performance ASIC for Extracting the Phase of a Complex Signal

    National Research Council Canada - National Science Library

    Altmeyer, Ronald

    2002-01-01

    This thesis documents the research, circuit design, and simulation testing of a VLSI ASIC which extracts phase angle information from a complex sampled signal using the arctangent relationship: (phi=tan/-1 (Q/1...

  14. Linear population allocation by bistable switches in response to transient stimulation.

    Science.gov (United States)

    Srimani, Jaydeep K; Yao, Guang; Neu, John; Tanouchi, Yu; Lee, Tae Jun; You, Lingchong

    2014-01-01

    Many cellular decision processes, including proliferation, differentiation, and phenotypic switching, are controlled by bistable signaling networks. In response to transient or intermediate input signals, these networks allocate a population fraction to each of two distinct states (e.g. OFF and ON). While extensive studies have been carried out to analyze various bistable networks, they are primarily focused on responses of bistable networks to sustained input signals. In this work, we investigate the response characteristics of bistable networks to transient signals, using both theoretical analysis and numerical simulation. We find that bistable systems exhibit a common property: for input signals with short durations, the fraction of switching cells increases linearly with the signal duration, allowing the population to integrate transient signals to tune its response. We propose that this allocation algorithm can be an optimal response strategy for certain cellular decisions in which excessive switching results in lower population fitness.

  15. Optical bistability via quantum interference from incoherent pumping and spontaneous emission

    International Nuclear Information System (INIS)

    Sahrai, M.; Asadpour, S.H.; Sadighi-Bonabi, R.

    2011-01-01

    We theoretically investigate the optical bistability (OB) in a V-type three-level atomic system confined in a unidirectional ring cavity via incoherent pumping field. It is shown that the threshold of optical bistability can be controlled by the rate of an incoherent pumping field and by interference mechanism arising from the spontaneous emission and incoherent pumping field. We demonstrate that the optical bistability converts to optical multi-stability (OM) by the quantum interference mechanism. - Highlights: → We modulate the optical bistability (OB) in a four-level N-type atomic system. → The threshold of optical bistability can be controlled by the quantum interferences. → OB converts to optical multi-stability (OM) by the quantum interferences. → We discuss the effect of an incoherent pumping field on reduction of OB threshold.

  16. A review of the recent research on vibration energy harvesting via bistable systems

    International Nuclear Information System (INIS)

    Harne, R L; Wang, K W

    2013-01-01

    The investigation of the conversion of vibrational energy into electrical power has become a major field of research. In recent years, bistable energy harvesting devices have attracted significant attention due to some of their unique features. Through a snap-through action, bistable systems transition from one stable state to the other, which could cause large amplitude motion and dramatically increase power generation. Due to their nonlinear characteristics, such devices may be effective across a broad-frequency bandwidth. Consequently, a rapid engagement of research has been undertaken to understand bistable electromechanical dynamics and to utilize the insight for the development of improved designs. This paper reviews, consolidates, and reports on the major efforts and findings documented in the literature. A common analytical framework for bistable electromechanical dynamics is presented, the principal results are provided, the wide variety of bistable energy harvesters are described, and some remaining challenges and proposed solutions are summarized. (topical review)

  17. Stochastic resonance in bistable systems driven by harmonic noise

    International Nuclear Information System (INIS)

    Neiman, A.; Schimansky-Geier, L.

    1994-01-01

    We study stochastic resonance in a bistable system which is excited simultaneously by white and harmonic noise which we understand as the signal. In our case the spectral line of the signal has a finite width as it occurs in many real situations. Using techniques of cumulant analysis as well as computer simulations we find that the effect of stochastic resonance is preserved in the case of harmonic noise excitation. Moreover we show that the width of the spectral line of the signal at the output can be decreased via stochastic resonance. The last could be of importance in the practical using of the stochastic resonance

  18. Bistability By Self-Reflection In A Saturable Absorber

    Science.gov (United States)

    Roso-Franco, Luis

    1987-01-01

    Propagation of laser light through a saturable absorber is theoretically studied. Computed steady state solutions of the Maxwell equations describing the unidimensional propagation of a plane monochromatic wave without introducing the slowly-varying envelope approximation are presented showing how saturation effects can influence the absorption of the field. At a certain range of refractive index and extintion coefficients, computed solutions display a very susprising behaviour, and a self-reflected wave appears inside the absorber. This can be useful for a new kind of biestable device, similar to a standard bistable cavity but with the back mirror self-induced by the light.

  19. The tunable bistable and multistable memory effect in polymer nanowires

    International Nuclear Information System (INIS)

    Rahman, Atikur; Sanyal, Milan K

    2008-01-01

    Tunable bistable and multistable resistance switching in conducting polymer nanowires has been reported. These wires show reproducible switching transition under several READ-WRITE-ERASE cycles. The switching is observed at low temperature and the ON/OFF resistance ratio for the voltage biased switching transition was found to be more than 10 3 . Current biased measurements show lower ON/OFF ratio and some of the nanowires exhibit a multistable switching transition in current biased measurements. The threshold voltage for switching and the ON/OFF resistance ratio can be tuned by changing doping concentration of the nanowires

  20. Electron transfer dynamics of bistable single-molecule junctions

    DEFF Research Database (Denmark)

    Danilov, A.V; Kubatkin, S.; Kafanov, S. G.

    2006-01-01

    We present transport measurements of single-molecule junctions bridged by a molecule with three benzene rings connected by two double bonds and with thiol end-groups that allow chemical binding to gold electrodes. The I-V curves show switching behavior between two distinct states. By statistical ...... analysis of the switching events, we show that a 300 meV mode mediates the transition between the two states. We propose that breaking and reformation of a S-H bond in the contact zone between molecule and electrode explains the observed bistability....

  1. 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.

  2. Atom-loss-induced quantum optical bi-stability switch

    International Nuclear Information System (INIS)

    Wu Bao-Jun; Cui Fu-Cheng

    2012-01-01

    We investigate the nonlinear dynamics of a system composed of a cigar-shaped Bose—Einstein condensate and an optical cavity with the two sides coupled dispersively. By adopting discrete-mode approximation for the condensate, taking atom loss as a necessary part of the model to analyze the evolution of the system, while using trial and error method to find out steady states of the system as a reference, numerical simulation demonstrates that with a constant pump, atom loss will trigger a quantum optical bi-stability switch, which predicts a new interesting phenomenon for experiments to verify

  3. 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.

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

    International Nuclear Information System (INIS)

    Hassan, S.S.; Sharaby, Y.A.; Ali, M.F.M.; Joshi, A.

    2012-01-01

    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.

  5. Bistable Helmholtz solitons in cubic-quintic materials

    International Nuclear Information System (INIS)

    Christian, J. M.; McDonald, G. S.; Chamorro-Posada, P.

    2007-01-01

    We propose a nonlinear Helmholtz equation for modeling the evolution of broad optical beams in media with a cubic-quintic intensity-dependent refractive index. This type of nonlinearity is appropriate for some semiconductor materials, glasses, and polymers. Exact analytical soliton solutions are presented that describe self-trapped nonparaxial beams propagating at any angle with respect to the reference direction. These spatially symmetric solutions are, to the best of our knowledge, the first bistable Helmholtz solitons to be derived. Accompanying conservation laws (both integral and particular forms) are also reported. Numerical simulations investigate the stability of the solitons, which appear to be remarkably robust against perturbations

  6. Bistable switching in dual-frequency liquid crystals

    Energy Technology Data Exchange (ETDEWEB)

    Palto, S. P., E-mail: palto@online.ru; Barnik, M I [Russian Academy of Sciences, Shubnikov Institute of Crystallography (Russian Federation)

    2006-06-15

    Various bistable switching modes in nematic liquid crystals with frequency inversion of the sign of dielectric anisotropy are revealed and investigated. Switching between states with different helicoidal distributions of the director field of a liquid crystal, as well as between uniform and helicoidal states, is realized by dual-frequency waveforms of a driving voltage. A distinctive feature of the dual-frequency switching is that the uniform planar distribution of the director field may correspond to a thermodynamically equilibrium state, and the chirality of an LC is not a necessary condition for switching to a helicoidal state.

  7. Entire solutions for bistable lattice differential equations with obstacles

    CERN Document Server

    Hoffman, Aaron; Vleck, E S Van

    2018-01-01

    The authors consider scalar lattice differential equations posed on square lattices in two space dimensions. Under certain natural conditions they show that wave-like solutions exist when obstacles (characterized by "holes") are present in the lattice. Their work generalizes to the discrete spatial setting the results obtained in Berestycki, Hamel, and Matuno (2009) for the propagation of waves around obstacles in continuous spatial domains. The analysis hinges upon the development of sub and super-solutions for a class of discrete bistable reaction-diffusion problems and on a generalization of a classical result due to Aronson and Weinberger that concerns the spreading of localized disturbances.

  8. Noticeable positive Doppler effect on optical bistability in an N-type active Raman gain atomic system

    International Nuclear Information System (INIS)

    Chang Zeng-Guang; Zhang Jing-Tao; Niu Yue-Ping; Gong Shang-Qing

    2012-01-01

    We theoretically investigate the Doppler effect on optical bistability in an N-type active Raman gain atomic system inside an optical ring cavity. It is shown that the Doppler effect can greatly enhance the dispersion and thus create the bistable behaviour or greatly increase the bistable region, which has been known as the positive Doppler effect on optical bistability. In addition, we find that a positive Doppler effect can change optical bistability from the hybrid dispersion-gain type to a dispersive type

  9. High-precision shape representation using a neuromorphic vision sensor with synchronous address-event communication interface

    Science.gov (United States)

    Belbachir, A. N.; Hofstätter, M.; Litzenberger, M.; Schön, P.

    2009-10-01

    A synchronous communication interface for neuromorphic temporal contrast vision sensors is described and evaluated in this paper. This interface has been designed for ultra high-speed synchronous arbitration of a temporal contrast image sensors pixels' data. Enabling high-precision timestamping, this system demonstrates its uniqueness for handling peak data rates and preserving the main advantage of the neuromorphic electronic systems, that is high and accurate temporal resolution. Based on a synchronous arbitration concept, the timestamping has a resolution of 100 ns. Both synchronous and (state-of-the-art) asynchronous arbiters have been implemented in a neuromorphic dual-line vision sensor chip in a standard 0.35 µm CMOS process. The performance analysis of both arbiters and the advantages of the synchronous arbitration over asynchronous arbitration in capturing high-speed objects are discussed in detail.

  10. High-precision shape representation using a neuromorphic vision sensor with synchronous address-event communication interface

    International Nuclear Information System (INIS)

    Belbachir, A N; Hofstätter, M; Litzenberger, M; Schön, P

    2009-01-01

    A synchronous communication interface for neuromorphic temporal contrast vision sensors is described and evaluated in this paper. This interface has been designed for ultra high-speed synchronous arbitration of a temporal contrast image sensors pixels' data. Enabling high-precision timestamping, this system demonstrates its uniqueness for handling peak data rates and preserving the main advantage of the neuromorphic electronic systems, that is high and accurate temporal resolution. Based on a synchronous arbitration concept, the timestamping has a resolution of 100 ns. Both synchronous and (state-of-the-art) asynchronous arbiters have been implemented in a neuromorphic dual-line vision sensor chip in a standard 0.35 µm CMOS process. The performance analysis of both arbiters and the advantages of the synchronous arbitration over asynchronous arbitration in capturing high-speed objects are discussed in detail

  11. 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 (H 2 L2') 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 (H 2 L5') 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.

  12. Computing with networks of spiking neurons on a biophysically motivated floating-gate based neuromorphic integrated circuit.

    Science.gov (United States)

    Brink, S; Nease, S; Hasler, P

    2013-09-01

    Results are presented from several spiking network experiments performed on a novel neuromorphic integrated circuit. The networks are discussed in terms of their computational significance, which includes applications such as arbitrary spatiotemporal pattern generation and recognition, winner-take-all competition, stable generation of rhythmic outputs, and volatile memory. Analogies to the behavior of real biological neural systems are also noted. The alternatives for implementing the same computations are discussed and compared from a computational efficiency standpoint, with the conclusion that implementing neural networks on neuromorphic hardware is significantly more power efficient than numerical integration of model equations on traditional digital hardware. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Optical bistability and limiting in polymer dispersed liquid crystal

    Energy Technology Data Exchange (ETDEWEB)

    Yshino, K.; Tagawa, A.; Sadohara, Y.; Ozaki, M. (Osaka University, Osaka (Japan). Faculty of Engineering); Munezawa, T. (Ajinomoto Co. Inc., Tokyo (Japan)); Nomura, Y. (Takiron Co. Ltd., Osaka (Japan))

    1991-04-15

    The linear electro-optical effect of polymer dispersed liquid crystal (PDLC) and the nonlinear optical response of electrically feedbacked PDLC were studied. Electro-optical limiting and bistability were observed in PDLCs with negative and positive feedback, respectively. In the PDLC film with positive feedback gain, an optical hysteresis loop shifted toward a high intensity region with decreasing magnitude of the feedback gain. The switching between high and low transmission states in an optical bistable region was realized by controlling incident light, and the on-off switching by superimposing light pulse on incident light for an extremely short period (several hundreds {mu}s). As the light pulse was strong, the minimum pulse width required for switching was as short as 500 {mu}s or less. The on-off switching was also realized by shutting out the incident light for a period equivalent to the pulse width. Slower response times of the PDLC film required longer minimum pulse widths. 12 refs., 11 figs.

  14. Bistability and displacement fluctuations in a quantum nanomechanical oscillator

    Science.gov (United States)

    Avriller, R.; Murr, B.; Pistolesi, F.

    2018-04-01

    Remarkable features have been predicted for the mechanical fluctuations at the bistability transition of a classical oscillator coupled capacitively to a quantum dot [Micchi et al., Phys. Rev. Lett. 115, 206802 (2015), 10.1103/PhysRevLett.115.206802]. These results have been obtained in the regime ℏ ω0≪kBT ≪ℏ Γ , where ω0, T , and Γ are the mechanical resonating frequency, the temperature, and the tunneling rate, respectively. A similar behavior could be expected in the quantum regime of ℏ Γ ≪kBT ≪ℏ ω0 . We thus calculate the energy- and displacement-fluctuation spectra and study their behavior as a function of the electromechanical coupling constant when the system enters the Frank-Condon regime. We find that in analogy with the classical case, the energy-fluctuation spectrum and the displacement spectrum widths show a maximum for values of the coupling constant at which a mechanical bistability is established.

  15. 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.

  16. 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.

  17. A new concept for active bistable twisting structures

    Science.gov (United States)

    Schultz, Marc R.

    2005-05-01

    A novel type of morphing structure capable of a large change in shape with a small energy input is discussed in this paper. The considered structures consist of two curved shells that are joined in a specific manner to form a bistable airfoil-like structure. The two stable shapes have a difference in axial twist, and the structure may be transformed between the stable shapes by a simple snap-through action. The benefit of a bistable structure of this type is that, if the stable shapes are operational shapes, power is needed only to transform the structure from one shape to another. The discussed structures could be used in aerodynamic applications such as morphing wings, or as aerodynamic control surfaces. The investigation discussed in this paper considers both experiment and finite-element analysis. Several graphite-epoxy composite and one steel device were created as proof-of-concept models. To demonstrate active control of these structures, piezocomposite actuators were applied to one of the composite structures and used to transform the structure between stable shapes. The analysis was used to compare the predicted shapes with the experimental shapes, and to study how changes to the geometric input values affected the shape and operational characteristics of the structures. The predicted shapes showed excellent agreement with the experimental shapes, and the results of the parametric study suggest that the shapes and the snap-through characteristics can be easily tailored to meet specific needs.

  18. A Reliable Bistable Board Implementation through I/O Redundancy

    International Nuclear Information System (INIS)

    Kim, Min Gyu; Chung, Tae Hyok; Lee, Youn Sang; Kim, Tae Hee; Song, Seung Hwan

    2010-01-01

    Nuclear power plant safety systems and related equipment used in the design, including an accident in all driving conditions that must be proven In addition, the safety-related equipment that is derived according to the digitization of the safety equipment is the most important factors. Therefore, it is necessary to prove that the device was satisfied the requirements for a given performance for safety-related digital equipment for the life of the installation. These proven is done through the process, design verification of the equipment, production management, such as installation and maintenance. Among other things, it is most important to implement of the performance and reliability features the safety-related equipment in the design phase. In this paper, Bistable Board implemented to generate a ESF sign-on signal throughout the signal processing of input signal from sensors. Also, for the reliable signal input and output, I/O Module that implements the redundancy increases the reliability of the Bistable Board , to verify the performance of safety-related equipment

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

    Science.gov (United States)

    Zhao, Xiang; Ouyang, Qi; Wang, Hongli

    2015-11-01

    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.

  20. Model-based design of bistable cell factories for metabolic engineering.

    Science.gov (United States)

    Srinivasan, Shyam; Cluett, William R; Mahadevan, Radhakrishnan

    2018-04-15

    Metabolism can exhibit dynamic phenomena like bistability due to the presence of regulatory motifs like the positive feedback loop. As cell factories, microorganisms with bistable metabolism can have a high and a low product flux at the two stable steady states, respectively. The exclusion of metabolic regulation and network dynamics limits the ability of pseudo-steady state stoichiometric models to detect the presence of bistability, and reliably assess the outcomes of design perturbations to metabolic networks. Using kinetic models of metabolism, we assess the change in the bistable characteristics of the network, and suggest designs based on perturbations to the positive feedback loop to enable the network to produce at its theoretical maximum rate. We show that the most optimal production design in parameter space, for a small bistable metabolic network, may exist at the boundary of the bistable region separating it from the monostable region of low product fluxes. The results of our analysis can be broadly applied to other bistable metabolic networks with similar positive feedback network topologies. This can complement existing model-based design strategies by providing a smaller number of feasible designs that need to be tested in vivo. http://lmse.biozone.utoronto.ca/downloads/. krishna.mahadevan@utoronto.ca. Supplementary data are available at Bioinformatics online.

  1. Synapse-centric mapping of cortical models to the SpiNNaker neuromorphic architecture

    Directory of Open Access Journals (Sweden)

    James Courtney Knight

    2016-09-01

    Full Text Available While the adult human brain has approximately 8.8x10^10 neurons, this number is dwarfed by its 1x10^15 synapses. From the point of view of neuromorphic engineering and neural simulation in general this makes the simulation of these synapses a particularly complex problem. SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Current solutions for simulating spiking neural networks on SpiNNaker are heavily inspired by work on distributed high-performance computing. However, while SpiNNaker shares many characteristics with such distributed systems, its component nodes have much more limited resources and, as the system lacks global synchronization, the computation performed on each node must complete within a fixed time step. We first analyze the performance of the current SpiNNaker neural simulation software and identify several problems that occur when it is used to simulate networks of the type often used to model the cortex which contain large numbers of sparsely connected synapses. We then present a new, more flexible approach for mapping the simulation of such networks to SpiNNaker which solves many of these problems. Finally we analyze the performance of our new approach using both benchmarks, designed to represent cortical connectivity, and larger, functional cortical models. In a benchmark network where neurons receive input from 8000 STDP synapses, our new approach allows more neurons to be simulated on each SpiNNaker core than has been previously possible. We also demonstrate that the largest plastic neural network previously simulated on neuromorphic hardware can be run in real time using our new approach: double the speed that was previously achieved. Additionally this network contains two types of plastic synapse which previously had to be trained separately but, using our new approach, can be trained simultaneously.

  2. Training and operation of an integrated neuromorphic network based on metal-oxide memristors

    Science.gov (United States)

    Prezioso, M.; Merrikh-Bayat, F.; Hoskins, B. D.; Adam, G. C.; Likharev, K. K.; Strukov, D. B.

    2015-05-01

    Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 1014 synapses, makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging. To provide comparable complexity while operating much faster and with manageable power dissipation, networks based on circuits combining complementary metal-oxide-semiconductors (CMOSs) and adjustable two-terminal resistive devices (memristors) have been developed. In such circuits, the usual CMOS stack is augmented with one or several crossbar layers, with memristors at each crosspoint. There have recently been notable improvements in the fabrication of such memristive crossbars and their integration with CMOS circuits, including first demonstrations of their vertical integration. Separately, discrete memristors have been used as artificial synapses in neuromorphic networks. Very recently, such experiments have been extended to crossbar arrays of phase-change memristive devices. The adjustment of such devices, however, requires an additional transistor at each crosspoint, and hence these devices are much harder to scale than metal-oxide memristors, whose nonlinear current-voltage curves enable transistor-free operation. Here we report the experimental implementation of transistor-free metal-oxide memristor crossbars, with device variability sufficiently low to allow operation of integrated neural networks, in a simple network: a single-layer perceptron (an algorithm for linear classification). The network can be taught in situ using a coarse-grain variety of the delta rule algorithm to perform the perfect classification of 3 × 3-pixel black/white images into three classes (representing letters). This demonstration is an important step towards much larger and more complex memristive neuromorphic networks.

  3. Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform.

    Science.gov (United States)

    Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B

    2016-01-01

    Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks.

  4. 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.

  5. 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.

  6. VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability.

    Science.gov (United States)

    Feng, Lichen; Li, Zunchao; Wang, Yuanfa

    2018-02-01

    Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (VLSI) design based on the nonlinear support vector machine (SVM). The proposed design mainly consists of a feature extraction (FE) module and an SVM module. The FE module performs the three-level Daubechies discrete wavelet transform to fit the physiological bands of the electroencephalogram (EEG) signal and extracts the time-frequency domain features reflecting the nonstationary signal properties. The SVM module integrates the modified sequential minimal optimization algorithm with the table-driven-based Gaussian kernel to enable efficient on-chip learning. The presented design is verified on an Altera Cyclone II field-programmable gate array and tested using the two publicly available EEG datasets. Experiment results show that the designed VLSI system improves the detection accuracy and training efficiency.

  7. 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.

  8. 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.

  9. An analog VLSI real time optical character recognition system based on a neural architecture

    International Nuclear Information System (INIS)

    Bo, G.; Caviglia, D.; Valle, M.

    1999-01-01

    In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system

  10. An analog VLSI real time optical character recognition system based on a neural architecture

    Energy Technology Data Exchange (ETDEWEB)

    Bo, G.; Caviglia, D.; Valle, M. [Genoa Univ. (Italy). Dip. of Biophysical and Electronic Engineering

    1999-03-01

    In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system.

  11. First results from a silicon-strip detector with VLSI readout

    International Nuclear Information System (INIS)

    Anzivino, G.; Horisberger, R.; Hubbeling, L.; Hyams, B.; Parker, S.; Breakstone, A.; Litke, A.M.; Walker, J.T.; Bingefors, N.

    1986-01-01

    A 256-strip silicon detector with 25 μm strip pitch, connected to two 128-channel NMOS VLSI chips (Microplex), has been tested using straight-through tracks from a ruthenium beta source. The readout channels have a pitch of 47.5 μm. A single multiplexed output provides voltages proportional to the integrated charge from each strip. The most probable signal height from the beta traversals is approximately 14 times the rms noise in any single channel. (orig.)

  12. 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.

  13. Bistable resistive memory behavior in gelatin-CdTe quantum dot composite film

    Science.gov (United States)

    Vallabhapurapu, Sreedevi; Rohom, Ashwini; Chaure, N. B.; Du, Shengzhi; Srinivasan, Ananthakrishnan

    2018-05-01

    Bistable memory behavior has been observed for the first time in gelatin type A thin film dispersed with functionalized CdTe quantum dots. The two terminal device with the polymer nanocomposite layer sandwiched between an indium tin oxide coated glass plate and an aluminium top electrode performs as a bistable resistive random access memory module. Butterfly shaped (O-shaped with a hysteresis in forward and reverse sweeps) current-voltage response is observed in this device. The conduction mechanism leading to the bistable electrical switching has been deduced to be a combination of ohmic and electron hopping.

  14. Bistability Analysis of Excitatory-Inhibitory Neural Networks in Limited-Sustained-Activity Regime

    International Nuclear Information System (INIS)

    Ni Yun; Wu Liang; Wu Dan; Zhu Shiqun

    2011-01-01

    Bistable behavior of neuronal complex networks is investigated in the limited-sustained-activity regime when the network is composed of excitatory and inhibitory neurons. The standard stability analysis is performed on the two metastable states separately. Both theoretical analysis and numerical simulations show consistently that the difference between time scales of excitatory and inhibitory populations can influence the dynamical behaviors of the neuronal networks dramatically, leading to the transition from bistable behaviors with memory effects to the collapse of bistable behaviors. These results may suggest one possible neuronal information processing by only tuning time scales. (interdisciplinary physics and related areas of science and technology)

  15. Optical nonlinearity and bistability in the bound exciton energy range of CdS

    International Nuclear Information System (INIS)

    Hoenig, T.; Gutowski, J.

    1988-01-01

    Under high excitation conditions thick CdS samples show pronounced broad-band nonlinear transmission in the bound exciton region and up to a wavelength of about 515 nm at cryo-temperatures. This behavior is only explainable in a model based on impurity neutralization and bound exciton creation. The suitability of these nonlinearities to yield optical bistability will be shown. Bistable operation is investigated in dependence of crystal thickness, impurity concentration, excitation density, wavelength, and temperature. A strong correlation to acceptor-bound exciton generation is obtained, and the explanation of this bistable operation fits well with that of the above mentioned transmission behavior. (author)

  16. 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.

  17. 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.

  18. Neuromorphic optical sensor chip with color change-intensity change disambiguation

    Science.gov (United States)

    Fu, ZhenHong; Mao, Rui; Cartwright, Alexander N.; Titus, Albert H.

    2010-02-01

    In this paper, we describe the development of a novel, retina-like neuromorphic chip that has an array of two types of retina 'cells' arranged to mimic the fovea structure in certain animals. One of the two retina cell types performs irradiance detection and the other can perform color detection. Together, via the two parallel pathways the retina chip can perform color change intensity change disambiguation (CCICD). The irradiance detection cell has a wide-dynamic detection range that spans almost 3 orders of magnitude. The color detection cell has a buried double junction (BDJ) photodiode as the photoreceptor followed by two parallel logarithmic I-V convertors. The output from this is a color response which has at least a 50nm resolution for wavelengths from 400nm to 900nm. With these two cells, the array can perform color change -intensity change disambiguation (CCICD) to determine if a change in the output of the irradiance pathway is because of irradiance change, color change, or both. This biological retina-like neuromorphic sensor array is implemented in ON-SEMI 0.5μm technology, a standard CMOS fabrication process available at MOSIS.

  19. Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform

    Directory of Open Access Journals (Sweden)

    Massimiliano eGiulioni

    2016-02-01

    Full Text Available We demonstrate robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission and follows the basic theoretical principles presented in (Benosman et al. 2014: the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. The same basic principle is embedded in the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina. Mimicking those cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. We built a 3x3 test grid of independent detectors, each observing a different portion of the scene, so that our final output is a spike train encoding a 3x3 optical flow vector field. In this work we focus on the architectural aspects, and we demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene.

  20. Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks.

    Science.gov (United States)

    Lee, Wang Wei; Kukreja, Sunil L; Thakor, Nitish V

    2017-01-01

    This paper presents a neuromorphic tactile encoding methodology that utilizes a temporally precise event-based representation of sensory signals. We introduce a novel concept where touch signals are characterized as patterns of millisecond precise binary events to denote pressure changes. This approach is amenable to a sparse signal representation and enables the extraction of relevant features from thousands of sensing elements with sub-millisecond temporal precision. We also proposed measures adopted from computational neuroscience to study the information content within the spiking representations of artificial tactile signals. Implemented on a state-of-the-art 4096 element tactile sensor array with 5.2 kHz sampling frequency, we demonstrate the classification of transient impact events while utilizing 20 times less communication bandwidth compared to frame based representations. Spiking sensor responses to a large library of contact conditions were also synthesized using finite element simulations, illustrating an 8-fold improvement in information content and a 4-fold reduction in classification latency when millisecond-precise temporal structures are available. Our research represents a significant advance, demonstrating that a neuromorphic spatiotemporal representation of touch is well suited to rapid identification of critical contact events, making it suitable for dynamic tactile sensing in robotic and prosthetic applications.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. Delay induced stability switch, multitype bistability and chaos in an intraguild predation model.

    Science.gov (United States)

    Shu, Hongying; Hu, Xi; Wang, Lin; Watmough, James

    2015-12-01

    In many predator-prey models, delay has a destabilizing effect and induces oscillations; while in many competition models, delay does not induce oscillations. By analyzing a rather simple delayed intraguild predation model, which combines both the predator-prey relation and competition, we show that delay in intraguild predation models promotes very complex dynamics. The delay can induce stability switches exhibiting a destabilizing role as well as a stabilizing role. It is shown that three types of bistability are possible: one stable equilibrium coexists with another stable equilibrium (node-node bistability); one stable equilibrium coexists with a stable periodic solution (node-cycle bistability); one stable periodic solution coexists with another stable periodic solution (cycle-cycle bistability). Numerical simulations suggest that delay can also induce chaos in intraguild predation models.

  6. A novel optic bistable device with very low threshold intensity using photorefractive films

    Science.gov (United States)

    Wang, Sean X.; Sun, Yuankun; Trivedi, Sudhir B.; Li, Guifang

    1994-08-01

    Brimrose Corporation of America reports the successful completion of the SBIR Phase I research in low-threshold intensity optical bistable devices using photorefractive nonlinearity. A thin photorefractive film optical bistable device was proposed in the Phase I proposal. The feasibility of this device was theoretically investigated. The theoretical feasibility study formulates the materials requirements in such a kind of configuration for Phase II research. In addition, we have proposed and investigated another configuration of optical bistable devices that do not require advanced photorefractive materials, namely, the self-pumped phase conjugator. We have successfully demonstrated a low-threshold optical bistable operation in a KNSBN:CU crystal. To the best of our knowledge, the threshold of 650 mW/sq. cm is the lowest of its kind to be achieved so far.

  7. Innovative Energy Harvester Design Using Bistable Mechanism With Compensational Springs In Gravity Field

    International Nuclear Information System (INIS)

    Vysotskyi, Bogdan; Parrain, Fabien; Lefeuvre, Elie; Aubry, Denis; Gaucher, Philippe

    2016-01-01

    The purpose of the presented work is to introduce the novel design of electrostatic energy harvester using bistable mechanism with compensational springs in gravity field capable of providing the output of several μW under the excitation of extremely small amplitude (up to 0.2g) and low frequency (10-100Hz). Presented energy harvester uses the bistable hysteresis modification to achieve low-frequency low-amplitude sensibility. It was demonstrated with finite element modelling (FEM) that hysteresis width produced by bistability is changing with a constant linear coefficient as a function of a compensational spring stiffness and thus a device sensitivity could be adjusted to the minimum point for the amplitude of external excitation. Further, highly non-linear bistable double curved beam mechanism assures the high sensitivity in frequencial domain due to the non-defined bandwidth. The equivalent circuit technique is used for simulating the device performance. (paper)

  8. Geometric and potential dynamics interpretation of the optic ring resonator bistability

    Science.gov (United States)

    Chiangga, S.; Chittha, T.; Frank, T. D.

    2015-07-01

    The optical bistability is a fundamental nonlinear feature of the ring resonator. A geometric and potential dynamics interpretation of the bistability is given. Accordingly, the bistability of the nonlinear system is shown to be a consequence of geometric laws of vector calculus describing the resonator ring. In contrast, the so-called transcendental relations that have been obtained in the literature in order to describe the optical wave are interpreted in terms of potential dynamical systems. The proposed novel interpretation provides new insights into the nature of the ring resonator optical bistability. The fundamental work by Rukhlenko, Premaratne and Agrawal (2010) as well as a more recent study by Chiangga, Pitakwongsaporn, Frank and Yupapin (2013) are considered.

  9. Bistable output from a coupled-resonator vertical-cavity laser diode

    International Nuclear Information System (INIS)

    Fischer, A. J.; Choquette, K. D.; Chow, W. W.; Allerman, A. A.; Geib, K.

    2000-01-01

    We report a monolithic coupled-resonator vertical-cavity laser with an ion-implanted top cavity and a selectively oxidized bottom cavity which exhibits bistable behavior in the light output versus injection current. Large bistability regions over current ranges as wide as 18 mA have been observed with on/off contrast ratios of greater than 20 dB. The position and width of the bistability region can be varied by changing the bias to the top cavity. Switching between on and off states can be accomplished with changes as small as 250 μW to the electrical power applied to the top cavity. The bistable behavior is the response of the nonlinear susceptibility in the top cavity to the changes in the bottom intracavity laser intensity as the bottom cavity reaches the thermal rollover point

  10. Harnessing the bistable composite shells to design a tunable phononic band gap structure

    Science.gov (United States)

    Li, Yi; Xu, Yanlong

    2018-02-01

    By proposing a system composed of an array of bistable composite shells immersed in air, we develop a new class of periodic structure to control the propagation of sound. Through numerical investigation, we find that the acoustic band gap of this system can be switched on and off by triggering the snap through deformation of the bistable composite shells. The shape of cross section and filling fraction of unit cell can be altered by different number of bistable composite shells, and they have strong impact on the position and width of the band gap. The proposed concept paves the way of using the bistable structures to design a new class of metamaterials that can be enable to manipulate sound.

  11. Microscopic observation of zenithal bistable switching in nematic devices with different surface relief structures

    International Nuclear Information System (INIS)

    Uche, C; Elston, S J; Parry-Jones, L A

    2005-01-01

    Nematic liquid crystals have been shown to exhibit zenithal electro-optic bistability in devices containing sinusoidal and deformed sinusoidal gratings. Recently it has been shown that zenithal bistable states can also be supported at isolated edges of square gratings. In this paper, we present microscopic observations of bistability in cells containing sinusoidal gratings and long-pitch square gratings. We have also investigated a novel display based on square wells. High frame-rate video microscopy was used to obtain time-sequenced images when the devices were switched with monopolar pulses. These show that zenithal bistable switching can occur by two different processes: (i) domain growth (observed in cells containing sinusoidal gratings) and (ii) homogenous switching (observed in cells containing isolated edges

  12. Optical bistability in the oscillation of an inhomogeneously broadened quasi-three-level laser

    International Nuclear Information System (INIS)

    Liu, Junhai; Tian, Xueping

    2013-01-01

    A theoretical modeling analysis is presented to study the optical bistability exhibited in the oscillation of an inhomogeneously broadened quasi-three-level laser. All the major characteristics of optical bistability depend on two normalized parameters, f and x a , which are defined by f = I sat,a /I sat,m and x a = 2α a0 p a /δ and are related to measurable properties of the laser medium. In comparison with the case of a homogeneously broadened laser, the essential condition for the occurrence of such bistability, f a /(x a + 1), turns out to be the same, whereas the intensities at the up- and down-thresholds are substantially increased and the bistability range is reduced. (paper)

  13. A bistable switch in dynamic thiodepsipeptide folding and template-directed ligation.

    Science.gov (United States)

    Mukherjee, Rakesh; Cohen-Luria, Rivka; Wagner, Nathaniel; Ashkenasy, Gonen

    2015-10-12

    Bistable reaction networks provide living cells with chemically controlled mechanisms for long-term memory storage. Such networks are also often switchable and can be flipped from one state to the other. We target here a major challenge in systems chemistry research, namely developing synthetic, non-enzymatic, networks that mimic such a complex function. Therefore, we describe a dynamic network that depending on initial thiodepsipeptide concentrations leads to one of two distinct steady states. This bistable system is readily switched by applying the appropriate stimuli. The relationship between the reaction network topology and its capacity to invoke bistability is then analyzed by control experiments and theory. We suggest that demonstrating bistable behavior using synthetic networks further highlights their possible role in early evolution, and may shine light on potential utility for novel applications, such as chemical memories. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Angular dependence of the exchange bias for the bistable state

    Energy Technology Data Exchange (ETDEWEB)

    Bai, Yuhao [College of Physics and Electronic Information, Shanxi Normal University, Linfen 041004 (China); Research College of materials science, Shanxi Normal University, Linfen 041004 (China); Xu, Xiaohong, E-mail: xuxh@dns.sxnu.edu.cn [Research College of materials science, Shanxi Normal University, Linfen 041004 (China); Key Laboratory of Magnetic Molecules and Magnetic Information Materials, Ministry of Education, Shanxi Normal University, Linfen 041004 (China)

    2017-06-15

    The angular dependence of the exchange bias (ADEB) has been investigated in detail when the exchange-coupled ferromagnetic (FM)/antiferromagnetic (AFM) bilayer is in the bistable state. Complete and incomplete jump phenomena were found at the intrinsic easy and hard axes, when they pass through two special positions making the angular deviation of 58.2826° and 121.7174° from the easy axis of the uniaxial anisotropy, respectively. The combination of these different types of the jump phenomena at the intrinsic easy and hard axes yields five distinct types of the ADEB. The physical condition for each type of ADEB is established. Additionally, the extreme value problem of the exchange bias field and coercivity are also discussed, which is an important technological issue in the design of the magnetoresistive and spintronic devices. These results enable us to make a comprehensive understanding of the experimental ADEB curves.

  15. 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.

  16. Controllable optical bistability and multistability in a graphene monolayer system

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Duo, E-mail: zhangduo10@126.com [School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan 430023 (China); Sun, Zhaoyu [School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan 430023 (China); Ding, Chunling [School of Physics and Electronics, Henan University, Kaifeng 475004 (China); Yu, Rong [School of Science, Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan 430073 (China); Yang, Xiaoxue [Wuhan National Laboratory for Optoelectronics and School of Physics, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2016-02-15

    We theoretically investigate the behavior of optical bistability (OB) and optical multistability (OM) in a graphene monolayer system driven by an elliptically polarized control field and a right-hand circularly polarized probe field. Our numerical results show that it is easy to realize the transition from OB to OM or vice versa by adjusting the frequency detunings of the probe field and the control field, as well as the polarization-dependent phase difference between the two components of the control laser field. The influences of the intensity of the control field and the cooperation parameter on the OB behavior are also discussed in detail. These results may provide some new possibilities for technological applications in optoelectronics and solid-state quantum information science.

  17. Coherent-feedback-induced controllable optical bistability and photon blockade

    International Nuclear Information System (INIS)

    Liu, Yu-Long; Liu, Zhong-Peng; Zhang, Jing

    2015-01-01

    It is well known that some nonlinear phenomena such as strong photon blockade are difficult to observe in optomechanical systems with current experimental technology. Here we present a coherent feedback control strategy in which a linear cavity is coherently controlled by an optomechanical controller in a feedback manner. The coherent feedback loop transfers quantum nonlinearity from the controller to the controlled cavity causing destructive quantum interference to occur, and making it possible to observe strong nonlinear effects. With the help of the coherent feedback loop, large and tunable bistability and strong photon blockade of the cavity modes can be achieved even in the optomechanical weak coupling regime. Additionally, the coherent feedback loop leads to two-photon and multiphoton tunnelings for the controlled linear cavity, which are also typical quantum nonlinear phenomena. We hope that our work can give new perspectives on engineering nonlinear interactions in quantum systems. (paper)

  18. Oscillatory bistability of real-space transfer in semiconductor heterostructures

    Science.gov (United States)

    Do˙ttling, R.; Scho˙ll, E.

    1992-01-01

    Charge transport parallel to the layers of a modulation-doped GaAs/AlxGa1-xAs heterostructure is studied theoretically. The heating of electrons by the applied electric field leads to real-space transfer of electrons from the GaAs into the adjacent AlxGa1-xAs layer. For sufficiently large dc bias, spontaneous periodic 100-GHz current oscillations, and bistability and hysteretic switching transitions between oscillatory and stationary states are predicted. We present a detailed investigation of complex bifurcation scenarios as a function of the bias voltage U0 and the load resistance RL. For large RL subcritical Hopf bifurcations and global bifurcations of limit cycles are displayed.

  19. Optical bistability of optical fiber ring doped by Erbium and quantum dots

    International Nuclear Information System (INIS)

    Safari, S.; Tofighi, S.; Bahrampour, A.; Sajad, B.; Shahshahani, F.

    2012-01-01

    In this paper, theoretical analysis of the steady state behavior of the optical bistability in an optical fiber ring doped by Erbium and quantum dots is presented. The up and down switching power is calculated and the dependence of the switching power on different fiber ring parameters is investigated. The switching power for this type of optical bistability device is obtained much lower than the fiber ring which its half length is doped by Erbium ion.

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

    Directory of Open Access Journals (Sweden)

    Veith Weilnhammer

    2017-05-01

    Full Text Available 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

  1. Optical bistability of a thin film of resonant atoms in a phase-sensitive thermostate

    International Nuclear Information System (INIS)

    Basharov, A.M.

    1995-01-01

    It is shown theoretically that when a thin film of two-level atoms interacting with a resonant coherent electromagnetic wave is additionally illuminated with a squeezed field, a bistable transmission/reflection regime for coherent waves is obtained. This regime depends strongly on the phase difference between the coherent and the squeezed fields. New regimes, including a bistable regime, for the interaction of a coherent field with a film of resonant atoms are predicted based on this phenomenon. 14 refs., 5 figs

  2. Optical bistability in a single-sided cavity coupled to a quantum channel

    Science.gov (United States)

    Payravi, M.; Solookinejad, Gh; Jabbari, M.; Nafar, M.; Ahmadi Sangachin, E.

    2018-06-01

    In this paper, we discuss the long wavelength optical reflection and bistable behavior of an InGaN/GaN quantum dot nanostructure coupled to a single-sided cavity. It is found that due to the presence of a strong coupling field, the reflection coefficient can be controlled at long wavelength, which is essential for adjusting the threshold of reflected optical bistability. Moreover, the phase shift features of the reflection pulse inside an electromagnetically induced transparency window are also discussed.

  3. Bistability of heat transfer of a viscous liquid under conditions of flow channel

    International Nuclear Information System (INIS)

    Melkikh, A.V.; Seleznev, V.D.

    2001-01-01

    The heat exchange model for a viscous liquid flowing under the pressure drop effect in a tube, surrounded by the medium with a lower temperature, is considered. It is shown that the system bistable behavior is possible by availability of the liquid viscosity exponential dependence on the temperature and by negligible dissipative heat release. The transitions between cold and hot flows in this case should proceed by a jump. The liquid and channel parameters, whereby the bistability may be observed, are determined [ru

  4. Heat dissipation and information flow for delayed bistable Langevin systems near coherence resonance.

    Science.gov (United States)

    Xiao, Tiejun

    2016-11-01

    In this paper, stochastic thermodynamics of delayed bistable Langevin systems near coherence resonance is discussed. We calculate the heat dissipation rate and the information flow of a delayed bistable Langevin system under various noise intensities. Both the heat dissipation rate and the information flow are found to be bell-shaped functions of the noise intensity, which implies that coherence resonance manifests itself in the thermodynamic properties.

  5. Bistable laser device with multiple coupled active vertical-cavity resonators

    Science.gov (United States)

    Fischer, Arthur J.; Choquette, Kent D.; Chow, Weng W.

    2003-08-19

    A new class of bistable coupled-resonator vertical-cavity semiconductor laser devices has been developed. These bistable laser devices can be switched, either electrically or optically, between lasing and non-lasing states. A switching signal with a power of a fraction of a milliwatt can change the laser output of such a device by a factor of a hundred, thereby enabling a range of optical switching and data encoding applications.

  6. 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

  7. Evidence for distinct mechanisms underlying attentional priming and sensory memory for bistable perception.

    Science.gov (United States)

    Brinkhuis, M A B; Kristjánsson, Á; Brascamp, J W

    2015-08-01

    Attentional selection in visual search paradigms and perceptual selection in bistable perception paradigms show functional similarities. For example, both are sensitive to trial history: They are biased toward previously selected targets or interpretations. We investigated whether priming by target selection in visual search and sensory memory for bistable perception are related. We did this by presenting two trial types to observers. We presented either ambiguous spheres that rotated over a central axis and could be perceived as rotating in one of two directions, or search displays in which the unambiguously rotating target and distractor spheres closely resembled the two possible interpretations of the ambiguous stimulus. We interleaved both trial types within experiments, to see whether priming by target selection during search trials would affect the perceptual outcome of bistable perception and, conversely, whether sensory memory during bistable perception would affect target selection times during search. Whereas we found intertrial repetition effects among consecutive search trials and among consecutive bistable trials, we did not find cross-paradigm effects. Thus, even though we could ascertain that our experiments robustly elicited processes of both search priming and sensory memory for bistable perception, these same experiments revealed no interaction between the two.

  8. Cell individuality: the bistable gene expression of the type III secretion system in Dickeya dadantii 3937.

    Science.gov (United States)

    Zeng, Quan; Laiosa, Michael D; Steeber, Douglas A; Biddle, Eulandria M; Peng, Quan; Yang, Ching-Hong

    2012-01-01

    Dickeya dadantii 3937 is a gram-negative phytopathogenic bacterium that expresses genes encoding a type III secretion system (T3SS) in a bistable pattern when cultured in a homogeneous minimal media. In this work, we further characterized the bistable gene expression of T3SS at the single-cell level. We demonstrated that bistable expression of the HrpL-regulon genes, such as hrpA and hrpN, is controlled by the same regulatory mechanism. We also showed that the expression level of the T3SS master regulatory gene hrpL plays an important role in the development of the bistable expression of hrpA. A high expression level of hrpL is required but unable to guarantee the high-state expression of hrpA in a cell. In addition, bistable expression patterns of T3SS genes in other gram-negative pathogens of the Enterobacteriaceae and Pseudomonadaceae families were also described in this study. This suggests that the T3SS bistability might be a conserved population behavior in several gram-negative bacterial pathogens.

  9. Investigation of a bistable dual-stage vibration isolator under harmonic excitation

    International Nuclear Information System (INIS)

    Yang, Kai; Huang, Hai; Harne, R L; Wang, K W

    2014-01-01

    This study explores the steady-state performance of a dual-stage vibration isolator, which is configured by a bistable oscillator and a linear oscillator. The potential force of the bistable stage comprises negative linear and positive cubic nonlinear stiffnesses such that the two restoring force contributions may counterbalance to minimize dynamic force transmission. By applying a first-order harmonic balance, it is predicted that the bistable dual-stage isolator may significantly outperform an equivalent pure linear dual-stage isolator. This conclusion is verified through a series of numerical investigations. Following a parametric study, design guidelines are detailed to achieve performance improvements. Then, the ‘valley’ response, which is the special phenomenon of the bistable dual-stage isolator due to the counterbalance of the negative linear and positive nonlinear potential forces, is revealed and quantitatively explained. Numerical studies demonstrate the role of initial conditions, and it is shown that the likelihood of beneficial single periodic valley and intra-well responses for isolation purposes can be increased by greater bistable stage damping. Finally, a bistable dual-stage isolator prototype is developed and tested, and the numerical and experimental results verify the theoretical predictions. (paper)

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

    International Nuclear Information System (INIS)

    Zhang, Chuanyi; Zhang, Weifeng

    2015-01-01

    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

  11. The Independent and Shared Mechanisms of Intrinsic Brain Dynamics: Insights From Bistable Perception

    Directory of Open Access Journals (Sweden)

    Teng Cao

    2018-04-01

    Full Text Available In bistable perception, constant input leads to alternating perception. The dynamics of the changing perception reflects the intrinsic dynamic properties of the “unconscious inferential” process in the brain. Under the same condition, individuals differ in how fast they experience the perceptual alternation. In this study, testing many forms of bistable perception in a large number of observers, we investigated the key question of whether there is a general and common mechanism or multiple and independent mechanisms that control the dynamics of the inferential brain. Bistable phenomena tested include binocular rivalry, vase-face, Necker cube, moving plaid, motion induced blindness, biological motion, spinning dancer, rotating cylinder, Lissajous-figure, rolling wheel, and translating diamond. Switching dynamics for each bistable percept was measured in 100 observers. Results show that the switching rates of subsets of bistable percept are highly correlated. The clustering of dynamic properties of some bistable phenomena but not an overall general control of switching dynamics implies that the brain’s inferential processes are both shared and independent – faster in constructing 3D structure from motion does not mean faster in integrating components into an objects.

  12. Bulk chirality effect for symmetric bistable switching of liquid crystals on topologically self-patterned degenerate anchoring surface.

    Science.gov (United States)

    Park, Min-Kyu; Joo, Kyung-Il; Kim, Hak-Rin

    2017-06-26

    We demonstrate a bistable switching liquid crystal (LC) mode utilizing a topologically self-structured dual-groove surface for degenerated easy axes of LC anchoring. In our study, the effect of the bulk elastic distortion of the LC directors on the bistable anchoring surface is theoretically analyzed for balanced bistable states based on a free energy diagram. By adjusting bulk LC chirality, we developed ideally symmetric and stable bistable anchoring and switching properties, which can be driven by a low in-plane pulsed field of about 0.7 V/µm. The fabricated device has a contrast ratio of 196:1.

  13. The effect of magnetic field on bistability in 1D photonic crystal doped by magnetized plasma and coupled nonlinear defects

    International Nuclear Information System (INIS)

    Mehdian, H.; Mohammadzahery, Z.; Hasanbeigi, A.

    2014-01-01

    In this work, we study the defect mode and bistability behavior of 1-D photonic band gap structure with magnetized plasma and coupled nonlinear defects. The transfer matrix method has been employed to investigate the magnetic field effect on defect mode frequency and bistability threshold. The obtained results show that the frequency of defect mode and bistability threshold can be altered, without changing the structure of the photonic multilayer. Therefore, the bistability behavior of the subjected structure in the presence of magnetized plasma can be utilized in manufacturing wide frequency range devices

  14. Influence of Fano interference and incoherent processes on optical bistability in a four-level quantum dot nanostructure

    International Nuclear Information System (INIS)

    Hossein Asadpour, Seyyed; Solookinejad, G; Panahi, M; Ahmadi Sangachin, E

    2016-01-01

    Role of Fano interference and incoherent pumping field on optical bistability in a four-level designed InGaN/GaN quantum dot nanostructure embedded in a unidirectional ring cavity are analyzed. It is found that intensity threshold of optical bistability can be manipulated by Fano interference. It is shown that incoherent pumping fields make the threshold of optical bistability behave differently by Fano interference. Moreover, in the presence of Fano interference the medium becomes phase-dependent. Therefore, the relative phase of applied fields can affect the behaviors of optical bistability and intensity threshold can be controlled easily. (paper)

  15. 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.

  16. Initial beam test results from a silicon-strip detector with VLSI readout

    International Nuclear Information System (INIS)

    Adolphsen, C.; Litke, A.; Schwarz, A.

    1986-01-01

    Silicon detectors with 256 strips, having a pitch of 25 μm, and connected to two 128 channel NMOS VLSI chips each (Microplex), have been tested in relativistic charged particle beams at CERN and at the Stanford Linear Accelerator Center. The readout chips have an input channel pitch of 47.5 μm and a single multiplexed output which provides voltages proportional to the integrated charge from each strip. The most probable signal height from minimum ionizing tracks was 15 times the rms noise in any single channel. Two-track traversals with a separation of 100 μm were cleanly resolved

  17. New domain for image analysis: VLSI circuits testing, with Romuald, specialized in parallel image processing

    Energy Technology Data Exchange (ETDEWEB)

    Rubat Du Merac, C; Jutier, P; Laurent, J; Courtois, B

    1983-07-01

    This paper describes some aspects of specifying, designing and evaluating a specialized machine, Romuald, for the capture, coding, and processing of video and scanning electron microscope (SEM) pictures. First the authors present the functional organization of the process unit of romuald and its hardware, giving details of its behaviour. Then they study the capture and display unit which, thanks to its flexibility, enables SEM images coding. Finally, they describe an application which is now being developed in their laboratory: testing VLSI circuits with new methods: sem+voltage contrast and image processing. 15 references.

  18. 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.

  19. Positron emission tomographic images and expectation maximization: A VLSI architecture for multiple iterations per second

    International Nuclear Information System (INIS)

    Jones, W.F.; Byars, L.G.; Casey, M.E.

    1988-01-01

    A digital electronic architecture for parallel processing of the expectation maximization (EM) algorithm for Positron Emission tomography (PET) image reconstruction is proposed. Rapid (0.2 second) EM iterations on high resolution (256 x 256) images are supported. Arrays of two very large scale integration (VLSI) chips perform forward and back projection calculations. A description of the architecture is given, including data flow and partitioning relevant to EM and parallel processing. EM images shown are produced with software simulating the proposed hardware reconstruction algorithm. Projected cost of the system is estimated to be small in comparison to the cost of current PET scanners

  20. FILTRES: a 128 channels VLSI mixed front-end readout electronic development for microstrip detectors

    International Nuclear Information System (INIS)

    Anstotz, F.; Hu, Y.; Michel, J.; Sohler, J.L.; Lachartre, D.

    1998-01-01

    We present a VLSI digital-analog readout electronic chain for silicon microstrip detectors. The characteristics of this circuit have been optimized for the high resolution tracker of the CERN CMS experiment. This chip consists of 128 channels at 50 μm pitch. Each channel is composed by a charge amplifier, a CR-RC shaper, an analog memory, an analog processor, an output FIFO read out serially by a multiplexer. This chip has been processed in the radiation hard technology DMILL. This paper describes the architecture of the circuit and presents test results of the 128 channel full chain chip. (orig.)

  1. Techniques for Computing the DFT Using the Residue Fermat Number Systems and VLSI

    Science.gov (United States)

    Truong, T. K.; Chang, J. J.; Hsu, I. S.; Pei, D. Y.; Reed, I. S.

    1985-01-01

    The integer complex multiplier and adder over the direct sum of two copies of a finite field is specialized to the direct sum of the rings of integers modulo Fermat numbers. Such multiplications and additions can be used in the implementation of a discrete Fourier transform (DFT) of a sequence of complex numbers. The advantage of the present approach is that the number of multiplications needed for the DFT can be reduced substantially over the previous approach. The architectural designs using this approach are regular, simple, expandable and, therefore, naturally suitable for VLSI implementation.

  2. Conditional bistability, a generic cellular mnemonic mechanism for robust and flexible working memory computations.

    Science.gov (United States)

    Rodriguez, Guillaume; Sarazin, Matthieu; Clemente, Alexandra; Holden, Stephanie; Paz, Jeanne T; Delord, Bruno

    2018-04-30

    Persistent neural activity, the substrate of working memory, is thought to emerge from synaptic reverberation within recurrent networks. However, reverberation models do not robustly explain fundamental dynamics of persistent activity, including high-spiking irregularity, large intertrial variability, and state transitions. While cellular bistability may contribute to persistent activity, its rigidity appears incompatible with persistent activity labile characteristics. Here, we unravel in a cellular model a form of spike-mediated conditional bistability that is robust, generic and provides a rich repertoire of mnemonic computations. Under asynchronous synaptic inputs of the awakened state, conditional bistability generates spiking/bursting episodes, accounting for the irregularity, variability and state transitions characterizing persistent activity. This mechanism has likely been overlooked because of the sub-threshold input it requires and we predict how to assess it experimentally. Our results suggest a reexamination of the role of intrinsic properties in the collective network dynamics responsible for flexible working memory. SIGNIFICANCE STATEMENT This study unravels a novel form of intrinsic neuronal property, i.e. conditional bistability. We show that, thanks of its conditional character, conditional bistability favors the emergence of flexible and robust forms of persistent activity in PFC neural networks, in opposition to previously studied classical forms of absolute bistability. Specifically, we demonstrate for the first time that conditional bistability 1) is a generic biophysical spike-dependent mechanism of layer V pyramidal neurons in the PFC and that 2) it accounts for essential neurodynamical features for the organisation and flexibility of PFC persistent activity (the large irregularity and intertrial variability of the discharge and its organization under discrete stable states), which remain unexplained in a robust fashion by current models

  3. 2D MoS2 Neuromorphic Devices for Brain-Like Computational Systems.

    Science.gov (United States)

    Jiang, Jie; Guo, Junjie; Wan, Xiang; Yang, Yi; Xie, Haipeng; Niu, Dongmei; Yang, Junliang; He, Jun; Gao, Yongli; Wan, Qing

    2017-08-01

    Hardware implementation of artificial synapses/neurons with 2D solid-state devices is of great significance for nanoscale brain-like computational systems. Here, 2D MoS 2 synaptic/neuronal transistors are fabricated by using poly(vinyl alcohol) as the laterally coupled, proton-conducting electrolytes. Fundamental synaptic functions, such as an excitatory postsynaptic current, paired-pulse facilitation, and a dynamic filter for information transmission of biological synapse, are successfully emulated. Most importantly, with multiple input gates and one modulatory gate, spiking-dependent logic operation/modulation, multiplicative neural coding, and neuronal gain modulation are also experimentally demonstrated. The results indicate that the intriguing 2D MoS 2 transistors are also very promising for the next-generation of nanoscale neuromorphic device applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Neuromorphic Audio-Visual Sensor Fusion on a Sound-Localising Robot

    Directory of Open Access Journals (Sweden)

    Vincent Yue-Sek Chan

    2012-02-01

    Full Text Available This paper presents the first robotic system featuring audio-visual sensor fusion with neuromorphic sensors. We combine a pair of silicon cochleae and a silicon retina on a robotic platform to allow the robot to learn sound localisation through self-motion and visual feedback, using an adaptive ITD-based sound localisation algorithm. After training, the robot can localise sound sources (white or pink noise in a reverberant environment with an RMS error of 4 to 5 degrees in azimuth. In the second part of the paper, we investigate the source binding problem. An experiment is conducted to test the effectiveness of matching an audio event with a corresponding visual event based on their onset time. The results show that this technique can be quite effective, despite its simplicity.

  5. Ab Initio Molecular-Dynamics Simulation of Neuromorphic Computing in Phase-Change Memory Materials.

    Science.gov (United States)

    Skelton, Jonathan M; Loke, Desmond; Lee, Taehoon; Elliott, Stephen R

    2015-07-08

    We present an in silico study of the neuromorphic-computing behavior of the prototypical phase-change material, Ge2Sb2Te5, using ab initio molecular-dynamics simulations. Stepwise changes in structural order in response to temperature pulses of varying length and duration are observed, and a good reproduction of the spike-timing-dependent plasticity observed in nanoelectronic synapses is demonstrated. Short above-melting pulses lead to instantaneous loss of structural and chemical order, followed by delayed partial recovery upon structural relaxation. We also investigate the link between structural order and electrical and optical properties. These results pave the way toward a first-principles understanding of phase-change physics beyond binary switching.

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

    DEFF Research Database (Denmark)

    Farkhani, Hooman; Tohidi, Mohammad; Farkhani, Sadaf

    2017-01-01

    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...... energy consumption and delay of such NCSs. In this paper, a new real-time sensing (RTS) circuit is proposed to track the MTJ state and terminate stimulation phase immediately after MTJ switching. This leads to significant degradation in energy consumption and delay of NCS. The simulation results using...... a 65-nm CMOS technology and a 40-nm MTJ technology confirm that the energy consumption of a RTS-based NCS is improved by 50% in comparison with a typical NCS. Moreover, utilizing RTS circuit improves the overall speed of an NCS by 2.75x....

  7. 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.

  8. 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.

  9. 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 states

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. Rac1 and RhoA: Networks, loops and bistability.

    Science.gov (United States)

    Nguyen, Lan K; Kholodenko, Boris N; von Kriegsheim, Alex

    2016-08-17

    Cell migration requires a precise temporal and spatial coordination of several processes which allow the cell to efficiently move. The extension and retraction of membrane protrusion, as well as adhesion are controlled by the Rho-family small GTPases. Two members of the family, Rac1 and RhoA, can show opposite behaviors and spatial localisations, with RhoA being active toward the rear of the cell and regulating its retraction during migration, whereas Rac1 is active toward the front of the cell. In addition to the spatial segregation, RhoA and Rac1 activity at the leading edge of the cells has an element of temporal segregation, with RhoA and Rac1 activities peaking at separate points during the migratory cycle of protrusion and retraction. Elements of this separation have been explained by the presence of 2 mutually inhibitory feedbacks, where Rac1 inhibits RhoA and RhoA in turn can inhibit Rac1. Recently, it was shown that Rac1 and RhoA activity and downstream signaling respond in a bistable manner to perturbations of this network.

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

    Science.gov (United States)

    Nadin, Grégoire; Strugarek, Martin; Vauchelet, Nicolas

    2018-05-01

    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.

  18. Nonlinear response and bistability of driven ion acoustic waves

    Science.gov (United States)

    Akbari-Moghanjoughi, M.

    2017-08-01

    The hydrodynamic model is used to obtain a generalized pseudoforce equation through which the nonlinear response of periodically driven ion acoustic waves is studied in an electron-ion plasma with isothermal and adiabatic ion fluids. The pseudotime series, corresponding to different driving frequencies, indicates that nonlinearity effects appear more strongly for smaller frequency values. The existence of extra harmonic resonances in the nonlinear amplitude spectrum is a clear indication of the interaction of an external force with harmonic components of the nonlinear ion acoustic waves. It is shown that many plasma parameters significantly and differently affect the nonlinear resonance spectrum of ion acoustic excitations. A heuristic but accurate model for the foldover effect is used which quite satisfactorily predicts the bistability of driven plasma oscillations. It is remarked that the characteristic resonance peak of isothermal ion plasma oscillations appears at lower frequencies but is stronger compared to that of adiabatic ions. Comparison of the exact numerical results for fully nonlinear and approximate (weakly nonlinear) models indicates that a weakly nonlinear model exaggerates the hysteresis and jump phenomenon for higher values of the external force amplitude.

  19. On the functional relevance of frontal cortex for passive and voluntarily controlled bistable vision.

    Science.gov (United States)

    de Graaf, Tom A; de Jong, Maartje C; Goebel, Rainer; van Ee, Raymond; Sack, Alexander T

    2011-10-01

    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 switches, leading some researchers to suggest that frontal regions causally induce perceptual switches. But the opposite also seems possible: frontal activations may themselves be caused by spontaneous switches. Classically implicated in attentional processes, these same regions are also candidates for the origins of voluntary control over bistable vision. Here too, it remains unknown whether frontal cortex is actually functionally relevant. It is even possible that spontaneous perceptual switches and voluntarily induced switches are mediated by the same top-down mechanisms. To directly address these issues, we here induced "virtual lesions," with transcranial magnetic stimulation, in frontal, parietal, and 2 lower level visual cortices using an established ambiguous structure-from-motion stimulus. We found that dorsolateral prefrontal cortex was causally relevant for voluntary control over perceptual switches. In contrast, we failed to find any evidence for an active role of frontal cortex in passive bistable vision. Thus, it seems the same pathway used for willed top-down modulation of bistable vision is not used during passive bistable viewing.

  20. Investigation of bistable perception with the "silhouette spinner": sit still, spin the dancer with your will.

    Science.gov (United States)

    Liu, Chao-Hsuan; Tzeng, Ovid J L; Hung, Daisy L; Tseng, Philip; Juan, Chi-Hung

    2012-05-01

    Many studies have used static and non-biologically related stimuli to investigate bistable perception and found that the percept is usually dominated by their intrinsic nature with some influence of voluntary control from the viewer. Here we used a dynamic stimulus of a rotating human body, the silhouette spinner illusion, to investigate how the viewers' intentions may affect their percepts. In two experiments, we manipulated observer intention (active or passive), fixation position (body or feet), and spinning velocity (fast, medium, or slow). Our results showed that the normalized alternating rate between two bistable percepts was greater when (1) participants actively attempted to switch percepts, (2) when participants fixated at the spinner's feet rather than the body, inducing as many as 25 switches of the bistable percepts within 1 min, and (3) when they watched the spinner at high velocity. These results suggest that a dynamic biologically-bistable percept can be quickly alternated by the viewers' intention. Furthermore, the higher alternating rate in the feet condition compared to the body condition suggests a role for biological meaningfulness in determining bistable percepts, where 'biologically plausible' interpretations are favored by the visual system. Copyright © 2012 Elsevier Ltd. All rights reserved.