Aliasing-free wideband beamforming using sparse signal representation
Tang, Z.; Blacquière, G.; Leus, G.
2011-01-01
Sparse signal representation (SSR) is considered to be an appealing alternative to classical beamforming for direction-of-arrival (DOA) estimation. For wideband signals, the SSR-based approach constructs steering matrices, referred to as dictionaries in this paper, corresponding to different
An Analog Correlator for Ultra-Wideband Receivers
Directory of Open Access Journals (Sweden)
Tu Chunjiang
2005-01-01
Full Text Available We present a new analog circuit exhibiting high bandwidth and low distortion, specially designed for signal correlation in an ultra-wideband receiver front end. The ultra-wideband short impulse signals are correlated with a local pulse template by the correlator. A comparator then samples the output for signal detection. A typical Gilbert mixer core is adopted for multiplication of broadband signals up to . As a result of synchronization of the received signal and the local template, the output voltage level after integration and sampling can reach up to , which is sufficient for detection by the comparator. The circuit dissipates about from double voltage supplies of and using SiGe BiCMOS technology. Simulation results are presented to show the feasibility of this circuit design for use in ultra-wideband receivers.
Analog system for computing sparse codes
Rozell, Christopher John; Johnson, Don Herrick; Baraniuk, Richard Gordon; Olshausen, Bruno A.; Ortman, Robert Lowell
2010-08-24
A parallel dynamical system for computing sparse representations of data, i.e., where the data can be fully represented in terms of a small number of non-zero code elements, and for reconstructing compressively sensed images. The system is based on the principles of thresholding and local competition that solves a family of sparse approximation problems corresponding to various sparsity metrics. The system utilizes Locally Competitive Algorithms (LCAs), nodes in a population continually compete with neighboring units using (usually one-way) lateral inhibition to calculate coefficients representing an input in an over complete dictionary.
Distributed fiber sparse-wideband vibration sensing by sub-Nyquist additive random sampling
Zhang, Jingdong; Zheng, Hua; Zhu, Tao; Yin, Guolu; Liu, Min; Bai, Yongzhong; Qu, Dingrong; Qiu, Feng; Huang, Xianbing
2018-05-01
The round trip time of the light pulse limits the maximum detectable vibration frequency response range of phase-sensitive optical time domain reflectometry ({\\phi}-OTDR). Unlike the uniform laser pulse interval in conventional {\\phi}-OTDR, we randomly modulate the pulse interval, so that an equivalent sub-Nyquist additive random sampling (sNARS) is realized for every sensing point of the long interrogation fiber. For an {\\phi}-OTDR system with 10 km sensing length, the sNARS method is optimized by theoretical analysis and Monte Carlo simulation, and the experimental results verify that a wide-band spars signal can be identified and reconstructed. Such a method can broaden the vibration frequency response range of {\\phi}-OTDR, which is of great significance in sparse-wideband-frequency vibration signal detection, such as rail track monitoring and metal defect detection.
Design of a High Linearity Four-Quadrant Analog Multiplier in Wideband Frequency Range
Directory of Open Access Journals (Sweden)
Abdul kareem Mokif Obais
2017-05-01
Full Text Available In this paper, a voltage mode four quadrant analog multiplier in the wideband frequency rangeis designed using a wideband operational amplifier (OPAMP and squaring circuits. The wideband OPAMP is designed using 10 identical NMOS transistorsand operated with supply voltages of ±12V. Two NMOS transistors and two wideband OPAMP are utilized in the design of the proposed squaring circuit. All the NMOS transistors are based on 0.35µm NMOStechnology. The multiplier has input and output voltage ranges of ±10 V, high range of linearity from -10 V to +10 V, and cutoff frequency of about 5 GHz. The proposed multiplier is designed on PSpice in Orcad 16.6
Wide-band analog frequency modulation of optic signals using indirect techniques
Fitzmartin, D. J.; Balboni, E. J.; Gels, R. G.
1991-01-01
The wideband frequency modulation (FM) of an optical carrier by a radio frequency (RF) or microwave signal can be accomplished independent of laser type when indirect modulation is employed. Indirect modulators exploit the integral relation of phase to frequency so that phase modulators can be used to impress frequency modulation on an optical carrier. The use of integrated optics phase modulators, which are highly linear, enables the generation of optical wideband FM signals with very low intermodulation distortion. This modulator can be used as part of an optical wideband FM link for RF and microwave signals. Experimental results from the test of an indirect frequency modulator for an optical carrier are discussed.
Valente, Virgilio; Dai Jiang; Demosthenous, Andreas
2015-08-01
This paper presents the preliminary design and simulation of a flexible and programmable analog front-end (AFE) circuit with current and voltage readout capabilities for electric impedance spectroscopy (EIS). The AFE is part of a fully integrated multifrequency EIS platform. The current readout comprises of a transimpedance stage and an automatic gain control (AGC) unit designed to accommodate impedance changes larger than 3 order of magnitude. The AGC is based on a dynamic peak detector that tracks changes in the input current over time and regulates the gain of a programmable gain amplifier in order to optimise the signal-to-noise ratio. The system works up to 1 MHz. The voltage readout consists of a 2 stages of fully differential current-feedback instrumentation amplifier which provide 100 dB of CMRR and a programmable gain up to 20 V/V per stage with a bandwidth in excess of 10MHz.
Directory of Open Access Journals (Sweden)
Eswaran Uthirajoo
Full Text Available For the first time, a new circuit to extend the linear operation bandwidth of a LTE (Long Term Evolution power amplifier, while delivering a high efficiency is implemented in less than 1 mm2 chip area. The 950 µm × 900 µm monolithic microwave integrated circuit (MMIC power amplifier (PA is fabricated in a 2 µm InGaP/GaAs process. An on-chip analog pre-distorter (APD is designed to improve the linearity of the PA, up to 20 MHz channel bandwidth. Intended for 1.95 GHz Band 1 LTE application, the PA satisfies adjacent channel leakage ratio (ACLR and error vector magnitude (EVM specifications for a wide LTE channel bandwidth of 20 MHz at a linear output power of 28 dBm with corresponding power added efficiency (PAE of 52.3%. With a respective input and output return loss of 30 dB and 14 dB, the PA's power gain is measured to be 32.5 dB while exhibiting an unconditional stability characteristic from DC up to 5 GHz. The proposed APD technique serves to be a good solution to improve linearity of a PA without sacrificing other critical performance metrics.
Uthirajoo, Eswaran; Ramiah, Harikrishnan; Kanesan, Jeevan; Reza, Ahmed Wasif
2014-01-01
For the first time, a new circuit to extend the linear operation bandwidth of a LTE (Long Term Evolution) power amplifier, while delivering a high efficiency is implemented in less than 1 mm2 chip area. The 950 µm × 900 µm monolithic microwave integrated circuit (MMIC) power amplifier (PA) is fabricated in a 2 µm InGaP/GaAs process. An on-chip analog pre-distorter (APD) is designed to improve the linearity of the PA, up to 20 MHz channel bandwidth. Intended for 1.95 GHz Band 1 LTE application, the PA satisfies adjacent channel leakage ratio (ACLR) and error vector magnitude (EVM) specifications for a wide LTE channel bandwidth of 20 MHz at a linear output power of 28 dBm with corresponding power added efficiency (PAE) of 52.3%. With a respective input and output return loss of 30 dB and 14 dB, the PA's power gain is measured to be 32.5 dB while exhibiting an unconditional stability characteristic from DC up to 5 GHz. The proposed APD technique serves to be a good solution to improve linearity of a PA without sacrificing other critical performance metrics.
Uthirajoo, Eswaran; Ramiah, Harikrishnan; Kanesan, Jeevan; Reza, Ahmed Wasif
2014-01-01
For the first time, a new circuit to extend the linear operation bandwidth of a LTE (Long Term Evolution) power amplifier, while delivering a high efficiency is implemented in less than 1 mm2 chip area. The 950 µm × 900 µm monolithic microwave integrated circuit (MMIC) power amplifier (PA) is fabricated in a 2 µm InGaP/GaAs process. An on-chip analog pre-distorter (APD) is designed to improve the linearity of the PA, up to 20 MHz channel bandwidth. Intended for 1.95 GHz Band 1 LTE application, the PA satisfies adjacent channel leakage ratio (ACLR) and error vector magnitude (EVM) specifications for a wide LTE channel bandwidth of 20 MHz at a linear output power of 28 dBm with corresponding power added efficiency (PAE) of 52.3%. With a respective input and output return loss of 30 dB and 14 dB, the PA’s power gain is measured to be 32.5 dB while exhibiting an unconditional stability characteristic from DC up to 5 GHz. The proposed APD technique serves to be a good solution to improve linearity of a PA without sacrificing other critical performance metrics. PMID:25033049
Baschirotto, A.; Harpe, P.J.A.; Makinwa, K.A.A.
2017-01-01
This book is based on the 18 tutorials presented during the 25th workshop on Advances in Analog Circuit Design. Expert designers present readers with information about a variety of topics at the frontier of analog circuit design, including low-power and energy-efficient analog electronics, with
Oliveira, Luis
2015-01-01
This book demonstrates how to design a wideband receiver operating in current mode, in which the noise and non-linearity are reduced, implemented in a low cost single chip, using standard CMOS technology. The authors present a solution to remove the transimpedance amplifier (TIA) block and connect directly the mixer’s output to a passive second-order continuous-time Σ∆ analog to digital converter (ADC), which operates in current-mode. These techniques enable the reduction of area, power consumption, and cost in modern CMOS receivers.
Sparse decompositions in 'incoherent' dictionaries
DEFF Research Database (Denmark)
Gribonval, R.; Nielsen, Morten
2003-01-01
a unique sparse representation in such a dictionary. In particular, it is proved that the result of Donoho and Huo, concerning the replacement of a combinatorial optimization problem with a linear programming problem when searching for sparse representations, has an analog for dictionaries that may...
Generalized Wideband Cyclic MUSIC
Directory of Open Access Journals (Sweden)
Zhang-Meng Liu
2009-01-01
Full Text Available The method of Spectral Correlation-Signal Subspace Fitting (SC-SSF fails to separate wideband cyclostationary signals with coherent second-order cyclic statistics (SOCS. Averaged Cyclic MUSIC (ACM method made up for the drawback to some degree via temporally averaging the cyclic cross-correlation of the array output. This paper interprets ACM from another perspective and proposes a new DOA estimation method by generalizing ACM for wideband cyclostationary signals. The proposed method successfully makes up for the aforementioned drawback of SC-SSF and obtains a more satisfying performance than ACM. It is also demonstrated that ACM is a simplified form of the proposed method when only a single spectral frequency is exploited, and the integration of the frequencies within the signal bandwidth helps the new method to outperform ACM.
Hollister, Allen L
2007-01-01
In this book, the theory needed to understand wideband amplifier design using the simplest models possible will be developed. This theory will be used to develop algebraic equations that describe particular circuits used in high frequency design so that the reader develops a ""gut level"" understanding of the process and circuit. SPICE and Genesys simulations will be performed to show the accuracy of the algebraic models. By looking at differences between the algebraic equations and the simulations, new algebraic models will be developed that include parameters originally left out of the model
Wideband pulse amplifiers for the NECTAr chip
Sanuy, A.; Delagnes, E.; Gascon, D.; Sieiro, X.; Bolmont, J.; Corona, P.; Feinstein, F.; Glicenstein, J.-F.; Naumann, C. L.; Nayman, P.; Ribó, M.; Tavernet, J.-P.; Toussenel, F.; Vincent, P.; Vorobiov, S.
2012-12-01
The NECTAr collaboration's FE option for the camera of the CTA is a 16 bits and 1-3 GS/s sampling chip based on analog memories including most of the readout functions. This works describes the input amplifiers of the NECTAr ASIC. A fully differential wideband amplifier, with voltage gain up to 20 V/V and a BW of 400 MHz. As it is impossible to design a fully differential OpAmp with an 8 GHz GBW product in a 0.35 CMOS technology, an alternative implementation based on HF linearized transconductors is explored. The output buffer is a class AB miller operational amplifier, with special non-linear current boost.
Wideband pulse amplifiers for the NECTAr chip
International Nuclear Information System (INIS)
Sanuy, A.; Delagnes, E.; Gascon, D.; Sieiro, X.; Bolmont, J.; Corona, P.; Feinstein, F.; Glicenstein, J-F.; Naumann, C.L.; Nayman, P.; Ribó, M.
2012-01-01
The NECTAr collaboration's FE option for the camera of the CTA is a 16 bits and 1–3 GS/s sampling chip based on analog memories including most of the readout functions. This works describes the input amplifiers of the NECTAr ASIC. A fully differential wideband amplifier, with voltage gain up to 20 V/V and a BW of 400 MHz. As it is impossible to design a fully differential OpAmp with an 8 GHz GBW product in a 0.35 CMOS technology, an alternative implementation based on HF linearized transconductors is explored. The output buffer is a class AB miller operational amplifier, with special non-linear current boost.
Wideband pulse amplifiers for the NECTAr chip
Energy Technology Data Exchange (ETDEWEB)
Sanuy, A., E-mail: asanuy@ecm.ub.es [Dept. AM i Dept. ECM, Institut de Ciencies del Cosmos (ICC), Universitat de Barcelona. Marti i Franques 1, E08028, Barcelona (Spain); Delagnes, E. [IRFU/DSM/CEA, CE-Saclay, Bat. 141 SEN Saclay, F-91191, Gif-sur-Yvette (France); Gascon, D. [Dept. AM i Dept. ECM, Institut de Ciencies del Cosmos (ICC), Universitat de Barcelona. Marti i Franques 1, E08028, Barcelona (Spain); Sieiro, X. [Departament d' Electronica, Universitat de Barcelona. Marti i Franques 1, E08028, Barcelona (Spain); Bolmont, J.; Corona, P. [LPNHE, Universite Paris VI and Universite Paris VII and IN2P3/CNRS, Barre 12-22, 1er etage, 4 place Jussieu, 75252 Paris (France); Feinstein, F. [LUPM, Universite Montpellier II and IN2P3/CNRS, CC072, bat. 13, place Eugene Bataillon, 34095 Montpellier (France); Glicenstein, J-F. [IRFU/DSM/CEA, CE-Saclay, Bat. 141 SEN Saclay, F-91191, Gif-sur-Yvette (France); Naumann, C.L.; Nayman, P. [LPNHE, Universite Paris VI and Universite Paris VII and IN2P3/CNRS, Barre 12-22, 1er etage, 4 place Jussieu, 75252 Paris (France); Ribo, M. [Dept. AM i Dept. ECM, Institut de Ciencies del Cosmos (ICC), Universitat de Barcelona. Marti i Franques 1, E08028, Barcelona (Spain); and others
2012-12-11
The NECTAr collaboration's FE option for the camera of the CTA is a 16 bits and 1-3 GS/s sampling chip based on analog memories including most of the readout functions. This works describes the input amplifiers of the NECTAr ASIC. A fully differential wideband amplifier, with voltage gain up to 20 V/V and a BW of 400 MHz. As it is impossible to design a fully differential OpAmp with an 8 GHz GBW product in a 0.35 CMOS technology, an alternative implementation based on HF linearized transconductors is explored. The output buffer is a class AB miller operational amplifier, with special non-linear current boost.
Wideband Piezomagnetoelastic Vibration Energy Harvesting
DEFF Research Database (Denmark)
Lei, Anders; Thomsen, Erik Vilain
2014-01-01
This work presents a small-scale wideband piezomagnetoelastic vibration energy harvester (VEH) aimed for operation at frequencies of a few hundred Hz. The VEH consists of a tape-casted PZT cantilever with thin sheets of iron foil attached on each side of the free tip. The wideband operation...... is achieved by placing the cantilever in a magnetic field induced by either one or two magnets located oppositely of the cantilever. The attraction force created by the magnetic field and iron foils introduces a mechanical force in opposite direction of the cantilevers restoring force causing a spring...
Sparse structure regularized ranking
Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin
2014-01-01
Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse
International Nuclear Information System (INIS)
Xu, Lijun; Ren, Ying; Sun, Shijie; Cao, Zhang
2016-01-01
In this paper, an under-sampling method for wideband capacitance measurement was proposed by using the compressive sensing strategy. As the excitation signal is sparse in the frequency domain, the compressed sampling method that uses a random demodulator was adopted, which could greatly decrease the sampling rate. Besides, four switches were used to replace the multiplier in the random demodulator. As a result, not only the sampling rate can be much smaller than the signal excitation frequency, but also the circuit’s structure is simpler and its power consumption is lower. A hardware prototype was constructed to validate the method. In the prototype, an excitation voltage with a frequency up to 200 kHz was applied to a capacitance-to-voltage converter. The output signal of the converter was randomly modulated by a pseudo-random sequence through four switches. After a low-pass filter, the signal was sampled by an analog-to-digital converter at a sampling rate of 50 kHz, which was three times lower than the highest exciting frequency. The frequency and amplitude of the signal were then reconstructed to obtain the measured capacitance. Both theoretical analysis and experiments were carried out to show the feasibility of the proposed method and to evaluate the performance of the prototype, including its linearity, sensitivity, repeatability, accuracy and stability within a given measurement range. (paper)
Maritime wideband communication networks video transmission scheduling
Yang, Tingting
2014-01-01
This Springer Brief covers emerging maritime wideband communication networks and how they facilitate applications such as maritime distress, urgency, safety and general communications. It provides valuable insight on the data transmission scheduling and protocol design for the maritime wideband network. This brief begins with an introduction to maritime wideband communication networks including the architecture, framework, operations and a comprehensive survey on current developments. The second part of the brief presents the resource allocation and scheduling for video packet transmission wit
Wideband 4-diode sampling circuit
Wojtulewicz, Andrzej; Radtke, Maciej
2016-09-01
The objective of this work was to develop a wide-band sampling circuit. The device should have the ability to collect samples of a very fast signal applied to its input, strengthen it and prepare for further processing. The study emphasizes the method of sampling pulse shaping. The use of ultrafast pulse generator allows sampling signals with a wide frequency spectrum, reaching several gigahertzes. The device uses a pulse transformer to prepare symmetrical pulses. Their final shape is formed with the help of the step recovery diode, two coplanar strips and Schottky diode. Made device can be used in the sampling oscilloscope, as well as other measurement system.
Wideband feedback system prototype validation
Li, K; Bjorsvik, E; Fox, J; Hofle, W; Kotzian, G; Rivetta, C; Salvant, B; Turgut, O
2017-01-01
A wideband feedback demonstrator system has been de-veloped in collaboration with US-LARP under the joint lead-ership of CERN and SLAC. The system includes widebandkicker structures and amplifiers along with a fast digital re-configurable system up to 4 GS/s for single bunch and multibunch control. Most of the components have been installedin recent years and have been put into operation to test bothintra-bunch damping and individual bunch control in a multibunch train. In this note we report on the MD program,procedure and key findings that were made with this systemin the past year.
Zhang, Tianzhu
2015-06-01
Sparse representation has been applied to visual tracking by finding the best target candidate with minimal reconstruction error by use of target templates. However, most sparse representation based trackers only consider holistic or local representations and do not make full use of the intrinsic structure among and inside target candidates, thereby making the representation less effective when similar objects appear or under occlusion. In this paper, we propose a novel Structural Sparse Tracking (SST) algorithm, which not only exploits the intrinsic relationship among target candidates and their local patches to learn their sparse representations jointly, but also preserves the spatial layout structure among the local patches inside each target candidate. We show that our SST algorithm accommodates most existing sparse trackers with the respective merits. Both qualitative and quantitative evaluations on challenging benchmark image sequences demonstrate that the proposed SST algorithm performs favorably against several state-of-the-art methods.
Sparse structure regularized ranking
Wang, Jim Jing-Yan
2014-04-17
Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.
Zhang, Tianzhu; Yang, Ming-Hsuan; Ahuja, Narendra; Ghanem, Bernard; Yan, Shuicheng; Xu, Changsheng; Liu, Si
2015-01-01
candidate. We show that our SST algorithm accommodates most existing sparse trackers with the respective merits. Both qualitative and quantitative evaluations on challenging benchmark image sequences demonstrate that the proposed SST algorithm performs
Introduction to Ultra Wideband for Wireless Communications
DEFF Research Database (Denmark)
Nikookar, Homayoun; Prasad, Ramjee
wireless channels, interference, signal processing as well as applications and standardization activities are addressed. Introduction to Ultra Wideband for Wireless Communications provides easy-to-understand material to (graduate) students and researchers working in the field of commercial UWB wireless......Ultra Wideband (UWB) Technology is the cutting edge technology for wireless communications with a wide range of applications. In Introduction to Ultra Wideband for Wireless Communications UWB principles and technologies for wireless communications are explained clearly. Key issues such as UWB...... communications. Due to tutorial nature of the book it can also be adopted as a textbook on the subject in the Telecommunications Engineering curriculum. Problems at the end of each chapter extend the reader's understanding of the subject. Introduction to Ultra Wideband for Wireless Communications will aslo...
SparseM: A Sparse Matrix Package for R *
Directory of Open Access Journals (Sweden)
Roger Koenker
2003-02-01
Full Text Available SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the package is illustrated by a family of linear model fitting functions that implement least squares methods for problems with sparse design matrices. Significant performance improvements in memory utilization and computational speed are possible for applications involving large sparse matrices.
Ultra wideband antennas design, methodologies, and performance
Galvan-Tejada, Giselle M; Jardón Aguilar, Hildeberto
2015-01-01
Ultra Wideband Antennas: Design, Methodologies, and Performance presents the current state of the art of ultra wideband (UWB) antennas, from theory specific for these radiators to guidelines for the design of omnidirectional and directional UWB antennas. Offering a comprehensive overview of the latest UWB antenna research and development, this book:Discusses the developed theory for UWB antennas in frequency and time domainsDelivers a brief exposition of numerical methods for electromagnetics oriented to antennasDescribes solid-planar equivalen
A wideband software reconfigurable modem
Turner, J. H., Jr.; Vickers, H.
A wideband modem is described which provides signal processing capability for four Lx-band signals employing QPSK, MSK and PPM waveforms and employs a software reconfigurable architecture for maximum system flexibility and graceful degradation. The current processor uses a 2901 and two 8086 microprocessors per channel and performs acquisition, tracking, and data demodulation for JITDS, GPS, IFF and TACAN systems. The next generation processor will be implemented using a VHSIC chip set employing a programmable complex array vector processor module, a GP computer module, customized gate array modules, and a digital array correlator. This integrated processor has application to a wide number of diverse system waveforms, and will bring the benefits of VHSIC technology insertion into avionic antijam communications systems.
Ulmann, Bernd
2013-01-01
This book is a comprehensive introduction to analog computing. As most textbooks about this powerful computing paradigm date back to the 1960s and 1970s, it fills a void and forges a bridge from the early days of analog computing to future applications. The idea of analog computing is not new. In fact, this computing paradigm is nearly forgotten, although it offers a path to both high-speed and low-power computing, which are in even more demand now than they were back in the heyday of electronic analog computers.
Sparse distributed memory overview
Raugh, Mike
1990-01-01
The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.
Efficient convolutional sparse coding
Wohlberg, Brendt
2017-06-20
Computationally efficient algorithms may be applied for fast dictionary learning solving the convolutional sparse coding problem in the Fourier domain. More specifically, efficient convolutional sparse coding may be derived within an alternating direction method of multipliers (ADMM) framework that utilizes fast Fourier transforms (FFT) to solve the main linear system in the frequency domain. Such algorithms may enable a significant reduction in computational cost over conventional approaches by implementing a linear solver for the most critical and computationally expensive component of the conventional iterative algorithm. The theoretical computational cost of the algorithm may be reduced from O(M.sup.3N) to O(MN log N), where N is the dimensionality of the data and M is the number of elements in the dictionary. This significant improvement in efficiency may greatly increase the range of problems that can practically be addressed via convolutional sparse representations.
Sparse approximation with bases
2015-01-01
This book systematically presents recent fundamental results on greedy approximation with respect to bases. Motivated by numerous applications, the last decade has seen great successes in studying nonlinear sparse approximation. Recent findings have established that greedy-type algorithms are suitable methods of nonlinear approximation in both sparse approximation with respect to bases and sparse approximation with respect to redundant systems. These insights, combined with some previous fundamental results, form the basis for constructing the theory of greedy approximation. Taking into account the theoretical and practical demand for this kind of theory, the book systematically elaborates a theoretical framework for greedy approximation and its applications. The book addresses the needs of researchers working in numerical mathematics, harmonic analysis, and functional analysis. It quickly takes the reader from classical results to the latest frontier, but is written at the level of a graduate course and do...
Supervised Convolutional Sparse Coding
Affara, Lama Ahmed
2018-04-08
Convolutional Sparse Coding (CSC) is a well-established image representation model especially suited for image restoration tasks. In this work, we extend the applicability of this model by proposing a supervised approach to convolutional sparse coding, which aims at learning discriminative dictionaries instead of purely reconstructive ones. We incorporate a supervised regularization term into the traditional unsupervised CSC objective to encourage the final dictionary elements to be discriminative. Experimental results show that using supervised convolutional learning results in two key advantages. First, we learn more semantically relevant filters in the dictionary and second, we achieve improved image reconstruction on unseen data.
Supervised Transfer Sparse Coding
Al-Shedivat, Maruan
2014-07-27
A combination of the sparse coding and transfer learn- ing techniques was shown to be accurate and robust in classification tasks where training and testing objects have a shared feature space but are sampled from differ- ent underlying distributions, i.e., belong to different do- mains. The key assumption in such case is that in spite of the domain disparity, samples from different domains share some common hidden factors. Previous methods often assumed that all the objects in the target domain are unlabeled, and thus the training set solely comprised objects from the source domain. However, in real world applications, the target domain often has some labeled objects, or one can always manually label a small num- ber of them. In this paper, we explore such possibil- ity and show how a small number of labeled data in the target domain can significantly leverage classifica- tion accuracy of the state-of-the-art transfer sparse cod- ing methods. We further propose a unified framework named supervised transfer sparse coding (STSC) which simultaneously optimizes sparse representation, domain transfer and classification. Experimental results on three applications demonstrate that a little manual labeling and then learning the model in a supervised fashion can significantly improve classification accuracy.
Exarchakis, Georgios; Lücke, Jörg
2017-11-01
Sparse coding algorithms with continuous latent variables have been the subject of a large number of studies. However, discrete latent spaces for sparse coding have been largely ignored. In this work, we study sparse coding with latents described by discrete instead of continuous prior distributions. We consider the general case in which the latents (while being sparse) can take on any value of a finite set of possible values and in which we learn the prior probability of any value from data. This approach can be applied to any data generated by discrete causes, and it can be applied as an approximation of continuous causes. As the prior probabilities are learned, the approach then allows for estimating the prior shape without assuming specific functional forms. To efficiently train the parameters of our probabilistic generative model, we apply a truncated expectation-maximization approach (expectation truncation) that we modify to work with a general discrete prior. We evaluate the performance of the algorithm by applying it to a variety of tasks: (1) we use artificial data to verify that the algorithm can recover the generating parameters from a random initialization, (2) use image patches of natural images and discuss the role of the prior for the extraction of image components, (3) use extracellular recordings of neurons to present a novel method of analysis for spiking neurons that includes an intuitive discretization strategy, and (4) apply the algorithm on the task of encoding audio waveforms of human speech. The diverse set of numerical experiments presented in this letter suggests that discrete sparse coding algorithms can scale efficiently to work with realistic data sets and provide novel statistical quantities to describe the structure of the data.
Wideband feeds for the upgraded GMRT
International Nuclear Information System (INIS)
Bandari, Hanumanth Rao; Sankarasubramanian, G; Kumar, A Praveen
2013-01-01
This paper describes the existing feeds in use at the GMRT Observatory and details the ongoing development of next generation wideband feeds for the upgraded GMRT. The existing feeds include: feed with folded thick dipoles (for 150 MHz), dipole-disc feed (for 325 MHz), dual-band coaxial feed (for 233 MHZ and 610 MHz), and corrugated horn feed (for 1400–1450 MHz). The new broadband feeds covered in this paper are: cone-dipole feeds for 250–500 and 500–1000 MHz, wideband horn feed for 550–900 MHz, and dual ring feed for 130–260 MHz. Design techniques and performance results for these are described.
Sparse inpainting and isotropy
Energy Technology Data Exchange (ETDEWEB)
Feeney, Stephen M.; McEwen, Jason D.; Peiris, Hiranya V. [Department of Physics and Astronomy, University College London, Gower Street, London, WC1E 6BT (United Kingdom); Marinucci, Domenico; Cammarota, Valentina [Department of Mathematics, University of Rome Tor Vergata, via della Ricerca Scientifica 1, Roma, 00133 (Italy); Wandelt, Benjamin D., E-mail: s.feeney@imperial.ac.uk, E-mail: marinucc@axp.mat.uniroma2.it, E-mail: jason.mcewen@ucl.ac.uk, E-mail: h.peiris@ucl.ac.uk, E-mail: wandelt@iap.fr, E-mail: cammarot@axp.mat.uniroma2.it [Kavli Institute for Theoretical Physics, Kohn Hall, University of California, 552 University Road, Santa Barbara, CA, 93106 (United States)
2014-01-01
Sparse inpainting techniques are gaining in popularity as a tool for cosmological data analysis, in particular for handling data which present masked regions and missing observations. We investigate here the relationship between sparse inpainting techniques using the spherical harmonic basis as a dictionary and the isotropy properties of cosmological maps, as for instance those arising from cosmic microwave background (CMB) experiments. In particular, we investigate the possibility that inpainted maps may exhibit anisotropies in the behaviour of higher-order angular polyspectra. We provide analytic computations and simulations of inpainted maps for a Gaussian isotropic model of CMB data, suggesting that the resulting angular trispectrum may exhibit small but non-negligible deviations from isotropy.
Sparse matrix test collections
Energy Technology Data Exchange (ETDEWEB)
Duff, I.
1996-12-31
This workshop will discuss plans for coordinating and developing sets of test matrices for the comparison and testing of sparse linear algebra software. We will talk of plans for the next release (Release 2) of the Harwell-Boeing Collection and recent work on improving the accessibility of this Collection and others through the World Wide Web. There will only be three talks of about 15 to 20 minutes followed by a discussion from the floor.
International Nuclear Information System (INIS)
Hofmann, R.B.
1995-01-01
Analogs are used to understand complex or poorly understood phenomena for which little data may be available at the actual repository site. Earthquakes are complex phenomena, and they can have a large number of effects on the natural system, as well as on engineered structures. Instrumental data close to the source of large earthquakes are rarely obtained. The rare events for which measurements are available may be used, with modfications, as analogs for potential large earthquakes at sites where no earthquake data are available. In the following, several examples of nuclear reactor and liquified natural gas facility siting are discussed. A potential use of analog earthquakes is proposed for a high-level nuclear waste (HLW) repository
Sensing RF signals with the optical wideband converter
Valley, George C.; Sefler, George A.; Shaw, T. J.
2013-01-01
The optical wideband converter (OWC) is a system for measuring properties of RF signals in the GHz band without use of high speed electronics. In the OWC the RF signal is modulated on a repetitively pulsed optical field with a large wavelength chirp, the optical field is diffracted onto a spatial light modulator (SLM) whose pixels are modulated with a pseudo-random bit sequences (PRBSs), and finally the optical field is directed to a photodiode and the resulting current integrated for each PRBS. When the number of PRBSs and measurements equals the number of SLM pixels, the RF signal can be obtained in principle by multiplying the measurement vector by the inverse of the square matrix given by the PRBSs and the properties of the optics. When the number of measurements is smaller than the number of pixels, a compressive sensing (CS) measurement can be performed, and sparse RF signals can be obtained using one of the standard CS recovery algorithms such as the penalized l1 norm (also known as basis pursuit) or one of the variants of matching pursuit. Accurate reconstruction of RF signals requires good calibration of the OWC. In this paper, we present results using the OWC for RF signals consisting of 2 sinusoids recovered using 3 techniques (matrix inversion, basis pursuit, and matching pursuit). We compare results obtained with orthogonal matching pursuit with nonlinear least squares to basis pursuit with an over-complete dictionary.
Ultra-wideband radar sensors and networks
Leach, Jr., Richard R; Nekoogar, Faranak; Haugen, Peter C
2013-08-06
Ultra wideband radar motion sensors strategically placed in an area of interest communicate with a wireless ad hoc network to provide remote area surveillance. Swept range impulse radar and a heart and respiration monitor combined with the motion sensor further improves discrimination.
High Dynamic Range Nonlinear Measurement using Analog Cancellation
2012-10-01
shield around sensitive areas. The target may also be sensitive to radiated coupling from the system and will benefit from a shield box or Faraday ... cage , if it is not already enclosed. On the shared measurement path and through the target, cross-channel coupling cannot be prevented, so low-PIM...testing is desired, traditional filtering is recommended, as the primary benefits of the analog canceller are effectively nullified. 2.4 Wideband
Compressed sensing & sparse filtering
Carmi, Avishy Y; Godsill, Simon J
2013-01-01
This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and limited data. One such trend that recently gained popularity and to some extent revolutionised signal processing is compressed sensing. Compressed sensing builds upon the observation that many signals in nature are nearly sparse (or compressible, as they are normally referred to) in some domain, and consequently they can be reconstructed to within high accuracy from far fewer observations than traditionally held to be necessary.Â Apart from compressed sensing this book contains other related app
Wang, Jim Jing-Yan; Gao, Xin
2014-01-01
Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised manner, where only a few training samples are labeled. By using the manifold structure spanned by the data set of both labeled and unlabeled samples and the constraints provided by the labels of the labeled samples, we learn the variable class labels for all the samples. Furthermore, to improve the discriminative ability of the learned sparse codes, we assume that the class labels could be predicted from the sparse codes directly using a linear classifier. By solving the codebook, sparse codes, class labels and classifier parameters simultaneously in a unified objective function, we develop a semi-supervised sparse coding algorithm. Experiments on two real-world pattern recognition problems demonstrate the advantage of the proposed methods over supervised sparse coding methods on partially labeled data sets.
Wang, Jim Jing-Yan
2014-07-06
Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised manner, where only a few training samples are labeled. By using the manifold structure spanned by the data set of both labeled and unlabeled samples and the constraints provided by the labels of the labeled samples, we learn the variable class labels for all the samples. Furthermore, to improve the discriminative ability of the learned sparse codes, we assume that the class labels could be predicted from the sparse codes directly using a linear classifier. By solving the codebook, sparse codes, class labels and classifier parameters simultaneously in a unified objective function, we develop a semi-supervised sparse coding algorithm. Experiments on two real-world pattern recognition problems demonstrate the advantage of the proposed methods over supervised sparse coding methods on partially labeled data sets.
A wideband absorber for television studios
Baird, M. D. M.
The acoustic treatment in BBC television has taken various forms to date, all of which have been relatively expensive, some of which provide inadequate absorption. An investigation has been conducted into the possibilities of producing a new type of wideband absorber which would be more economic, also taking installation time into account, than earlier designs. This Report describes the absorption coefficient measurements made on various combinations of materials, from which a wideband sound absorber has been developed. The absorber works efficiently between 50 Hz and 10 kHz, is simple and easy to construct using readily available materials, and is fire resistant. The design lends itself, if necessary, to on-site fine tuning, and savings in the region of 50 percent can be achieved in terms of cost and space with respect to previous designs.
Super wideband characteristics of monopolar patch antenna
Directory of Open Access Journals (Sweden)
Xi Chen
2013-12-01
Full Text Available A simple method of acquiring super wideband characteristics for monopolar patch antenna is proposed. Through adopting a modified cone as feeding and radiating structure, the monopolar patch antenna can reach the impedance bandwidth of more than 1:23.4 for voltage standing wave ratio (VSWR ≤ 2. In the whole operating band, the antenna has the like-monopole omnidirectional radiation patterns and the peak gains of 3.8–8.7 dB. Meanwhile, the height of the antenna is just 0.074λ(c, and the diameter of the radiated body is 0.205λ(c, which is smaller than other ultra-wideband omnidirectional antenna.
Ultra-Wideband, Short Pulse Electromagnetics 9
Rachidi, Farhad; Kaelin, Armin; Sabath, Frank; UWB SP 9
2010-01-01
Ultra-wideband (UWB), short-pulse (SP) electromagnetics are now being used for an increasingly wide variety of applications, including collision avoidance radar, concealed object detection, and communications. Notable progress in UWB and SP technologies has been achieved by investigations of their theoretical bases and improvements in solid-state manufacturing, computers, and digitizers. UWB radar systems are also being used for mine clearing, oil pipeline inspections, archeology, geology, and electronic effects testing. Ultra-wideband Short-Pulse Electromagnetics 9 presents selected papers of deep technical content and high scientific quality from the UWB-SP9 Conference, which was held from July 21-25, 2008, in Lausanne, Switzerland. The wide-ranging coverage includes contributions on electromagnetic theory, time-domain computational techniques, modeling, antennas, pulsed-power, UWB interactions, radar systems, UWB communications, and broadband systems and components. This book serves as a state-of-the-art r...
Denning, Peter J.
1989-01-01
Sparse distributed memory was proposed be Pentti Kanerva as a realizable architecture that could store large patterns and retrieve them based on partial matches with patterns representing current sensory inputs. This memory exhibits behaviors, both in theory and in experiment, that resemble those previously unapproached by machines - e.g., rapid recognition of faces or odors, discovery of new connections between seemingly unrelated ideas, continuation of a sequence of events when given a cue from the middle, knowing that one doesn't know, or getting stuck with an answer on the tip of one's tongue. These behaviors are now within reach of machines that can be incorporated into the computing systems of robots capable of seeing, talking, and manipulating. Kanerva's theory is a break with the Western rationalistic tradition, allowing a new interpretation of learning and cognition that respects biology and the mysteries of individual human beings.
A Resistive Wideband Space Beam Splitter
Mahesh, Nivedita; Subrahmanyan, Ravi; Shankar, N. Udaya; Raghunathan, Agaram
2014-01-01
We present the design, construction and measurements of the electromagnetic performance of a wideband space beam splitter. The beam splitter is designed to power divide the incident radiation into reflected and transmitted components for interferometer measurement of spectral features in the mean cosmic radio background. Analysis of a 2-element interferometer configuration with a vertical beam splitter between a pair of antennas leads to the requirement that the beam splitter be a resistive s...
Wideband FM Demodulation and Multirate Frequency Transformations
2016-12-15
Noble identities to extend the proposed approach to larger wideband to narrowband conversion factors and more practical implementations. We further...framework . . . . . . . . . . . . . . . . . . . . . 8 2 Block diagrams of the alternative MFT system for large conversion factors (a) and the Noble Identity ...of both MFT frameworks with conversion factor R = 128 and normalized radian frequency shift wd = 0.1π under the extreme senario with modulation index
Wideband DOA Estimation through Projection Matrix Interpolation
Selva, J.
2017-01-01
This paper presents a method to reduce the complexity of the deterministic maximum likelihood (DML) estimator in the wideband direction-of-arrival (WDOA) problem, which is based on interpolating the array projection matrix in the temporal frequency variable. It is shown that an accurate interpolator like Chebyshev's is able to produce DML cost functions comprising just a few narrowband-like summands. Actually, the number of such summands is far smaller (roughly by factor ten in the numerical ...
Parallel Sparse Matrix - Vector Product
DEFF Research Database (Denmark)
Alexandersen, Joe; Lazarov, Boyan Stefanov; Dammann, Bernd
This technical report contains a case study of a sparse matrix-vector product routine, implemented for parallel execution on a compute cluster with both pure MPI and hybrid MPI-OpenMP solutions. C++ classes for sparse data types were developed and the report shows how these class can be used...
Principles and Limitations of Ultra-Wideband FM Communications Systems
Directory of Open Access Journals (Sweden)
Kouwenhoven Michiel HL
2005-01-01
Full Text Available This paper presents a novel UWB communications system using double FM: a low-modulation index digital FSK followed by a high-modulation index analog FM to create a constant-envelope UWB signal. FDMA techniques at the subcarrier level are exploited to accommodate multiple users. The system is intended for low (1–10 kbps and medium (100–1000 kbps bit rate, and short-range WPAN systems. A wideband delay-line FM demodulator that is not preceded by any limiting amplifier constitutes the key component of the UWBFM receiver. This unusual approach permits multiple users to share the same RF bandwidth. Multipath, however, may limit the useful subcarrier bandwidth to one octave. This paper addresses the performance with AWGN and multipath, the resistance to narrowband interference, as well as the simultaneous detection of multiple FM signals at the same carrier frequency. SPICE and Matlab simulation results illustrate the principles and limitations of this new technology. A hardware demonstrator has been realized and has allowed the confirmation of theory with practical results.
Coherent time-stretch transformation for real-time capture of wideband signals.
Buckley, Brandon W; Madni, Asad M; Jalali, Bahram
2013-09-09
Time stretch transformation of wideband waveforms boosts the performance of analog-to-digital converters and digital signal processors by slowing down analog electrical signals before digitization. The transform is based on dispersive Fourier transformation implemented in the optical domain. A coherent receiver would be ideal for capturing the time-stretched optical signal. Coherent receivers offer improved sensitivity, allow for digital cancellation of dispersion-induced impairments and optical nonlinearities, and enable decoding of phase-modulated optical data formats. Because time-stretch uses a chirped broadband (>1 THz) optical carrier, a new coherent detection technique is required. In this paper, we introduce and demonstrate coherent time stretch transformation; a technique that combines dispersive Fourier transform with optically broadband coherent detection.
Extension of the ITU Channel Models for Wideband (OFDM) Systems
DEFF Research Database (Denmark)
Sørensen, Troels Bundgaard; Frederiksen, Frank
2005-01-01
for the evaluation of wideband system concepts with frequency dependent characteristics, e.g. frequency domain link adaptation and packet scheduling, both of which are likely to be part of future wideband systems such as based on OFDM. With the suggested procedure the frequency correlation can be kept approximately...
Consensus Convolutional Sparse Coding
Choudhury, Biswarup
2017-12-01
Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high-dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaicing and 4D light field view synthesis.
Consensus Convolutional Sparse Coding
Choudhury, Biswarup
2017-04-11
Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaickingand 4D light field view synthesis.
Consensus Convolutional Sparse Coding
Choudhury, Biswarup; Swanson, Robin; Heide, Felix; Wetzstein, Gordon; Heidrich, Wolfgang
2017-01-01
Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high-dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaicing and 4D light field view synthesis.
Turbulent flows over sparse canopies
Sharma, Akshath; García-Mayoral, Ricardo
2018-04-01
Turbulent flows over sparse and dense canopies exerting a similar drag force on the flow are investigated using Direct Numerical Simulations. The dense canopies are modelled using a homogeneous drag force, while for the sparse canopy, the geometry of the canopy elements is represented. It is found that on using the friction velocity based on the local shear at each height, the streamwise velocity fluctuations and the Reynolds stress within the sparse canopy are similar to those from a comparable smooth-wall case. In addition, when scaled with the local friction velocity, the intensity of the off-wall peak in the streamwise vorticity for sparse canopies also recovers a value similar to a smooth-wall. This indicates that the sparse canopy does not significantly disturb the near-wall turbulence cycle, but causes its rescaling to an intensity consistent with a lower friction velocity within the canopy. In comparison, the dense canopy is found to have a higher damping effect on the turbulent fluctuations. For the case of the sparse canopy, a peak in the spectral energy density of the wall-normal velocity, and Reynolds stress is observed, which may indicate the formation of Kelvin-Helmholtz-like instabilities. It is also found that a sparse canopy is better modelled by a homogeneous drag applied on the mean flow alone, and not the turbulent fluctuations.
Sparse Regression by Projection and Sparse Discriminant Analysis
Qi, Xin; Luo, Ruiyan; Carroll, Raymond J.; Zhao, Hongyu
2015-01-01
predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths
In Defense of Sparse Tracking: Circulant Sparse Tracker
Zhang, Tianzhu; Bibi, Adel Aamer; Ghanem, Bernard
2016-01-01
Sparse representation has been introduced to visual tracking by finding the best target candidate with minimal reconstruction error within the particle filter framework. However, most sparse representation based trackers have high computational cost, less than promising tracking performance, and limited feature representation. To deal with the above issues, we propose a novel circulant sparse tracker (CST), which exploits circulant target templates. Because of the circulant structure property, CST has the following advantages: (1) It can refine and reduce particles using circular shifts of target templates. (2) The optimization can be efficiently solved entirely in the Fourier domain. (3) High dimensional features can be embedded into CST to significantly improve tracking performance without sacrificing much computation time. Both qualitative and quantitative evaluations on challenging benchmark sequences demonstrate that CST performs better than all other sparse trackers and favorably against state-of-the-art methods.
In Defense of Sparse Tracking: Circulant Sparse Tracker
Zhang, Tianzhu
2016-12-13
Sparse representation has been introduced to visual tracking by finding the best target candidate with minimal reconstruction error within the particle filter framework. However, most sparse representation based trackers have high computational cost, less than promising tracking performance, and limited feature representation. To deal with the above issues, we propose a novel circulant sparse tracker (CST), which exploits circulant target templates. Because of the circulant structure property, CST has the following advantages: (1) It can refine and reduce particles using circular shifts of target templates. (2) The optimization can be efficiently solved entirely in the Fourier domain. (3) High dimensional features can be embedded into CST to significantly improve tracking performance without sacrificing much computation time. Both qualitative and quantitative evaluations on challenging benchmark sequences demonstrate that CST performs better than all other sparse trackers and favorably against state-of-the-art methods.
Real-time wideband holographic surveillance system
Sheen, D.M.; Collins, H.D.; Hall, T.E.; McMakin, D.L.; Gribble, R.P.; Severtsen, R.H.; Prince, J.M.; Reid, L.D.
1996-09-17
A wideband holographic surveillance system including a transceiver for generating a plurality of electromagnetic waves; antenna for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; the transceiver also receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; a computer for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and a display for displaying the processed information to determine nature of the target. The computer has instructions to apply a three dimensional backward wave algorithm. 28 figs.
Language Recognition via Sparse Coding
2016-09-08
explanation is that sparse coding can achieve a near-optimal approximation of much complicated nonlinear relationship through local and piecewise linear...training examples, where x(i) ∈ RN is the ith example in the batch. Optionally, X can be normalized and whitened before sparse coding for better result...normalized input vectors are then ZCA- whitened [20]. Em- pirically, we choose ZCA- whitening over PCA- whitening , and there is no dimensionality reduction
Compact super-wideband optical antenna
Wang, Wen C.; Forber, Richard; Bui, Kenneth
2009-05-01
We present progress on advanced optical antennas, which are compact, small size-weight-power units capable to receive super wideband radiated RF signals from 30 MHz to over 3 GHz. Based on electro-optical modulation of fiber-coupled guided wave light, these dielectric E-field sensors exhibit dipole-like azimuthal omni directionality, and combine small size (channels, and high EO sensing materials. The antenna system photonic link consists of a 1550 nm PM fiber-pigtailed laser, a specialized optical modulator antenna in channel waveguide format, a wideband photoreceiver, and optical phase stabilizing components. The optical modulator antenna design employs a dielectric (no electrode) Mach-Zehnder interferometer (MZI) arranged so that sensing RF bandwidth is not limited by optical transit time effects, and MZI phase drift is bias stabilized. For a prototype optical antenna system that is < 100 in3, < 10 W, < 5 lbs, we present test data on sensitivity (< 20 mV/m-Hz1/2), RF bandwidth, and antenna directionality, and show good agreement with theoretical predictions.
Integrated wide-band low-background amplifiers
International Nuclear Information System (INIS)
Il'yushchenko, I.I.
1980-01-01
Ways of increasing stability and reproduction of characteristics of wide-band integral amplifiers that would to the least extent increase their background noises, are discussed. Considered are some certain flowsheets of integral wide-band amplifiers with low background noise of foreign production which differ from one another by construction of inlet cascades as well as by the applied feedback type. The principal flowsheets of the amplifiers and their main performances are presented. The analysis of the data obtained has revealed that microcircuits made of cascades with a common emitter and local combined feedback are most wide-band among all the considered microcircuits [ru
Shearlets and Optimally Sparse Approximations
DEFF Research Database (Denmark)
Kutyniok, Gitta; Lemvig, Jakob; Lim, Wang-Q
2012-01-01
Multivariate functions are typically governed by anisotropic features such as edges in images or shock fronts in solutions of transport-dominated equations. One major goal both for the purpose of compression as well as for an efficient analysis is the provision of optimally sparse approximations...... optimally sparse approximations of this model class in 2D as well as 3D. Even more, in contrast to all other directional representation systems, a theory for compactly supported shearlet frames was derived which moreover also satisfy this optimality benchmark. This chapter shall serve as an introduction...... to and a survey about sparse approximations of cartoon-like images by band-limited and also compactly supported shearlet frames as well as a reference for the state-of-the-art of this research field....
Sparse Representations of Hyperspectral Images
Swanson, Robin J.
2015-01-01
Hyperspectral image data has long been an important tool for many areas of sci- ence. The addition of spectral data yields significant improvements in areas such as object and image classification, chemical and mineral composition detection, and astronomy. Traditional capture methods for hyperspectral data often require each wavelength to be captured individually, or by sacrificing spatial resolution. Recently there have been significant improvements in snapshot hyperspectral captures using, in particular, compressed sensing methods. As we move to a compressed sensing image formation model the need for strong image priors to shape our reconstruction, as well as sparse basis become more important. Here we compare several several methods for representing hyperspectral images including learned three dimensional dictionaries, sparse convolutional coding, and decomposable nonlocal tensor dictionaries. Addi- tionally, we further explore their parameter space to identify which parameters provide the most faithful and sparse representations.
Sparse Representations of Hyperspectral Images
Swanson, Robin J.
2015-11-23
Hyperspectral image data has long been an important tool for many areas of sci- ence. The addition of spectral data yields significant improvements in areas such as object and image classification, chemical and mineral composition detection, and astronomy. Traditional capture methods for hyperspectral data often require each wavelength to be captured individually, or by sacrificing spatial resolution. Recently there have been significant improvements in snapshot hyperspectral captures using, in particular, compressed sensing methods. As we move to a compressed sensing image formation model the need for strong image priors to shape our reconstruction, as well as sparse basis become more important. Here we compare several several methods for representing hyperspectral images including learned three dimensional dictionaries, sparse convolutional coding, and decomposable nonlocal tensor dictionaries. Addi- tionally, we further explore their parameter space to identify which parameters provide the most faithful and sparse representations.
Wideband Autonomous Cognitive Radios for Networked Satellites Communications, Phase II
National Aeronautics and Space Administration — Wideband Autonomous Cognitive Radios (WACRs) are advanced radios that have the ability to sense state of the RF spectrum and the network and self-optimize its...
Wideband QAMC reflector's antenna for low profile applications
Grelier, M.; Jousset, M.; Mallégol, S.; Lepage, A. C.; Begaud, X.; LeMener, J. M.
2011-06-01
A wideband reflector's antenna based on quasi-artificial magnetic conductor is proposed. To validate the design, an Archimedean spiral has been backed to this new reflector. In comparison to classical solution using absorbent material, the prototype presents a very low thickness of λ/15 at the lowest operating frequency and an improved gain over a 2.4:1 bandwidth. The whole methodology to design this reflector can be applied to other wideband antennas.
An Ultra-Wideband Millimeter-Wave Phased Array
Novak, Markus H.; Miranda, Felix A.; Volakis, John L.
2016-01-01
Wideband millimeter-wave arrays are of increasing importance due to their growing use in high data rate systems, including 5G communication networks. In this paper, we present a new class of ultra-wideband millimeter wave arrays that operate from nearly 20 GHz to 90 GHz. The array is based on tightly coupled dipoles. Feeding designs and fabrication challenges are presented, and a method for suppressing feed resonances is provided.
Image understanding using sparse representations
Thiagarajan, Jayaraman J; Turaga, Pavan; Spanias, Andreas
2014-01-01
Image understanding has been playing an increasingly crucial role in several inverse problems and computer vision. Sparse models form an important component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiting the sparsity of natural signals has led to advances in several application areas including image compression, denoising, inpainting, compressed sensing, blin
Multichannel Baseband Processor for Wideband CDMA
Jalloul, Louay M. A.; Lin, Jim
2005-12-01
The system architecture of the cellular base station modem engine (CBME) is described. The CBME is a single-chip multichannel transceiver capable of processing and demodulating signals from multiple users simultaneously. It is optimized to process different classes of code-division multiple-access (CDMA) signals. The paper will show that through key functional system partitioning, tightly coupled small digital signal processing cores, and time-sliced reuse architecture, CBME is able to achieve a high degree of algorithmic flexibility while maintaining efficiency. The paper will also highlight the implementation and verification aspects of the CBME chip design. In this paper, wideband CDMA is used as an example to demonstrate the architecture concept.
Multichannel Baseband Processor for Wideband CDMA
Directory of Open Access Journals (Sweden)
Jim Lin
2005-07-01
Full Text Available The system architecture of the cellular base station modem engine (CBME is described. The CBME is a single-chip multichannel transceiver capable of processing and demodulating signals from multiple users simultaneously. It is optimized to process different classes of code-division multiple-access (CDMA signals. The paper will show that through key functional system partitioning, tightly coupled small digital signal processing cores, and time-sliced reuse architecture, CBME is able to achieve a high degree of algorithmic flexibility while maintaining efficiency. The paper will also highlight the implementation and verification aspects of the CBME chip design. In this paper, wideband CDMA is used as an example to demonstrate the architecture concept.
Ultra-Wideband Transceivers for Cochlear Implants
Directory of Open Access Journals (Sweden)
Reisenzahn Alexander
2005-01-01
Full Text Available Ultra-wideband (UWB radio offers low power consumption, low power spectral density, high immunity against interference, and other benefits, not only for consumer electronics, but also for medical devices. A cochlear implant (CI is an electronic hearing apparatus, requiring a wireless link through human tissue. In this paper we propose an UWB link for a data rate of Mbps and a propagation distance up to 500 mm. Transmitters with step recovery diode and transistor pulse generators are proposed. Two types of antennas and their filter characteristics in the UWB spectrum will be discussed. An ultra-low-power back tunnel diode receiver prototype is described and compared with conventional detector receivers.
Elementary wideband timing of radio pulsars
Energy Technology Data Exchange (ETDEWEB)
Pennucci, Timothy T. [University of Virginia, Department of Astronomy, P.O. Box 400325 Charlottesville, VA 22904-4325 (United States); Demorest, Paul B.; Ransom, Scott M., E-mail: pennucci@virginia.edu, E-mail: pdemores@nrao.edu, E-mail: sransom@nrao.edu [National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903-2475 (United States)
2014-08-01
We present an algorithm for the simultaneous measurement of a pulse time-of-arrival (TOA) and dispersion measure (DM) from folded wideband pulsar data. We extend the prescription from Taylor's 1992 work to accommodate a general two-dimensional template 'portrait', the alignment of which can be used to measure a pulse phase and DM. We show that there is a dedispersion reference frequency that removes the covariance between these two quantities and note that the recovered pulse profile scaling amplitudes can provide useful information. We experiment with pulse modeling by using a Gaussian-component scheme that allows for independent component evolution with frequency, a 'fiducial component', and the inclusion of scattering. We showcase the algorithm using our publicly available code on three years of wideband data from the bright millisecond pulsar J1824–2452A (M28A) from the Green Bank Telescope, and a suite of Monte Carlo analyses validates the algorithm. By using a simple model portrait of M28A, we obtain DM trends comparable to those measured by more standard methods, with improved TOA and DM precisions by factors of a few. Measurements from our algorithm will yield precisions at least as good as those from traditional techniques, but is prone to fewer systematic effects and is without ad hoc parameters. A broad application of this new method for dispersion measure tracking with modern large-bandwidth observing systems should improve the timing residuals for pulsar timing array experiments, such as the North American Nanohertz Observatory for Gravitational Waves.
Wideband aperture array using RF channelizers and massively parallel digital 2D IIR filterbank
Sengupta, Arindam; Madanayake, Arjuna; Gómez-García, Roberto; Engeberg, Erik D.
2014-05-01
Wideband receive-mode beamforming applications in wireless location, electronically-scanned antennas for radar, RF sensing, microwave imaging and wireless communications require digital aperture arrays that offer a relatively constant far-field beam over several octaves of bandwidth. Several beamforming schemes including the well-known true time-delay and the phased array beamformers have been realized using either finite impulse response (FIR) or fast Fourier transform (FFT) digital filter-sum based techniques. These beamforming algorithms offer the desired selectivity at the cost of a high computational complexity and frequency-dependant far-field array patterns. A novel approach to receiver beamforming is the use of massively parallel 2-D infinite impulse response (IIR) fan filterbanks for the synthesis of relatively frequency independent RF beams at an order of magnitude lower multiplier complexity compared to FFT or FIR filter based conventional algorithms. The 2-D IIR filterbanks demand fast digital processing that can support several octaves of RF bandwidth, fast analog-to-digital converters (ADCs) for RF-to-bits type direct conversion of wideband antenna element signals. Fast digital implementation platforms that can realize high-precision recursive filter structures necessary for real-time beamforming, at RF radio bandwidths, are also desired. We propose a novel technique that combines a passive RF channelizer, multichannel ADC technology, and single-phase massively parallel 2-D IIR digital fan filterbanks, realized at low complexity using FPGA and/or ASIC technology. There exists native support for a larger bandwidth than the maximum clock frequency of the digital implementation technology. We also strive to achieve More-than-Moore throughput by processing a wideband RF signal having content with N-fold (B = N Fclk/2) bandwidth compared to the maximum clock frequency Fclk Hz of the digital VLSI platform under consideration. Such increase in bandwidth is
National Research Council Canada - National Science Library
Hutchens, Robert
2001-01-01
..., A key enabler to this end is sufficient wideband satellite communications connectivity DoD's organic wideband satellite communications capabilities are inadequate, so commercial services must be used...
Sparse PCA with Oracle Property.
Gu, Quanquan; Wang, Zhaoran; Liu, Han
In this paper, we study the estimation of the k -dimensional sparse principal subspace of covariance matrix Σ in the high-dimensional setting. We aim to recover the oracle principal subspace solution, i.e., the principal subspace estimator obtained assuming the true support is known a priori. To this end, we propose a family of estimators based on the semidefinite relaxation of sparse PCA with novel regularizations. In particular, under a weak assumption on the magnitude of the population projection matrix, one estimator within this family exactly recovers the true support with high probability, has exact rank- k , and attains a [Formula: see text] statistical rate of convergence with s being the subspace sparsity level and n the sample size. Compared to existing support recovery results for sparse PCA, our approach does not hinge on the spiked covariance model or the limited correlation condition. As a complement to the first estimator that enjoys the oracle property, we prove that, another estimator within the family achieves a sharper statistical rate of convergence than the standard semidefinite relaxation of sparse PCA, even when the previous assumption on the magnitude of the projection matrix is violated. We validate the theoretical results by numerical experiments on synthetic datasets.
Science Teachers' Analogical Reasoning
Mozzer, Nilmara Braga; Justi, Rosária
2013-08-01
Analogies can play a relevant role in students' learning. However, for the effective use of analogies, teachers should not only have a well-prepared repertoire of validated analogies, which could serve as bridges between the students' prior knowledge and the scientific knowledge they desire them to understand, but also know how to introduce analogies in their lessons. Both aspects have been discussed in the literature in the last few decades. However, almost nothing is known about how teachers draw their own analogies for instructional purposes or, in other words, about how they reason analogically when planning and conducting teaching. This is the focus of this paper. Six secondary teachers were individually interviewed; the aim was to characterize how they perform each of the analogical reasoning subprocesses, as well as to identify their views on analogies and their use in science teaching. The results were analyzed by considering elements of both theories about analogical reasoning: the structural mapping proposed by Gentner and the analogical mechanism described by Vosniadou. A comprehensive discussion of our results makes it evident that teachers' content knowledge on scientific topics and on analogies as well as their pedagogical content knowledge on the use of analogies influence all their analogical reasoning subprocesses. Our results also point to the need for improving teachers' knowledge about analogies and their ability to perform analogical reasoning.
Sparse Regression by Projection and Sparse Discriminant Analysis
Qi, Xin
2015-04-03
© 2015, © American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America. Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high-dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths and the tuning parameters are determined by a cross-validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares, and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared with the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplementary materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.
Algorithms for sparse, symmetric, definite quadratic lambda-matrix eigenproblems
International Nuclear Information System (INIS)
Scott, D.S.; Ward, R.C.
1981-01-01
Methods are presented for computing eigenpairs of the quadratic lambda-matrix, M lambda 2 + C lambda + K, where M, C, and K are large and sparse, and have special symmetry-type properties. These properties are sufficient to insure that all the eigenvalues are real and that theory analogous to the standard symmetric eigenproblem exists. The methods employ some standard techniques such as partial tri-diagonalization via the Lanczos Method and subsequent eigenpair calculation, shift-and- invert strategy and subspace iteration. The methods also employ some new techniques such as Rayleigh-Ritz quadratic roots and the inertia of symmetric, definite, quadratic lambda-matrices
Apparatus And Method For Wireless Monitoring Using Ultra-wideband Frequencies
Sana, Furrukh
2015-04-23
A system for and a method of wirelessly monitoring one or more patients can include transmitting ultra-wideband pulses toward the one or more patients, receiving ultra-wideband signals, and sampling the ultra-wideband signals. Sampling the ultra-wideband pulses can be performed with a sample rate that is less than the Nyquist rate. Impulse response can be estimated and/or recovered by exploiting sparsity of the impulse response.
Intuitive analog circuit design
Thompson, Marc
2013-01-01
Intuitive Analog Circuit Design outlines ways of thinking about analog circuits and systems that let you develop a feel for what a good, working analog circuit design should be. This book reflects author Marc Thompson's 30 years of experience designing analog and power electronics circuits and teaching graduate-level analog circuit design, and is the ideal reference for anyone who needs a straightforward introduction to the subject. In this book, Dr. Thompson describes intuitive and ""back-of-the-envelope"" techniques for designing and analyzing analog circuits, including transistor amplifi
A Channelization-Based DOA Estimation Method for Wideband Signals
Directory of Open Access Journals (Sweden)
Rui Guo
2016-07-01
Full Text Available In this paper, we propose a novel direction of arrival (DOA estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR using direct wideband radio frequency (RF digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method.
Ultra wideband wireless body area networks
Thotahewa, Kasun Maduranga Silva; Yuce, Mehmet Rasit
2014-01-01
This book explores the design of ultra wideband (UWB) technology for wireless body-area networks (WBAN). The authors describe a novel implementation of WBAN sensor nodes that use UWB for data transmission and narrow band for data reception, enabling low power sensor nodes, with high data rate capability. The discussion also includes power efficient, medium access control (MAC) protocol design for UWB based WBAN applications and the authors present a MAC protocol in which a guaranteed delivery mechanism is utilized to transfer data with high priority. Readers will also benefit from this book’s feasibility analysis of the UWB technology for human implant applications through the study of electromagnetic and thermal power absorption of human tissue that is exposed to UWB signals. • Describes hardware platform development for IR-UWB based WBAN communication; • Discusses power efficient medium access control (MAC) protocol design for IR-UWB based WBAN applications; • Includes feasibility analy...
Ultra-wideband ranging precision and accuracy
International Nuclear Information System (INIS)
MacGougan, Glenn; O'Keefe, Kyle; Klukas, Richard
2009-01-01
This paper provides an overview of ultra-wideband (UWB) in the context of ranging applications and assesses the precision and accuracy of UWB ranging from both a theoretical perspective and a practical perspective using real data. The paper begins with a brief history of UWB technology and the most current definition of what constitutes an UWB signal. The potential precision of UWB ranging is assessed using Cramer–Rao lower bound analysis. UWB ranging methods are described and potential error sources are discussed. Two types of commercially available UWB ranging radios are introduced which are used in testing. Actual ranging accuracy is assessed from line-of-sight testing under benign signal conditions by comparison to high-accuracy electronic distance measurements and to ranges derived from GPS real-time kinematic positioning. Range measurements obtained in outdoor testing with line-of-sight obstructions and strong reflection sources are compared to ranges derived from classically surveyed positions. The paper concludes with a discussion of the potential applications for UWB ranging
Wide-band cable systems at SLAC
International Nuclear Information System (INIS)
Struven, W.
1983-01-01
SLAC's first cable TV system was installed in 1979 to remotely monitor a narrow pulse which was generated in the west end of the klystron gallery. When Stanford Linear Collider (SLC) experimental work started at the west end of the accelerator, the original 1979 cable was upgraded to a bidirectional system so that 2 MBaud point-to-point data and several video and 9600 baud channels could be transmitted. The implementation of the SLC requires a complete upgrading of the accelerator control system. The system is based on a distributed processing configuration using a PDP11/780 VAX in the Main Control Center (MCC) and Intel single-board computers in a multibus configuration along the accelerator. The high-speed data linking is supplied by a 1 MBaud Time Division Multiple Access (TDMA) Network. The same cable is used to provide video, low-speed data, voice and high-speed point-to-point data services. The transmission system will utilize a wideband midsplit cable facility to collect and distribute signals to all parts of the network
Gelmini, A.; Gottardi, G.; Moriyama, T.
2017-10-01
This work presents an innovative computational approach for the inversion of wideband ground penetrating radar (GPR) data. The retrieval of the dielectric characteristics of sparse scatterers buried in a lossy soil is performed by combining a multi-task Bayesian compressive sensing (MT-BCS) solver and a frequency hopping (FH) strategy. The developed methodology is able to benefit from the regularization capabilities of the MT-BCS as well as to exploit the multi-chromatic informative content of GPR measurements. A set of numerical results is reported in order to assess the effectiveness of the proposed GPR inverse scattering technique, as well as to compare it to a simpler single-task implementation.
Aragonès, Enriqueta; Gilboa, Itzhak; Postlewaite, Andrew; Schmeidler, David; Universitat Autònoma de Barcelona. Unitat de Fonaments de l'Anàlisi Econòmica; Universitat Autònoma de Barcelona. Institut d'Anàlisi Econòmica
2013-01-01
The art of rhetoric may be defined as changing other people's minds (opinions, beliefs) without providing them new information. One tech- nique heavily used by rhetoric employs analogies. Using analogies, one may draw the listener's attention to similarities between cases and to re-organize existing information in a way that highlights certain reg- ularities. In this paper we offer two models of analogies, discuss their theoretical equivalence, and show that finding good analogies is a com- p...
Effect of direction on loudness for wideband and reverberant sounds
DEFF Research Database (Denmark)
Sivonen, Ville Pekka; Ellermeier, Wolfgang
2006-01-01
The effect of incidence angle on loudness was investigated for wideband and reverberant sounds. In an adaptive procedure, five listeners matched the loudness of a sound coming from five incidence angles in the horizontal plane to that of the same sound with frontal incidence. The stimuli were...... presented to the listeners via individual binaural synthesis. The results confirm that loudness depends on sound incidence angle, as it does for narrow-band, anechoic sounds. The directional effects, however, were attenuated with the wideband and reverberant stimuli used in the present investigation....
Ultra-wideband RCS reduction using novel configured chessboard metasurface
International Nuclear Information System (INIS)
Zhuang Ya-Qiang; Wang Guang-Ming; Xu He-Xiu
2017-01-01
A novel artificial magnetic conductor (AMC) metasurface is proposed with ultra-wideband 180° phase difference for radar cross section (RCS) reduction. It is composed of two dual-resonant AMC cells, which enable a broadband phase difference of 180°±30° from 7.9 GHz to 19.2 GHz to be achieved. A novel strategy is devised by dividing each rectangular grid in a chessboard configuration into four triangular grids, leading to a further reduction of peak bistatic RCS. Both full-wave simulation and measurement results show that the proposed metasurface presents a good RCS reduction property over an ultra-wideband frequency range. (paper)
Timed arrays wideband and time varying antenna arrays
Haupt, Randy L
2015-01-01
Introduces timed arrays and design approaches to meet the new high performance standards The author concentrates on any aspect of an antenna array that must be viewed from a time perspective. The first chapters briefly introduce antenna arrays and explain the difference between phased and timed arrays. Since timed arrays are designed for realistic time-varying signals and scenarios, the book also reviews wideband signals, baseband and passband RF signals, polarization and signal bandwidth. Other topics covered include time domain, mutual coupling, wideband elements, and dispersion. The auth
Substrate Effects in Wideband SiGe HBT Mixer Circuits
DEFF Research Database (Denmark)
Johansen, Tom Keinicke; Vidkjær, Jens; Krozer, Viktor
2005-01-01
are also applied to predict short distance substrate coupling effects. Simulation results using extracted equivalent circuit models and substrate coupling networks are compared with experimental results obtained on a wideband mixer circuit implemented in a 0.35 μm, 60 GHz ft SiGe HBT BiCMOS process.......In this paper, the influence from substrate effects on the performance of wideband SiGe HBT mixer circuits is investigated. Equivalent circuit models including substrate networks are extracted from on-wafer test structures and compared with electromagnetic simulations. Electromagnetic simulations...
A new metamaterial-based wideband rectangular invisibility cloak
Islam, S. S.; Hasan, M. M.; Faruque, M. R. I.
2018-02-01
A new metamaterial-based wideband electromagnetic rectangular cloak is being introduced in this study. The metamaterial unit cell shows sharp transmittances in the C- and X-bands and displays wideband negative effective permittivity region there. The metamaterial unit cell was then applied in designing a rectangular-shaped electromagnetic cloak. The scattering reduction technique was adopted for the cloaking operation. The cloak operates in the certain portion of C-and X-bands that covers more than 4 GHz bandwidth region. The experimental results were provided as well for the metamaterial and the cloak.
Hyndman, D E
2013-01-01
Analog and Hybrid Computing focuses on the operations of analog and hybrid computers. The book first outlines the history of computing devices that influenced the creation of analog and digital computers. The types of problems to be solved on computers, computing systems, and digital computers are discussed. The text looks at the theory and operation of electronic analog computers, including linear and non-linear computing units and use of analog computers as operational amplifiers. The monograph examines the preparation of problems to be deciphered on computers. Flow diagrams, methods of ampl
Stefanovic, Danica
2008-01-01
Structured Analog CMOS Design describes a structured analog design approach that makes it possible to simplify complex analog design problems and develop a design strategy that can be used for the design of large number of analog cells. It intentionally avoids treating the analog design as a mathematical problem, developing a design procedure based on the understanding of device physics and approximations that give insight into parameter interdependences. The proposed transistor-level design procedure is based on the EKV modeling approach and relies on the device inversion level as a fundament
Wideband filter radiometers for blackbody temperature measurements
Boivin, L. P.; Bamber, C.; Gaertner, A. A.; Gerson, R. K.; Woods, D. J.; Woolliams, E. R.
2010-10-01
The use of high-temperature blackbody (HTBB) radiators to realize primary spectral irradiance scales requires that the operating temperature of the HTBB be accurately determined. We have developed five filter radiometers (FRs) to measure the temperature of the National Research Council of Canada's HTBB. The FRs are designed to minimize sensitivity to ambient temperature fluctuations. They incorporate air-spaced colored glass filters and a Si photodiode detector that are housed in a cell whose temperature is controlled to ±0.1°C by means of annular thermoelectric elements at the front and rear of the cell. These wideband filter radiometers operate in four different wavelength bands. The spectral responsivity measurements were performed in an underfill geometry for a power-mode calibration that is traceable to NRC's cryogenic radiometer. The spectral temperature sensitivity of each of these FRs has been measured. The apertures for these FRs were cold-formed by swaging machine-cut apertures onto precision dowel pins. A description of the filter radiometer design, fabrication and testing, together with a detailed uncertainty analysis, is presented. We derive the equations that relate the spectral irradiance measured by the FRs to the spectral radiance and temperature of the HTBB, and deal specifically with the change of index of refraction over the path of the radiation from the interior of the HTBB to the FRs. We believe these equations are more accurate than recently published derivations. Our measurements of the operating temperature of our HTBB working at temperatures near 2500 K, 2700 K and 2900 K, together with measurements using a pyrometer, show agreement between the five filter radiometers and with the pyrometer to within the estimated uncertainties.
Optical networks for wideband sensor array
Sheng, Lin Horng
2011-12-01
This thesis presents the realization of novel systems for optical sensing networks with an array of long-period grating (LPG) sensors. As a launching point of the thesis, the motivation to implement optical sensing network in precisely catering LPG sensors is presented. It highlights the flexibility of the sensing network to act as the foundation in order to boost the application of the various LPG sensor design in biological and chemical sensing. After the thorough study on the various optical sensing networks, sub-carrier multiplexing (SCM) and optical time division multiplexing (OTDM) schemes are adopted in conjunction with tunable laser source (TLS) to facilitate simultaneous interrogation of the LPG sensors array. In fact, these systems are distinct to have the capability to accommodate wideband optical sensors. Specifically, the LPG sensors which is in 20nm bandwidth are identified to operate in these systems. The working principles of the systems are comprehensively elucidated in this thesis. It highlights the mathematical approach to quantify the experimental setup of the optical sensing network. Additionally, the system components of the designs are identified and methodically characterized so that the components well operate in the designed environment. A mockup has been setup to demonstrate the application in sensing of various liquid indices and analyse the response of the LPG sensors in order to evaluate the performance of the systems. Eventually, the resemblance of the demultiplexed spectral response to the pristine spectral response are quantified to have excellent agreement. Finally, the promising result consistency of the systems is verified through repeatability test.
Sparse Matrices in Frame Theory
DEFF Research Database (Denmark)
Lemvig, Jakob; Krahmer, Felix; Kutyniok, Gitta
2014-01-01
Frame theory is closely intertwined with signal processing through a canon of methodologies for the analysis of signals using (redundant) linear measurements. The canonical dual frame associated with a frame provides a means for reconstruction by a least squares approach, but other dual frames...... yield alternative reconstruction procedures. The novel paradigm of sparsity has recently entered the area of frame theory in various ways. Of those different sparsity perspectives, we will focus on the situations where frames and (not necessarily canonical) dual frames can be written as sparse matrices...
Diffusion Indexes with Sparse Loadings
DEFF Research Database (Denmark)
Kristensen, Johannes Tang
The use of large-dimensional factor models in forecasting has received much attention in the literature with the consensus being that improvements on forecasts can be achieved when comparing with standard models. However, recent contributions in the literature have demonstrated that care needs...... to the problem by using the LASSO as a variable selection method to choose between the possible variables and thus obtain sparse loadings from which factors or diffusion indexes can be formed. This allows us to build a more parsimonious factor model which is better suited for forecasting compared...... it to be an important alternative to PC....
Sparse Linear Identifiable Multivariate Modeling
DEFF Research Database (Denmark)
Henao, Ricardo; Winther, Ole
2011-01-01
and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable......In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...
Programming for Sparse Minimax Optimization
DEFF Research Database (Denmark)
Jonasson, K.; Madsen, Kaj
1994-01-01
We present an algorithm for nonlinear minimax optimization which is well suited for large and sparse problems. The method is based on trust regions and sequential linear programming. On each iteration, a linear minimax problem is solved for a basic step. If necessary, this is followed...... by the determination of a minimum norm corrective step based on a first-order Taylor approximation. No Hessian information needs to be stored. Global convergence is proved. This new method has been extensively tested and compared with other methods, including two well known codes for nonlinear programming...
Dynamic Representations of Sparse Graphs
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Fagerberg, Rolf
1999-01-01
We present a linear space data structure for maintaining graphs with bounded arboricity—a large class of sparse graphs containing e.g. planar graphs and graphs of bounded treewidth—under edge insertions, edge deletions, and adjacency queries. The data structure supports adjacency queries in worst...... case O(c) time, and edge insertions and edge deletions in amortized O(1) and O(c+log n) time, respectively, where n is the number of nodes in the graph, and c is the bound on the arboricity....
Detecting analogies unconsciously
Directory of Open Access Journals (Sweden)
Thomas Peter Reber
2014-01-01
Full Text Available Analogies may arise from the conscious detection of similarities between a present and a past situation. In this functional magnetic resonance imaging study, we tested whether young volunteers would detect analogies unconsciously between a current supraliminal (visible and a past subliminal (invisible situation. The subliminal encoding of the past situation precludes awareness of analogy detection in the current situation. First, participants encoded subliminal pairs of unrelated words in either one or nine encoding trials. Later, they judged the semantic fit of supraliminally presented new words that either retained a previously encoded semantic relation (‘analog’ or not (‘broken analog’. Words in analogs versus broken analogs were judged closer semantically, which reflects unconscious analogy detection. Hippocampal activity associated with subliminal encoding correlated with the behavioral measure of unconscious analogy detection. Analogs versus broken analogs were processed with reduced prefrontal but enhanced medial temporal activity. We conclude that analogous episodes can be detected even unconsciously drawing on the episodic memory network.
Bayesian Inference Methods for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand
2013-01-01
This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...
Ultra wideband coplanar waveguide fed spiral antenna for humanitarian demining
DEFF Research Database (Denmark)
Thaysen, Jesper; Jakobsen, Kaj Bjarne; Appel-Hansen, Jørgen
2000-01-01
to 1 bandwidth with a return loss better than 10 dB from 0.4 to 3.8 GHz is presented. A wideband balun covering the frequency range of the antenna was developed. The constructed spiral antenna is very useful in a stepped frequency ground penetrating radar for humanitarian demining due to the very...
Ultra-wideband MMICs for remote sensing applications
DEFF Research Database (Denmark)
Johansen, Tom Keinicke; Vidkjær, Jens; Krozer, Viktor
2003-01-01
This paper presents an overview of the current activity at the Technical University of Denmark in the field of ultra-wideband monolitic microwave integrated circuits (MMICs) for next-generation high-resolution synthetic aperature radar (SAR) systems. The transfer function requirements for MMIC co...
Resilience of LTE networks against smart jamming attacks: Wideband model
Aziz, Farhan M.; Shamma, Jeff S.; Stuber, Gordon L.
2015-01-01
communications. We have previously shown that LTE networks are vulnerable to Denial-of-Service (DOS) and loss of service attacks from smart jammers. In this paper, we extend our previous work on resilience of LTE networks to wideband multipath fading channel
Digital Receiver Design for Transmitted Reference Ultra-Wideband Systems
Wang, Y.; Leus, G.; Van der Veen, A.J.
2009-01-01
A complete detection, channel estimation, synchronization, and equalization scheme for a transmitted reference (TR) ultra-wideband (UWB) system is proposed in this paper. The scheme is based on a data model which admits a moderate data rate and takes both the interframe interference (IFI) and the
Image fusion using sparse overcomplete feature dictionaries
Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt
2015-10-06
Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.
Sparse Image Reconstruction in Computed Tomography
DEFF Research Database (Denmark)
Jørgensen, Jakob Sauer
In recent years, increased focus on the potentially harmful effects of x-ray computed tomography (CT) scans, such as radiation-induced cancer, has motivated research on new low-dose imaging techniques. Sparse image reconstruction methods, as studied for instance in the field of compressed sensing...... applications. This thesis takes a systematic approach toward establishing quantitative understanding of conditions for sparse reconstruction to work well in CT. A general framework for analyzing sparse reconstruction methods in CT is introduced and two sets of computational tools are proposed: 1...... contributions to a general set of computational characterization tools. Thus, the thesis contributions help advance sparse reconstruction methods toward routine use in...
Dobkin, Bob
2012-01-01
Analog circuit and system design today is more essential than ever before. With the growth of digital systems, wireless communications, complex industrial and automotive systems, designers are being challenged to develop sophisticated analog solutions. This comprehensive source book of circuit design solutions aids engineers with elegant and practical design techniques that focus on common analog challenges. The book's in-depth application examples provide insight into circuit design and application solutions that you can apply in today's demanding designs. <
Patterson, Richard L.; Elbuluk, Malik; Hammoud, Ahmad; VanKeuls, Frederick W.
2009-01-01
This report discusses the performance of silicon germanium, wideband gain amplifiers under extreme temperatures. The investigated devices include Texas Instruments THS4304-SP and THS4302 amplifiers. Both chips are manufactured using the BiCom3 process based on silicon germanium technology along with silicon-on-insulator (SOI) buried oxide layers. The THS4304-SP device was chosen because it is a Class V radiation-tolerant (150 kRad, TID silicon), voltage-feedback operational amplifier designed for use in high-speed analog signal applications and is very desirable for NASA missions. It operates with a single 5 V power supply [1]. It comes in a 10-pin ceramic flatpack package, and it provides balanced inputs, low offset voltage and offset current, and high common mode rejection ratio. The fixed-gain THS4302 chip, which comes in a 16-pin leadless package, offers high bandwidth, high slew rate, low noise, and low distortion [2]. Such features have made the amplifier useful in a number of applications such as wideband signal processing, wireless transceivers, intermediate frequency (IF) amplifier, analog-to-digital converter (ADC) preamplifier, digital-to-analog converter (DAC) output buffer, measurement instrumentation, and medical and industrial imaging.
Sarpeshkar, R
2014-03-28
We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog-digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA-protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations.
When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores
Wang, Jim Jing-Yan; Cui, Xuefeng; Yu, Ge; Guo, Lili; Gao, Xin
2017-01-01
Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays
Neural Network for Sparse Reconstruction
Directory of Open Access Journals (Sweden)
Qingfa Li
2014-01-01
Full Text Available We construct a neural network based on smoothing approximation techniques and projected gradient method to solve a kind of sparse reconstruction problems. Neural network can be implemented by circuits and can be seen as an important method for solving optimization problems, especially large scale problems. Smoothing approximation is an efficient technique for solving nonsmooth optimization problems. We combine these two techniques to overcome the difficulties of the choices of the step size in discrete algorithms and the item in the set-valued map of differential inclusion. In theory, the proposed network can converge to the optimal solution set of the given problem. Furthermore, some numerical experiments show the effectiveness of the proposed network in this paper.
Diffusion Indexes With Sparse Loadings
DEFF Research Database (Denmark)
Kristensen, Johannes Tang
2017-01-01
The use of large-dimensional factor models in forecasting has received much attention in the literature with the consensus being that improvements on forecasts can be achieved when comparing with standard models. However, recent contributions in the literature have demonstrated that care needs...... to the problem by using the least absolute shrinkage and selection operator (LASSO) as a variable selection method to choose between the possible variables and thus obtain sparse loadings from which factors or diffusion indexes can be formed. This allows us to build a more parsimonious factor model...... in forecasting accuracy and thus find it to be an important alternative to PC. Supplementary materials for this article are available online....
Sparse and stable Markowitz portfolios.
Brodie, Joshua; Daubechies, Ingrid; De Mol, Christine; Giannone, Domenico; Loris, Ignace
2009-07-28
We consider the problem of portfolio selection within the classical Markowitz mean-variance framework, reformulated as a constrained least-squares regression problem. We propose to add to the objective function a penalty proportional to the sum of the absolute values of the portfolio weights. This penalty regularizes (stabilizes) the optimization problem, encourages sparse portfolios (i.e., portfolios with only few active positions), and allows accounting for transaction costs. Our approach recovers as special cases the no-short-positions portfolios, but does allow for short positions in limited number. We implement this methodology on two benchmark data sets constructed by Fama and French. Using only a modest amount of training data, we construct portfolios whose out-of-sample performance, as measured by Sharpe ratio, is consistently and significantly better than that of the naïve evenly weighted portfolio.
SPARSE FARADAY ROTATION MEASURE SYNTHESIS
International Nuclear Information System (INIS)
Andrecut, M.; Stil, J. M.; Taylor, A. R.
2012-01-01
Faraday rotation measure synthesis is a method for analyzing multichannel polarized radio emissions, and it has emerged as an important tool in the study of Galactic and extragalactic magnetic fields. The method requires the recovery of the Faraday dispersion function from measurements restricted to limited wavelength ranges, which is an ill-conditioned deconvolution problem. Here, we discuss a recovery method that assumes a sparse approximation of the Faraday dispersion function in an overcomplete dictionary of functions. We discuss the general case when both thin and thick components are included in the model, and we present the implementation of a greedy deconvolution algorithm. We illustrate the method with several numerical simulations that emphasize the effect of the covered range and sampling resolution in the Faraday depth space, and the effect of noise on the observed data.
Lin, Shih-Yin; Singh, Chandralekha
2011-01-01
Learning physics requires understanding the applicability of fundamental principles in a variety of contexts that share deep features. One way to help students learn physics is via analogical reasoning. Students can be taught to make an analogy between situations that are more familiar or easier to understand and another situation where the same…
Baser, Mustafa
2007-01-01
Students have difficulties in physics because of the abstract nature of concepts and principles. One of the effective methods for overcoming students' difficulties is the use of analogies to visualize abstract concepts to promote conceptual understanding. According to Iding, analogies are consistent with the tenets of constructivist learning…
Numerical solution of large sparse linear systems
International Nuclear Information System (INIS)
Meurant, Gerard; Golub, Gene.
1982-02-01
This note is based on one of the lectures given at the 1980 CEA-EDF-INRIA Numerical Analysis Summer School whose aim is the study of large sparse linear systems. The main topics are solving least squares problems by orthogonal transformation, fast Poisson solvers and solution of sparse linear system by iterative methods with a special emphasis on preconditioned conjuguate gradient method [fr
Sparse seismic imaging using variable projection
Aravkin, Aleksandr Y.; Tu, Ning; van Leeuwen, Tristan
2013-01-01
We consider an important class of signal processing problems where the signal of interest is known to be sparse, and can be recovered from data given auxiliary information about how the data was generated. For example, a sparse Green's function may be recovered from seismic experimental data using
Optical analogy. Synthesis report
International Nuclear Information System (INIS)
1965-01-01
The authors report the study of conditions under which light attenuation (reflection, diffusion, absorption) and the attenuation of some radiations (notably thermal neutrons) can be described with analogical calculations. The analogy between light physical properties and neutron properties is not searched for, but the analogy between their attenuation characteristics. After having discussed this possible analogy, they propose a mathematical formulation of neutron and optical phenomena which could theoretically justify the optical analogy. The second part reports a more practical study of optics problems such as the study of simple optics materials and illumination measurements, or more precisely the study of angular distributions of optical reflections, a determination of such angular distributions, and an experimental determination of the albedo
2015-06-01
adequately reconstructed by taking the inverse transform of only the large coefficients. In transform coding, a data set can be represented as ...transformed back into the measurement domain using the inverse transform , which in this case is the inverse Fourier transform or inverse cosine
Directory of Open Access Journals (Sweden)
Qing Xie
2016-01-01
Full Text Available The partial discharge (PD detection of electrical equipment is important for the safe operation of power system. The ultrasonic signal generated by the PD in the oil is a broadband signal. However, most methods of the array signal processing are used for the narrowband signal at present, and the effect of some methods for processing wideband signals is not satisfactory. Therefore, it is necessary to find new broadband signal processing methods to improve detection ability of the PD source. In this paper, the direction of arrival (DOA estimation method based on sparse representation of eigenvector is proposed, and this method can further reduce the noise interference. Moreover, the simulation results show that this direction finding method is feasible for broadband signal and thus improve the following positioning accuracy of the three-array localization method. And experimental results verify that the direction finding method based on sparse representation of eigenvector is feasible for the ultrasonic array, which can achieve accurate estimation of direction of arrival and improve the following positioning accuracy. This can provide important guidance information for the equipment maintenance in the practical application.
Malav, O P; Talukder, S; Gokulakrishnan, P; Chand, S
2015-01-01
The health-conscious consumers are in search of nutritious and convenient food item which can be best suited in their busy life. The vegetarianism is the key for the search of such food which resembles the meat in respect of nutrition and sensory characters, but not of animal origin and contains vegetable or its modified form, this is the point when meat analog evolved out and gets shape. The consumers gets full satisfaction by consumption of meat analog due to its typical meaty texture, appearance and the flavor which are being imparted during the skilled production of meat analog. The supplement of protein in vegetarian diet through meat alike food can be fulfilled by incorporating protein-rich vegetative food grade materials in meat analog and by adopting proper technological process which can promote the proper fabrication of meat analog with acceptable meat like texture, appearance, flavor, etc. The easily available vegetables, cereals, and pulses in India have great advantages and prospects to be used in food products and it can improve the nutritional and functional characters of the food items. The various form and functional characters of food items are available world over and attracts the meat technologists and the food processors to bring some innovativeness in meat analog and its presentation and marketability so that the acceptability of meat analog can be overgrown by the consumers.
Orthogonal sparse linear discriminant analysis
Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun
2018-03-01
Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.
Spectra of sparse random matrices
International Nuclear Information System (INIS)
Kuehn, Reimer
2008-01-01
We compute the spectral density for ensembles of sparse symmetric random matrices using replica. Our formulation of the replica-symmetric ansatz shares the symmetries of that suggested in a seminal paper by Rodgers and Bray (symmetry with respect to permutation of replica and rotation symmetry in the space of replica), but uses a different representation in terms of superpositions of Gaussians. It gives rise to a pair of integral equations which can be solved by a stochastic population-dynamics algorithm. Remarkably our representation allows us to identify pure-point contributions to the spectral density related to the existence of normalizable eigenstates. Our approach is not restricted to matrices defined on graphs with Poissonian degree distribution. Matrices defined on regular random graphs or on scale-free graphs, are easily handled. We also look at matrices with row constraints such as discrete graph Laplacians. Our approach naturally allows us to unfold the total density of states into contributions coming from vertices of different local coordinations and an example of such an unfolding is presented. Our results are well corroborated by numerical diagonalization studies of large finite random matrices
Thermal Studies on the SPS Wideband Transverse Feedback Kicker
Roggen, Toon; Hofle, Wolfgang; Montesinos, Eric; CERN. Geneva. ATS Department
2016-01-01
As part of the SPS wideband transverse feedback system in the framework of the LHC Injector Upgrade (LIU) project, a wideband kicker design is being proposed. Vertical beam instabilities due to intensity dependent effects (electron cloud instability (ECI) and transverse mode coupling instability (TMCI)) are potentially suppressed by using a feedback system driving such a kicker system. One of the options for a kicker is a one meter long slotted-coaxial kicker, providing a substantial vertical kick strength (10ˉ5 –10ˉ4 eV.s/m) over a bandwidth ranging from nearly DC to 1 GHz. The necessary kick strength requires a total power of 4 kW. This note describes thermal studies that assisted in the material choice of the feedthroughs of the slotted-coaxial kicker and guided the design choices.
Wideband MIMO Channel Capacity Analysis in Multiprobe Anechoic Chamber Setups
DEFF Research Database (Denmark)
Fan, Wei; Kyosti, Pekka; Nielsen, Jesper Ødum
2016-01-01
been used to determine the test area size for a limited number of probes. However, it is desirable that the test area size is defined in terms of data rate deviation of the simulated channel in the laboratory from that of the target channel model. This paper reports MIMO capacity analysis results...... for wideband spatio-temporal channel models, with emphasis on the impact of spatial correlation at the transmit (Tx) side, the channel model, and the spatial correlation at the Rx side on the capacity simulation accuracy. Simulation results show that the number of probes is irrelevant to capacity simulation......This paper discusses over the air (OTA) testing for multiple input multiple output (MIMO) capable terminals with emphasis on wideband MIMO channel capacity analysis in a multi-probe anechoic chamber setup. In the literature, the spatial correlation simulation accuracy at the receiver (Rx) side has...
Troubleshooting analog circuits
Pease, Robert A
1991-01-01
Troubleshooting Analog Circuits is a guidebook for solving product or process related problems in analog circuits. The book also provides advice in selecting equipment, preventing problems, and general tips. The coverage of the book includes the philosophy of troubleshooting; the modes of failure of various components; and preventive measures. The text also deals with the active components of analog circuits, including diodes and rectifiers, optically coupled devices, solar cells, and batteries. The book will be of great use to both students and practitioners of electronics engineering. Other
Discriminative sparse coding on multi-manifolds
Wang, J.J.-Y.; Bensmail, H.; Yao, N.; Gao, Xin
2013-01-01
Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.
Discriminative sparse coding on multi-manifolds
Wang, J.J.-Y.
2013-09-26
Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.
Compressive Detection Using Sub-Nyquist Radars for Sparse Signals
Directory of Open Access Journals (Sweden)
Ying Sun
2016-01-01
Full Text Available This paper investigates the compression detection problem using sub-Nyquist radars, which is well suited to the scenario of high bandwidths in real-time processing because it would significantly reduce the computational burden and save power consumption and computation time. A compressive generalized likelihood ratio test (GLRT detector for sparse signals is proposed for sub-Nyquist radars without ever reconstructing the signal involved. The performance of the compressive GLRT detector is analyzed and the theoretical bounds are presented. The compressive GLRT detection performance of sub-Nyquist radars is also compared to the traditional GLRT detection performance of conventional radars, which employ traditional analog-to-digital conversion (ADC at Nyquist sampling rates. Simulation results demonstrate that the former can perform almost as well as the latter with a very small fraction of the number of measurements required by traditional detection in relatively high signal-to-noise ratio (SNR cases.
Closely Mounted Compact Wideband Diversity Antenna for Mobile Phone Applications
Directory of Open Access Journals (Sweden)
Bunggil Yu
2012-01-01
Full Text Available Here a compact wideband diversity antenna covering the PCS/UMTS/WiMAX bands with high isolation and low enveloped correlation coefficient (ECC is proposed. To widen the bandwidth, the proposed antenna uses a structure with a gap-coupled feed and an inductively shorted line that has capacitive compensation between the radiator and the ground plane. Also, a suspended line with a parasitic element is used to enhance the isolation between the two antennas.
Doppler Processing with Ultra-Wideband (UWB) Radar Revisited
2018-01-01
REPORT TYPE Technical Note 3. DATES COVERED (From - To) December 2017 4. TITLE AND SUBTITLE Doppler Processing with Ultra-Wideband (UWB) Radar...unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT This technical note revisits previous work performed at the US Army Research Laboratory related to...target considered previously is proportional to a delayed version of the transmitted signal, up to a complex constant factor. We write the received
A wideband Noise-Canceling CMOS LNA exploiting a transformer
Blaakmeer, S.C.; Klumperink, Eric A.M.; Leenaerts, Domine M.W.; Nauta, Bram
2006-01-01
Abstract — A broadband LNA incorporating single-ended to differential conversion, has been successfully implemented using a noise-canceling technique and a single on-chip transformer. The LNA achieves a high voltage gain of 19dB, a wideband input match (2.5–4.0 GHz), and a Noise Figure of 4–5.4 dB,
A wideband Noise-Canceling CMOS LNA exploiting a transformer
Blaakmeer, S.C.; Klumperink, Eric A.M.; Leenaerts, Domine M.W.; Nauta, Bram
2006-01-01
A broadband LNA incorporating single-ended to differential conversion, has been successfully implemented using a noise-canceling technique and a single on-chip transformer. The LNA achieves a high voltage gain of 19dB, a wideband input match (2.5–4.0 GHz), and a Noise Figure of 4–5.4 dB, while
An inductorless wideband LNA with a new noise canceling technique
MOGHADAM, POURIA PAZHOUHESH; ABRISHAMIFAR, ADIB
2017-01-01
An inductorless wideband low-noise amplifier (LNA) employing a new noise canceling technique for multistandard applications is presented. The main amplifier has a cascode common gate structure, which provides good input impedance matching and isolation. The proposed noise canceling technique not only improves the noise figure and power gain but also embeds a g$_{m}$-boosting technique in itself, which reduces the power consumption of the main amplifier. Using current-steering and ...
Ultra-Wideband Electromagnetic Pulse Propagation through Causal Media
2016-03-04
AFRL-AFOSR-VA-TR-2016-0112 Ultra-Wideband Electromagnetic Pulse Propagation through Causal Media Natalie Cartwright RESEARCH FOUNDATION OF STATE... Electromagnetic Pulse Propagation through Causal Media 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-13-1-0013 5c. PROGRAM ELEMENT NUMBER 61102F 6...SUPPLEMENTARY NOTES 14. ABSTRACT When an electromagnetic pulse travels through a dispersive material each frequency of the transmitted pulse changes in both
Ruggedizing Printed Circuit Boards Using a Wideband Dynamic Absorber
Directory of Open Access Journals (Sweden)
V.C. Ho
2003-01-01
Full Text Available The existing approaches to ruggedizing inherently fragile and sensitive critical components of electronic equipment such as printed circuit boards (PCB for use in hostile industrial and military environment are either insufficient or expensive. This paper addresses a novel approach towards ruggedizing commercial-off-the-shelf PCBs using a miniature wideband dynamic absorber. The optimisation technique used relies on the experimentally measured vibration spectra and complex receptance of the original PCB.
Ultra-Wideband Coplanar-Fed Monopoles: A Comparative Study
Directory of Open Access Journals (Sweden)
J. Jilkova
2008-04-01
Full Text Available The paper provides an experimental comparison of four types of ultra-wideband coplanar-fed planar monopole antennas. Parameters of the open stub completed by an L-shaped monopole and the cross monopole were adopted from the literature. The forked monopole and the coplanar monopole were fabricated and measured. Monopoles were compared from the viewpoint of the impedance bandwidth, gain, directivity patterns and dimensions.
A Wideband Autonomous Cognitive Radio Development and Prototyping System
2017-11-14
three infrastructure modules (a Network Spectrum Analyzer, a Vector Signal Generator and a Rapid Printed Circuit Board (PCB) Fabrication Unit) and a...Antennas for Mobile Platforms”, 02/01/17-12/31/17 ($100K), Honeywell FM&T. 3. S. K. Jayaweera (Principal Investigator) and C. G. Christodoulou “Wideband...Signal Generator and a Rapid Printed Circuit Board (PCB) Fabrication Unit) and a Software Defined Radio (SDR) testbed made of several USRP SDR
Detection of moving humans in UHF wideband SAR
Sjögren, Thomas K.; Ulander, Lars M. H.; Frölind, Per-Olov; Gustavsson, Anders; Stenström, Gunnar; Jonsson, Tommy
2014-06-01
In this paper, experimental results for UHF wideband SAR imaging of humans on an open field and inside a forest is presented. The results show ability to detect the humans and suggest possible ways to improve the results. In the experiment, single channel wideband SAR mode of the UHF UWB system LORA developed by Swedish Defence Research Agency (FOI). The wideband SAR mode used in the experiment was from 220 to 450 MHz, thus with a fractional bandwidth of 0.68. Three humans walking and one stationary were available in the scene with one of the walking humans in the forest. The signature of the human in the forest appeared on the field, due to azimuth shift from the positive range speed component. One human on the field and the one in the forest had approximately the same speed and walking direction. The signatures in the SAR image were compared as a function of integration time based on focusing using the average relative speed of these given by GPS logs. A signal processing gain was obtained for the human in forest until approximately 15 s and 35 s for the human on the field. This difference is likely explained by uneven terrain and trees in the way, causing a non-straight walking path.
Wideband aural acoustic absorbance predicts conductive hearing loss in children.
Keefe, Douglas H; Sanford, Chris A; Ellison, John C; Fitzpatrick, Denis F; Gorga, Michael P
2012-12-01
This study tested the hypothesis that wideband aural absorbance predicts conductive hearing loss (CHL) in children medically classified as having otitis media with effusion. Absorbance was measured in the ear canal over frequencies from 0.25 to 8 kHz at ambient pressure or as a swept tympanogram. CHL was defined using criterion air-bone gaps of 20, 25, and 30 dB at octaves from 0.25 to 4 kHz. A likelihood-ratio predictor of CHL was constructed across frequency for ambient absorbance, and across frequency and pressure for absorbance tympanometry. Performance was evaluated at individual frequencies and for any frequency at which a CHL was present. Absorbance and conventional 0.226-kHz tympanograms were measured in children of age three to eight years with CHL and with normal hearing. Absorbance was smaller at frequencies above 0.7 kHz in the CHL group than the control group. Based on the area under the receiver operating characteristic curve, wideband absorbance in ambient and tympanometric tests were significantly better predictors of CHL than tympanometric width, the best 0.226-kHz predictor. Accuracies of ambient and tympanometric wideband absorbance did not differ. Absorbance accurately predicted CHL in children and was more accurate than conventional 0.226-kHz tympanometry.
Age effects in the human middle ear: Wideband acoustical measures
Feeney, M. Patrick; Sanford, Chris A.
2004-12-01
Studies that have examined age effects in the human middle ear using either admittance measures at 220 or 660 Hz or multifrequency tympanometry from 200 to 2000 Hz have had conflicting results. Several studies have suggested an increase in admittance with age, while several others have suggested a decrease in admittance with age. A third group of studies found no significant age effect. This study examined 226 Hz tympanometry and wideband energy reflectance and impedance at ambient pressure in a group of 40 young adults and a group of 30 adults with age >=60 years. The groups did not differ in admittance measures of the middle ear at 226 Hz. However, significant age effects were found in wideband energy reflectance and impedance. In particular, in older adults there was a comparative decrease in reflectance from 800 to 2000 Hz but an increase near 4000 Hz. The results suggest a decrease in middle-ear stiffness with age. The findings of this study hold relevance for understanding the aging process in the auditory system, for the establishment of normative data for wideband energy reflectance, for the possibility of a conductive component to presbycusis, and for the interpretation of otoacoustic emission measurements. .
Enhancing Scalability of Sparse Direct Methods
International Nuclear Information System (INIS)
Li, Xiaoye S.; Demmel, James; Grigori, Laura; Gu, Ming; Xia, Jianlin; Jardin, Steve; Sovinec, Carl; Lee, Lie-Quan
2007-01-01
TOPS is providing high-performance, scalable sparse direct solvers, which have had significant impacts on the SciDAC applications, including fusion simulation (CEMM), accelerator modeling (COMPASS), as well as many other mission-critical applications in DOE and elsewhere. Our recent developments have been focusing on new techniques to overcome scalability bottleneck of direct methods, in both time and memory. These include parallelizing symbolic analysis phase and developing linear-complexity sparse factorization methods. The new techniques will make sparse direct methods more widely usable in large 3D simulations on highly-parallel petascale computers
Regression with Sparse Approximations of Data
DEFF Research Database (Denmark)
Noorzad, Pardis; Sturm, Bob L.
2012-01-01
We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...
Sparse adaptive filters for echo cancellation
Paleologu, Constantin
2011-01-01
Adaptive filters with a large number of coefficients are usually involved in both network and acoustic echo cancellation. Consequently, it is important to improve the convergence rate and tracking of the conventional algorithms used for these applications. This can be achieved by exploiting the sparseness character of the echo paths. Identification of sparse impulse responses was addressed mainly in the last decade with the development of the so-called ``proportionate''-type algorithms. The goal of this book is to present the most important sparse adaptive filters developed for echo cancellati
Technique detection software for Sparse Matrices
Directory of Open Access Journals (Sweden)
KHAN Muhammad Taimoor
2009-12-01
Full Text Available Sparse storage formats are techniques for storing and processing the sparse matrix data efficiently. The performance of these storage formats depend upon the distribution of non-zeros, within the matrix in different dimensions. In order to have better results we need a technique that suits best the organization of data in a particular matrix. So the decision of selecting a better technique is the main step towards improving the system's results otherwise the efficiency can be decreased. The purpose of this research is to help identify the best storage format in case of reduced storage size and high processing efficiency for a sparse matrix.
Massive Asynchronous Parallelization of Sparse Matrix Factorizations
Energy Technology Data Exchange (ETDEWEB)
Chow, Edmond [Georgia Inst. of Technology, Atlanta, GA (United States)
2018-01-08
Solving sparse problems is at the core of many DOE computational science applications. We focus on the challenge of developing sparse algorithms that can fully exploit the parallelism in extreme-scale computing systems, in particular systems with massive numbers of cores per node. Our approach is to express a sparse matrix factorization as a large number of bilinear constraint equations, and then solving these equations via an asynchronous iterative method. The unknowns in these equations are the matrix entries of the factorization that is desired.
Ultra-Wideband Transceiver Design and Optimization
Mehra, Ashutosh
The technology landscape has quickly changed over the last few years. Developments in personal area networks, IC technology, DSP processing and bio-medical devices have enabled the integration of short range communication into low cost personal health care solutions. Newer technologies and solutions are being developed to cater to the personal operating space(POS) and body area networks(BAN). Health care is driving towards using multiple sensor and therapeutic nodes inside the POS. Technology has enabled remote patient care where the patient has low cost on-body wearables that allow the patient/physician to access vital signs without the patient physically visiting the clinic. Big semiconductor giants want to move into the wearable health monitor space. Along with the developments in fitness based health wearables, there has been a lot of interest towards developing BAN devices catering to the 'mission-critical' wearables and implants. Hearing aids, EKG monitors, neurostimulators are some examples. This work explores the use of the 802.15 ulta wideband (UWB) standard for designing a radio to operate in the a wireless sensor network in the BAN. The specific application targeted is a hearing aid. However, the design in this work is capable of working in a low power low range application with the ability to have multiple data rates ranging from a few kHz to 10's of MHz. The first radio designed by Marconi using spark-gap transmitters was an impulse radio (IR). The IR UWB technology boasts of low power, low cost, high data rates, multiple channels, simultaneous networking, the ability to carry information through obstacles that more limited bandwidths cannot, and also potentially lower complexity hardware design. The inherent timing accuracy associated with the technology gives UWB transmissions immunity to multipath fading and are hence make them more suitable for a cluttered indoor environment. The key difference with the traditional narrowband transceiver is that
Hickman, Ian
2013-01-01
Analog Circuits Cookbook presents articles about advanced circuit techniques, components and concepts, useful IC for analog signal processing in the audio range, direct digital synthesis, and ingenious video op-amp. The book also includes articles about amplitude measurements on RF signals, linear optical imager, power supplies and devices, and RF circuits and techniques. Professionals and students of electrical engineering will find the book informative and useful.
Zamora, Paul O [Gaithersburg, MD; Pena, Louis A [Poquott, NY; Lin, Xinhua [Plainview, NY; Takahashi, Kazuyuki [Germantown, MD
2012-07-24
The present invention provides a fibroblast growth factor heparin-binding analog of the formula: ##STR00001## where R.sub.1, R.sub.2, R.sub.3, R.sub.4, R.sub.5, X, Y and Z are as defined, pharmaceutical compositions, coating compositions and medical devices including the fibroblast growth factor heparin-binding analog of the foregoing formula, and methods and uses thereof.
A compact wideband precision impedance measurement system based on digital auto-balancing bridge
International Nuclear Information System (INIS)
Hu, Binxin; Wang, Jinyu; Song, Guangdong; Zhang, Faxiang
2016-01-01
The ac impedance spectroscopy measurements are predominantly taken by using impedance analyzers based on analog auto-balancing bridge. However, those bench-top analyzers are generally complicated, bulky and expensive, thus limiting their usage in industrial field applications. This paper presents the development of a compact wideband precision measurement system based on digital auto-balancing bridge. The methods of digital auto-balancing bridge and digital lock-in amplifier are analyzed theoretically. The overall design and several key sections including null detector, direct digital synthesizer-based sampling clock, and digital control unit are introduced in detail. The results show that the system achieves a basic measurement accuracy of 0.05% with a frequency range of 20 Hz–2 MHz. The advantages of versatile measurement capacity, fast measurement speed, small size and low cost make it quite suitable for industrial field applications. It is demonstrated that this system is practical and effective by applying in determining the impedance-temperature characteristic of a motor starter PTC thermistor. (paper)
Electrical Circuits and Water Analogies
Smith, Frederick A.; Wilson, Jerry D.
1974-01-01
Briefly describes water analogies for electrical circuits and presents plans for the construction of apparatus to demonstrate these analogies. Demonstrations include series circuits, parallel circuits, and capacitors. (GS)
Structure-based bayesian sparse reconstruction
Quadeer, Ahmed Abdul; Al-Naffouri, Tareq Y.
2012-01-01
Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical
Biclustering via Sparse Singular Value Decomposition
Lee, Mihee
2010-02-16
Sparse singular value decomposition (SSVD) is proposed as a new exploratory analysis tool for biclustering or identifying interpretable row-column associations within high-dimensional data matrices. SSVD seeks a low-rank, checkerboard structured matrix approximation to data matrices. The desired checkerboard structure is achieved by forcing both the left- and right-singular vectors to be sparse, that is, having many zero entries. By interpreting singular vectors as regression coefficient vectors for certain linear regressions, sparsity-inducing regularization penalties are imposed to the least squares regression to produce sparse singular vectors. An efficient iterative algorithm is proposed for computing the sparse singular vectors, along with some discussion of penalty parameter selection. A lung cancer microarray dataset and a food nutrition dataset are used to illustrate SSVD as a biclustering method. SSVD is also compared with some existing biclustering methods using simulated datasets. © 2010, The International Biometric Society.
Tunable Sparse Network Coding for Multicast Networks
DEFF Research Database (Denmark)
Feizi, Soheil; Roetter, Daniel Enrique Lucani; Sørensen, Chres Wiant
2014-01-01
This paper shows the potential and key enabling mechanisms for tunable sparse network coding, a scheme in which the density of network coded packets varies during a transmission session. At the beginning of a transmission session, sparsely coded packets are transmitted, which benefits decoding...... complexity. At the end of a transmission, when receivers have accumulated degrees of freedom, coding density is increased. We propose a family of tunable sparse network codes (TSNCs) for multicast erasure networks with a controllable trade-off between completion time performance to decoding complexity...... a mechanism to perform efficient Gaussian elimination over sparse matrices going beyond belief propagation but maintaining low decoding complexity. Supporting simulation results are provided showing the trade-off between decoding complexity and completion time....
SPARSE ELECTROMAGNETIC IMAGING USING NONLINEAR LANDWEBER ITERATIONS
Desmal, Abdulla; Bagci, Hakan
2015-01-01
minimization problem is solved using nonlinear Landweber iterations, where at each iteration a thresholding function is applied to enforce the sparseness-promoting L0/L1-norm constraint. The thresholded nonlinear Landweber iterations are applied to several two
Learning sparse generative models of audiovisual signals
Monaci, Gianluca; Sommer, Friedrich T.; Vandergheynst, Pierre
2008-01-01
This paper presents a novel framework to learn sparse represen- tations for audiovisual signals. An audiovisual signal is modeled as a sparse sum of audiovisual kernels. The kernels are bimodal functions made of synchronous audio and video components that can be positioned independently and arbitrarily in space and time. We design an algorithm capable of learning sets of such audiovi- sual, synchronous, shift-invariant functions by alternatingly solving a coding and a learning pr...
Hyperspectral Unmixing with Robust Collaborative Sparse Regression
Directory of Open Access Journals (Sweden)
Chang Li
2016-07-01
Full Text Available Recently, sparse unmixing (SU of hyperspectral data has received particular attention for analyzing remote sensing images. However, most SU methods are based on the commonly admitted linear mixing model (LMM, which ignores the possible nonlinear effects (i.e., nonlinearity. In this paper, we propose a new method named robust collaborative sparse regression (RCSR based on the robust LMM (rLMM for hyperspectral unmixing. The rLMM takes the nonlinearity into consideration, and the nonlinearity is merely treated as outlier, which has the underlying sparse property. The RCSR simultaneously takes the collaborative sparse property of the abundance and sparsely distributed additive property of the outlier into consideration, which can be formed as a robust joint sparse regression problem. The inexact augmented Lagrangian method (IALM is used to optimize the proposed RCSR. The qualitative and quantitative experiments on synthetic datasets and real hyperspectral images demonstrate that the proposed RCSR is efficient for solving the hyperspectral SU problem compared with the other four state-of-the-art algorithms.
Sana, Furrukh
2016-11-01
Sparse signals are abundant among both natural and man-made signals. Sparsity implies that the signal essentially resides in a small dimensional subspace. The sparsity of the signal can be exploited to improve its recovery from limited and noisy observations. Traditional estimation algorithms generally lack the ability to take advantage of signal sparsity. This dissertation considers several problems in the areas of biomedical engineering and geosciences with the aim of enhancing the recovery of information by exploiting the underlying sparsity in the problem. The objective is to overcome the fundamental bottlenecks, both in terms of estimation accuracies and required computational resources. In the first part of dissertation, we present a high precision technique for the monitoring of human respiratory movements by exploiting the sparsity of wireless ultra-wideband signals. The proposed technique provides a novel methodology of overcoming the Nyquist sampling constraint and enables robust performance in the presence of noise and interferences. We also present a comprehensive framework for the important problem of extracting the fetal electrocardiogram (ECG) signals from abdominal ECG recordings of pregnant women. The multiple measurement vectors approach utilized for this purpose provides an efficient mechanism of exploiting the common structure of ECG signals, when represented in sparse transform domains, and allows leveraging information from multiple ECG electrodes under a joint estimation formulation. In the second part of dissertation, we adopt sparse signal processing principles for improved information recovery in large-scale subsurface reservoir characterization problems. We propose multiple new algorithms for sparse representation of the subsurface geological structures, incorporation of useful prior information in the estimation process, and for reducing computational complexities of the problem. The techniques presented here enable significantly
47 CFR 15.250 - Operation of wideband systems within the band 5925-7250 MHz.
2010-10-01
... of wideband systems within the band 5925-7250 MHz. (a) The −10 dB bandwidth of a device operating... 47 Telecommunication 1 2010-10-01 2010-10-01 false Operation of wideband systems within the band... variations in temperature and supply voltage. (b) The −10 dB bandwidth of the fundamental emission shall be...
GaAs Wideband Low Noise Amplifier Design for Breast Cancer Detection System
DEFF Research Database (Denmark)
Yan, Lei; Krozer, Viktor; Delcourt, Sebastien
2009-01-01
Modern wideband systems require low-noise receivers with bandwidth approaching 10 GHz. This paper presents ultra-wideband stable low-noise amplifier MMIC with cascode and source follower buffer configuration using GaAs technology. Source degeneration, gate and shunt peaking inductors are used...
Sun, Xiao-Ming
2016-01-01
Purpose: The purpose of this study was to present normative data of tympanometric measurements of wideband acoustic immittance and to characterize wideband tympanograms. Method: Data were collected in 84 young adults with strictly defined normal hearing and middle ear status. Energy absorbance (EA) was measured using clicks for 1/12-octave…
Mutual Coupling Reduction for UWB MIMO Antennas with a Wideband Neutralization Line
DEFF Research Database (Denmark)
Zhang, Shuai; Pedersen, Gert F.
2016-01-01
A wideband neutralization line is proposed to reduce the mutual coupling of a compact ultrawideband (UWB) MIMO antenna. With the introduced decoupling method, the designed UWB MIMO antenna covers the band of 3.1-5 GHz with an isolation of higher than 22 dB. The proposed wideband neutralization line...
Biomedical sensor design using analog compressed sensing
Balouchestani, Mohammadreza; Krishnan, Sridhar
2015-05-01
The main drawback of current healthcare systems is the location-specific nature of the system due to the use of fixed/wired biomedical sensors. Since biomedical sensors are usually driven by a battery, power consumption is the most important factor determining the life of a biomedical sensor. They are also restricted by size, cost, and transmission capacity. Therefore, it is important to reduce the load of sampling by merging the sampling and compression steps to reduce the storage usage, transmission times, and power consumption in order to expand the current healthcare systems to Wireless Healthcare Systems (WHSs). In this work, we present an implementation of a low-power biomedical sensor using analog Compressed Sensing (CS) framework for sparse biomedical signals that addresses both the energy and telemetry bandwidth constraints of wearable and wireless Body-Area Networks (BANs). This architecture enables continuous data acquisition and compression of biomedical signals that are suitable for a variety of diagnostic and treatment purposes. At the transmitter side, an analog-CS framework is applied at the sensing step before Analog to Digital Converter (ADC) in order to generate the compressed version of the input analog bio-signal. At the receiver side, a reconstruction algorithm based on Restricted Isometry Property (RIP) condition is applied in order to reconstruct the original bio-signals form the compressed bio-signals with high probability and enough accuracy. We examine the proposed algorithm with healthy and neuropathy surface Electromyography (sEMG) signals. The proposed algorithm achieves a good level for Average Recognition Rate (ARR) at 93% and reconstruction accuracy at 98.9%. In addition, The proposed architecture reduces total computation time from 32 to 11.5 seconds at sampling-rate=29 % of Nyquist rate, Percentage Residual Difference (PRD)=26 %, Root Mean Squared Error (RMSE)=3 %.
Allen, Phillip E
1987-01-01
This text presents the principles and techniques for designing analog circuits to be implemented in a CMOS technology. The level is appropriate for seniors and graduate students familiar with basic electronics, including biasing, modeling, circuit analysis, and some familiarity with frequency response. Students learn the methodology of analog integrated circuit design through a hierarchically-oriented approach to the subject that provides thorough background and practical guidance for designing CMOS analog circuits, including modeling, simulation, and testing. The authors' vast industrial experience and knowledge is reflected in the circuits, techniques, and principles presented. They even identify the many common pitfalls that lie in the path of the beginning designer--expert advice from veteran designers. The text mixes the academic and practical viewpoints in a treatment that is neither superficial nor overly detailed, providing the perfect balance.
Analogical Reasoning in Geometry Education
Magdas, Ioana
2015-01-01
The analogical reasoning isn't used only in mathematics but also in everyday life. In this article we approach the analogical reasoning in Geometry Education. The novelty of this article is a classification of geometrical analogies by reasoning type and their exemplification. Our classification includes: analogies for understanding and setting a…
Digital and analog communication systems
Shanmugam, K. S.
1979-01-01
The book presents an introductory treatment of digital and analog communication systems with emphasis on digital systems. Attention is given to the following topics: systems and signal analysis, random signal theory, information and channel capacity, baseband data transmission, analog signal transmission, noise in analog communication systems, digital carrier modulation schemes, error control coding, and the digital transmission of analog signals.
Analogs for transuranic elements
International Nuclear Information System (INIS)
Weimer, W.C.; Laul, J.C.; Kutt, J.C.
1981-01-01
A combined theoretical and experimental approach is being used to estimate the long-term environmental and biogeochemical behaviors of selected transuranic elements. The objective of this research is to estimate the effect that long-term (hundreds of years) environmental weathering has on the behavior of the transuranic elements americium and curium. This is achieved by investigating the actual behavior of naturally occurring rare earth elements, especially neodymium, that serve as transuranic analogs. Determination of the analog element behavior provides data that can be used to estimate the ultimate availability to man of transuranic materials released into the environment
When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores
Wang, Jim Jing-Yan
2017-06-28
Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been considered separately, assuming that data coding and ranking are two independent and irrelevant problems. However, is there any internal relationship between sparse coding and ranking score learning? If yes, how to explore and make use of this internal relationship? In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm. To explore the local distribution in the sparse code space, and also to bridge coding and ranking problems, we assume that in the neighborhood of each data point, the ranking scores can be approximated from the corresponding sparse codes by a local linear function. By considering the local approximation error of ranking scores, the reconstruction error and sparsity of sparse coding, and the query information provided by the user, we construct a unified objective function for learning of sparse codes, the dictionary and ranking scores. We further develop an iterative algorithm to solve this optimization problem.
Sparse Learning with Stochastic Composite Optimization.
Zhang, Weizhong; Zhang, Lijun; Jin, Zhongming; Jin, Rong; Cai, Deng; Li, Xuelong; Liang, Ronghua; He, Xiaofei
2017-06-01
In this paper, we study Stochastic Composite Optimization (SCO) for sparse learning that aims to learn a sparse solution from a composite function. Most of the recent SCO algorithms have already reached the optimal expected convergence rate O(1/λT), but they often fail to deliver sparse solutions at the end either due to the limited sparsity regularization during stochastic optimization (SO) or due to the limitation in online-to-batch conversion. Even when the objective function is strongly convex, their high probability bounds can only attain O(√{log(1/δ)/T}) with δ is the failure probability, which is much worse than the expected convergence rate. To address these limitations, we propose a simple yet effective two-phase Stochastic Composite Optimization scheme by adding a novel powerful sparse online-to-batch conversion to the general Stochastic Optimization algorithms. We further develop three concrete algorithms, OptimalSL, LastSL and AverageSL, directly under our scheme to prove the effectiveness of the proposed scheme. Both the theoretical analysis and the experiment results show that our methods can really outperform the existing methods at the ability of sparse learning and at the meantime we can improve the high probability bound to approximately O(log(log(T)/δ)/λT).
In-place sparse suffix sorting
DEFF Research Database (Denmark)
Prezza, Nicola
2018-01-01
information regarding the lexicographical order of a size-b subset of all n text suffixes is often needed. Such information can be stored space-efficiently (in b words) in the sparse suffix array (SSA). The SSA and its relative sparse LCP array (SLCP) can be used as a space-efficient substitute of the sparse...... suffix tree. Very recently, Gawrychowski and Kociumaka [11] showed that the sparse suffix tree (and therefore SSA and SLCP) can be built in asymptotically optimal O(b) space with a Monte Carlo algorithm running in O(n) time. The main reason for using the SSA and SLCP arrays in place of the sparse suffix...... tree is, however, their reduced space of b words each. This leads naturally to the quest for in-place algorithms building these arrays. Franceschini and Muthukrishnan [8] showed that the full suffix array can be built in-place and in optimal running time. On the other hand, finding sub-quadratic in...
Ultra-wideband WDM VCSEL arrays by lateral heterogeneous integration
Geske, Jon
Advancements in heterogeneous integration are a driving factor in the development of evermore sophisticated and functional electronic and photonic devices. Such advancements will merge the optical and electronic capabilities of different material systems onto a common integrated device platform. This thesis presents a new lateral heterogeneous integration technology called nonplanar wafer bonding. The technique is capable of integrating multiple dissimilar semiconductor device structures on the surface of a substrate in a single wafer bond step, leaving different integrated device structures adjacent to each other on the wafer surface. Material characterization and numerical simulations confirm that the material quality is not compromised during the process. Nonplanar wafer bonding is used to fabricate ultra-wideband wavelength division multiplexed (WDM) vertical-cavity surface-emitting laser (VCSEL) arrays. The optically-pumped VCSEL arrays span 140 nm from 1470 to 1610 nm, a record wavelength span for devices operating in this wavelength range. The array uses eight wavelength channels to span the 140 nm with all channels separated by precisely 20 nm. All channels in the array operate single mode to at least 65°C with output power uniformity of +/- 1 dB. The ultra-wideband WDM VCSEL arrays are a significant first step toward the development of a single-chip source for optical networks based on coarse WDM (CWDM), a low-cost alternative to traditional dense WDM. The CWDM VCSEL arrays make use of fully-oxidized distributed Bragg reflectors (DBRs) to provide the wideband reflectivity required for optical feedback and lasing across 140 rim. In addition, a novel optically-pumped active region design is presented. It is demonstrated, with an analytical model and experimental results, that the new active-region design significantly improves the carrier uniformity in the quantum wells and results in a 50% lasing threshold reduction and a 20°C improvement in the peak
Monostatic ultra-wideband GPR antenna for through wall detection
Directory of Open Access Journals (Sweden)
Ali Jawad
2017-01-01
Full Text Available The aim of this paper is to present a monostatic arc-shaped ultra-wideband (UWB printed monopole antenna system with 3-16 GHz frequency bandwidth suitable for through-wall detection. Ground penetrating radar (GPR technique is used for detection with the gain of 6.2 dB achieved for the proposed antenna using defected ground structure (DGS method. To serve the purpose, a simulation experiment of through-wall detection model is constructed which consists of a monostatic antenna act as transmitter and receiver, concrete wall and human skin model. The time domain reflection of obtained result is then analysed for target detection.
Wide-band slow-wave systems simulation and applications
Staras, Stanislovas
2012-01-01
The field of electromagnetics has seen considerable advances in recent years, based on the wide applications of numerical methods for investigating electromagnetic fields, microwaves, and other devices. Wide-Band Slow-Wave Systems: Simulation and Applications presents new technical solutions and research results for the analysis, synthesis, and design of slow-wave structures for modern electronic devices with super-wide pass-bands. It makes available, for the first time in English, significant research from the past 20 years that was previously published only in Russian and Lithuanian. The aut
Optically addressed ultra-wideband phased antenna array
Bai, Jian
Demands for high data rate and multifunctional apertures from both civilian and military users have motivated development of ultra-wideband (UWB) electrically steered phased arrays. Meanwhile, the need for large contiguous frequency is pushing operation of radio systems into the millimeter-wave (mm-wave) range. Therefore, modern radio systems require UWB performance from VHF to mm-wave. However, traditional electronic systems suffer many challenges that make achieving these requirements difficult. Several examples includes: voltage controlled oscillators (VCO) cannot provide a tunable range of several octaves, distribution of wideband local oscillator signals undergo high loss and dispersion through RF transmission lines, and antennas have very limited bandwidth or bulky sizes. Recently, RF photonics technology has drawn considerable attention because of its advantages over traditional systems, with the capability of offering extreme power efficiency, information capacity, frequency agility, and spatial beam diversity. A hybrid RF photonic communication system utilizing optical links and an RF transducer at the antenna potentially provides ultra-wideband data transmission, i.e., over 100 GHz. A successful implementation of such an optically addressed phased array requires addressing several key challenges. Photonic generation of an RF source with over a seven-octave bandwidth has been demonstrated in the last few years. However, one challenge which still remains is how to convey phased optical signals to downconversion modules and antennas. Therefore, a feed network with phase sweeping capability and low excessive phase noise needs to be developed. Another key challenge is to develop an ultra-wideband array antenna. Modern frontends require antennas to be compact, planar, and low-profile in addition to possessing broad bandwidth, conforming to stringent space, weight, cost, and power constraints. To address these issues, I will study broadband and miniaturization
Ultra-wideband and 60 GHz communications for biomedical applications
Yuce, Mehmet R
2013-01-01
This book investigates the design of devices, systems, and circuits for medical applications using the two recently established frequency bands: ultra-wideband (3.1-10.6 GHz) and 60 GHz ISM band. These two bands provide the largest bandwidths available for communication technologies and present many attractive opportunities for medical applications. The applications of these bands in healthcare are wireless body area network (WBAN), medical imaging, biomedical sensing, wearable and implantable devices, fast medical device connectivity, video data transmission, and vital signs monitoring. The r
Farr, T. G.; Arcone, S.; Arvidson, R. W.; Baker, V.; Barlow, N. G.; Beaty, D.; Bell, M. S.; Blankenship, D. D.; Bridges, N.; Briggs, G.; Bulmer, M.; Carsey, F.; Clifford, S. M.; Craddock, R. A.; Dickerson, P. W.; Duxbury, N.; Galford, G. L.; Garvin, J.; Grant, J.; Green, J. R.; Gregg, T. K. P.; Guinness, E.; Hansen, V. L.; Hecht, M. H.; Holt, J.; Howard, A.; Keszthelyi, L. P.; Lee, P.; Lanagan, P. D.; Lentz, R. C. F.; Leverington, D. W.; Marinangeli, L.; Moersch, J. E.; Morris-Smith, P. A.; Mouginis-Mark, P.; Olhoeft, G. R.; Ori, G. G.; Paillou, P.; Reilly, J. F., II; Rice, J. W., Jr.; Robinson, C. A.; Sheridan, M.; Snook, K.; Thomson, B. J.; Watson, K.; Williams, K.; Yoshikawa, K.
2002-08-01
It is well recognized that interpretations of Mars must begin with the Earth as a reference. The most successful comparisons have focused on understanding geologic processes on the Earth well enough to extrapolate to Mars' environment. Several facets of terrestrial analog studies have been pursued and are continuing. These studies include field workshops, characterization of terrestrial analog sites, instrument tests, laboratory measurements (including analysis of Martian meteorites), and computer and laboratory modeling. The combination of all these activities allows scientists to constrain the processes operating in specific terrestrial environments and extrapolate how similar processes could affect Mars. The Terrestrial Analogs for Mars Community Panel has considered the following two key questions: (1) How do terrestrial analog studies tie in to the Mars Exploration Payload Assessment Group science questions about life, past climate, and geologic evolution of Mars, and (2) How can future instrumentation be used to address these questions. The panel has considered the issues of data collection, value of field workshops, data archiving, laboratory measurements and modeling, human exploration issues, association with other areas of solar system exploration, and education and public outreach activities.
Reasoning through Instructional Analogies
Kapon, Shulamit; diSessa, Andrea A.
2012-01-01
This article aims to account for students' assessments of the plausibility and applicability of analogical explanations, and individual differences in these assessments, by analyzing properties of students' underlying knowledge systems. We developed a model of explanation and change in explanation focusing on knowledge elements that provide a…
Directory of Open Access Journals (Sweden)
David Botting
2012-03-01
Full Text Available I will show that there is a type of analogical reasoning that instantiates a pattern of reasoning in confirmation theory that is considered at best paradoxical and at worst fatal to the entire syntactical approach to confirmation and explanation. However, I hope to elaborate conditions under which this is a sound (although not necessarily strong method of reasoning.
Analogy, explanation, and proof
Hummel, John E.; Licato, John; Bringsjord, Selmer
2014-01-01
People are habitual explanation generators. At its most mundane, our propensity to explain allows us to infer that we should not drink milk that smells sour; at the other extreme, it allows us to establish facts (e.g., theorems in mathematical logic) whose truth was not even known prior to the existence of the explanation (proof). What do the cognitive operations underlying the inference that the milk is sour have in common with the proof that, say, the square root of two is irrational? Our ability to generate explanations bears striking similarities to our ability to make analogies. Both reflect a capacity to generate inferences and generalizations that go beyond the featural similarities between a novel problem and familiar problems in terms of which the novel problem may be understood. However, a notable difference between analogy-making and explanation-generation is that the former is a process in which a single source situation is used to reason about a single target, whereas the latter often requires the reasoner to integrate multiple sources of knowledge. This seemingly small difference poses a challenge to the task of marshaling our understanding of analogical reasoning to understanding explanation. We describe a model of explanation, derived from a model of analogy, adapted to permit systematic violations of this one-to-one mapping constraint. Simulation results demonstrate that the resulting model can generate explanations for novel explananda and that, like the explanations generated by human reasoners, these explanations vary in their coherence. PMID:25414655
International Nuclear Information System (INIS)
Hofstadter, Doug
2004-01-01
Many new ideas in theoretical physics come from analogies to older ideas in physics. For instance, the abstract notion of 'isospin' (or isotopic spin) originated in the prior concept of 'spin' (quantized angular momentum); likewise, the concept of 'phonon' (quantum of sound, or quantized collective excitation of a crystal) was based on the prior concept of 'photon' (quantum of light, or quantized element of the electromagnetic field). But these two examples, far from being exceptions, in fact represent the bread and butter of inventive thinking in physics. In a nutshell, intraphysics analogy-making -- borrowing by analogy with something already known in another area of physics -- is central to the progress of physics. The aim of this talk is to reveal the pervasiveness -- indeed, the indispensability -- of this kind of semi-irrational, wholly intuitive type of thinking (as opposed to more deductive mathematical inference) in the mental activity known as 'doing physics'. Speculations as to why wild analogical leaps are so crucial to the act of discovery in physics (as opposed to other disciplines) will be offered.
Zak, M.
1998-01-01
Quantum analog computing is based upon similarity between mathematical formalism of quantum mechanics and phenomena to be computed. It exploits a dynamical convergence of several competing phenomena to an attractor which can represent an externum of a function, an image, a solution to a system of ODE, or a stochastic process.
Scalable group level probabilistic sparse factor analysis
DEFF Research Database (Denmark)
Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Riis, Nicolai Andre Brogaard
2017-01-01
Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a scalable group level probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component...... pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling...... shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex...
SPARSE ELECTROMAGNETIC IMAGING USING NONLINEAR LANDWEBER ITERATIONS
Desmal, Abdulla
2015-07-29
A scheme for efficiently solving the nonlinear electromagnetic inverse scattering problem on sparse investigation domains is described. The proposed scheme reconstructs the (complex) dielectric permittivity of an investigation domain from fields measured away from the domain itself. Least-squares data misfit between the computed scattered fields, which are expressed as a nonlinear function of the permittivity, and the measured fields is constrained by the L0/L1-norm of the solution. The resulting minimization problem is solved using nonlinear Landweber iterations, where at each iteration a thresholding function is applied to enforce the sparseness-promoting L0/L1-norm constraint. The thresholded nonlinear Landweber iterations are applied to several two-dimensional problems, where the ``measured\\'\\' fields are synthetically generated or obtained from actual experiments. These numerical experiments demonstrate the accuracy, efficiency, and applicability of the proposed scheme in reconstructing sparse profiles with high permittivity values.
Fast wavelet based sparse approximate inverse preconditioner
Energy Technology Data Exchange (ETDEWEB)
Wan, W.L. [Univ. of California, Los Angeles, CA (United States)
1996-12-31
Incomplete LU factorization is a robust preconditioner for both general and PDE problems but unfortunately not easy to parallelize. Recent study of Huckle and Grote and Chow and Saad showed that sparse approximate inverse could be a potential alternative while readily parallelizable. However, for special class of matrix A that comes from elliptic PDE problems, their preconditioners are not optimal in the sense that independent of mesh size. A reason may be that no good sparse approximate inverse exists for the dense inverse matrix. Our observation is that for this kind of matrices, its inverse entries typically have piecewise smooth changes. We can take advantage of this fact and use wavelet compression techniques to construct a better sparse approximate inverse preconditioner. We shall show numerically that our approach is effective for this kind of matrices.
Sparse regularization for force identification using dictionaries
Qiao, Baijie; Zhang, Xingwu; Wang, Chenxi; Zhang, Hang; Chen, Xuefeng
2016-04-01
The classical function expansion method based on minimizing l2-norm of the response residual employs various basis functions to represent the unknown force. Its difficulty lies in determining the optimum number of basis functions. Considering the sparsity of force in the time domain or in other basis space, we develop a general sparse regularization method based on minimizing l1-norm of the coefficient vector of basis functions. The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process. First, according to the profile of the unknown force, the dictionary composed of basis functions is determined. Second, a sparsity convex optimization model for force identification is constructed. Third, given the transfer function and the operational response, Sparse reconstruction by separable approximation (SpaRSA) is developed to solve the sparse regularization problem of force identification. Finally, experiments including identification of impact and harmonic forces are conducted on a cantilever thin plate structure to illustrate the effectiveness and applicability of SpaRSA. Besides the Dirac dictionary, other three sparse dictionaries including Db6 wavelets, Sym4 wavelets and cubic B-spline functions can also accurately identify both the single and double impact forces from highly noisy responses in a sparse representation frame. The discrete cosine functions can also successfully reconstruct the harmonic forces including the sinusoidal, square and triangular forces. Conversely, the traditional Tikhonov regularization method with the L-curve criterion fails to identify both the impact and harmonic forces in these cases.
Parallel transposition of sparse data structures
DEFF Research Database (Denmark)
Wang, Hao; Liu, Weifeng; Hou, Kaixi
2016-01-01
Many applications in computational sciences and social sciences exploit sparsity and connectivity of acquired data. Even though many parallel sparse primitives such as sparse matrix-vector (SpMV) multiplication have been extensively studied, some other important building blocks, e.g., parallel tr...... transposition in the latest vendor-supplied library on an Intel multicore CPU platform, and the MergeTrans approach achieves on average of 3.4-fold (up to 11.7-fold) speedup on an Intel Xeon Phi many-core processor....
Structure-based bayesian sparse reconstruction
Quadeer, Ahmed Abdul
2012-12-01
Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical information (Gaussian or otherwise) to obtain near optimal estimates. In addition, we make use of the rich structure of the sensing matrix encountered in many signal processing applications to develop a fast sparse recovery algorithm. The computational complexity of the proposed algorithm is very low compared with the widely used convex relaxation methods as well as greedy matching pursuit techniques, especially at high sparsity. © 1991-2012 IEEE.
Binary Sparse Phase Retrieval via Simulated Annealing
Directory of Open Access Journals (Sweden)
Wei Peng
2016-01-01
Full Text Available This paper presents the Simulated Annealing Sparse PhAse Recovery (SASPAR algorithm for reconstructing sparse binary signals from their phaseless magnitudes of the Fourier transform. The greedy strategy version is also proposed for a comparison, which is a parameter-free algorithm. Sufficient numeric simulations indicate that our method is quite effective and suggest the binary model is robust. The SASPAR algorithm seems competitive to the existing methods for its efficiency and high recovery rate even with fewer Fourier measurements.
Analog circuit design designing high performance amplifiers
Feucht, Dennis
2010-01-01
The third volume Designing High Performance Amplifiers applies the concepts from the first two volumes. It is an advanced treatment of amplifier design/analysis emphasizing both wideband and precision amplification.
Ultra-wideband reflective polarization converter based on anisotropic metasurface
Wu, Jia-Liang; Lin, Bao-Qin; Da, Xin-Yu
2016-08-01
In this paper, we propose an ultra-wideband reflective linear cross-polarization converter based on anisotropic metasurface. Its unit cell is composed of a square-shaped resonator with intersectant diagonal and metallic ground sheet separated by dielectric substrate. Simulated results show that the converter can generate resonances at four frequencies under normal incident electromagnetic (EM) wave, leading to the bandwidth expansion of cross-polarization reflection. For verification, the designed polarization converter is fabricated and measured. The measured and simulated results agree well with each other, showing that the fabricated converter can convert x- or y-polarized incident wave into its cross polarized wave in a frequency range from 7.57 GHz to 20.46 GHz with a relative bandwidth of 91.2%, and the polarization conversion efficiency is greater than 90%. The proposed polarization converter has a simple geometry but an ultra wideband compared with the published designs, and hence possesses potential applications in novel polarization-control devices. Project supported by the National Natural Science Foundation of China (Grant Nos. 61471387, 61271250, and 61571460).
Ultra-wideband reflective polarization converter based on anisotropic metasurface
International Nuclear Information System (INIS)
Wu Jia-Liang; Lin Bao-Qin; Da Xin-Yu
2016-01-01
In this paper, we propose an ultra-wideband reflective linear cross-polarization converter based on anisotropic metasurface. Its unit cell is composed of a square-shaped resonator with intersectant diagonal and metallic ground sheet separated by dielectric substrate. Simulated results show that the converter can generate resonances at four frequencies under normal incident electromagnetic (EM) wave, leading to the bandwidth expansion of cross-polarization reflection. For verification, the designed polarization converter is fabricated and measured. The measured and simulated results agree well with each other, showing that the fabricated converter can convert x - or y -polarized incident wave into its cross polarized wave in a frequency range from 7.57 GHz to 20.46 GHz with a relative bandwidth of 91.2%, and the polarization conversion efficiency is greater than 90%. The proposed polarization converter has a simple geometry but an ultra wideband compared with the published designs, and hence possesses potential applications in novel polarization-control devices. (paper)
Terrestrial Spaceflight Analogs: Antarctica
Crucian, Brian
2013-01-01
Alterations in immune cell distribution and function, circadian misalignment, stress and latent viral reactivation appear to persist during Antarctic winterover at Concordia Station. Some of these changes are similar to those observed in Astronauts, either during or immediately following spaceflight. Others are unique to the Concordia analog. Based on some initial immune data and environmental conditions, Concordia winterover may be an appropriate analog for some flight-associated immune system changes and mission stress effects. An ongoing smaller control study at Neumayer III will address the influence of the hypoxic variable. Changes were observed in the peripheral blood leukocyte distribution consistent with immune mobilization, and similar to those observed during spaceflight. Alterations in cytokine production profiles were observed during winterover that are distinct from those observed during spaceflight, but potentially consistent with those observed during persistent hypobaric hypoxia. The reactivation of latent herpesviruses was observed during overwinter/isolation, that is consistently associated with dysregulation in immune function.
Analog storage integrated circuit
Walker, J.T.; Larsen, R.S.; Shapiro, S.L.
1989-03-07
A high speed data storage array is defined utilizing a unique cell design for high speed sampling of a rapidly changing signal. Each cell of the array includes two input gates between the signal input and a storage capacitor. The gates are controlled by a high speed row clock and low speed column clock so that the instantaneous analog value of the signal is only sampled and stored by each cell on coincidence of the two clocks. 6 figs.
Analogy, Explanation, and Proof
Directory of Open Access Journals (Sweden)
John eHummel
2014-11-01
Full Text Available People are habitual explanation generators. At its most mundane, our propensity to explain allows us to infer that we should not drink milk that smells sour; at the other extreme, it allows us to establish facts (e.g., theorems in mathematical logic whose truth was not even known prior to the existence of the explanation (proof. What do the cognitive operations underlying the (inductive inference that the milk is sour have in common with the (deductive proof that, say, the square root of two is irrational? Our ability to generate explanations bears striking similarities to our ability to make analogies. Both reflect a capacity to generate inferences and generalizations that go beyond the featural similarities between a novel problem and familiar problems in terms of which the novel problem may be understood. However, a notable difference between analogy-making and explanation-generation is that the former is a process in which a single source situation is used to reason about a single target, whereas the latter often requires the reasoner to integrate multiple sources of knowledge. This small-seeming difference poses a challenge to the task of marshaling our understanding of analogical reasoning in the service of understanding explanation. We describe a model of explanation, derived from a model of analogy, adapted to permit systematic violations of this one-to-one mapping constraint. Simulation results demonstrate that the resulting model can generate explanations for novel explananda and that, like the explanations generated by human reasoners, these explanations vary in their coherence.
Subspace Based Blind Sparse Channel Estimation
DEFF Research Database (Denmark)
Hayashi, Kazunori; Matsushima, Hiroki; Sakai, Hideaki
2012-01-01
The paper proposes a subspace based blind sparse channel estimation method using 1–2 optimization by replacing the 2–norm minimization in the conventional subspace based method by the 1–norm minimization problem. Numerical results confirm that the proposed method can significantly improve...
Multilevel sparse functional principal component analysis.
Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S
2014-01-29
We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.
Continuous speech recognition with sparse coding
CSIR Research Space (South Africa)
Smit, WJ
2009-04-01
Full Text Available generative model. The spike train is classified by making use of a spike train model and dynamic programming. It is computationally expensive to find a sparse code. We use an iterative subset selection algorithm with quadratic programming for this process...
Multisnapshot Sparse Bayesian Learning for DOA
DEFF Research Database (Denmark)
Gerstoft, Peter; Mecklenbrauker, Christoph F.; Xenaki, Angeliki
2016-01-01
The directions of arrival (DOA) of plane waves are estimated from multisnapshot sensor array data using sparse Bayesian learning (SBL). The prior for the source amplitudes is assumed independent zero-mean complex Gaussian distributed with hyperparameters, the unknown variances (i.e., the source...
Better Size Estimation for Sparse Matrix Products
DEFF Research Database (Denmark)
Amossen, Rasmus Resen; Campagna, Andrea; Pagh, Rasmus
2010-01-01
We consider the problem of doing fast and reliable estimation of the number of non-zero entries in a sparse Boolean matrix product. Let n denote the total number of non-zero entries in the input matrices. We show how to compute a 1 ± ε approximation (with small probability of error) in expected t...
Rotational image deblurring with sparse matrices
DEFF Research Database (Denmark)
Hansen, Per Christian; Nagy, James G.; Tigkos, Konstantinos
2014-01-01
We describe iterative deblurring algorithms that can handle blur caused by a rotation along an arbitrary axis (including the common case of pure rotation). Our algorithms use a sparse-matrix representation of the blurring operation, which allows us to easily handle several different boundary...
Feature based omnidirectional sparse visual path following
Goedemé, Toon; Tuytelaars, Tinne; Van Gool, Luc; Vanacker, Gerolf; Nuttin, Marnix
2005-01-01
Goedemé T., Tuytelaars T., Van Gool L., Vanacker G., Nuttin M., ''Feature based omnidirectional sparse visual path following'', Proceedings IEEE/RSJ international conference on intelligent robots and systems - IROS2005, pp. 1003-1008, August 2-6, 2005, Edmonton, Alberta, Canada.
Comparison of sparse point distribution models
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Vester-Christensen, Martin; Larsen, Rasmus
2010-01-01
This paper compares several methods for obtaining sparse and compact point distribution models suited for data sets containing many variables. These are evaluated on a database consisting of 3D surfaces of a section of the pelvic bone obtained from CT scans of 33 porcine carcasses. The superior m...
A sparse-grid isogeometric solver
Beck, Joakim
2018-02-28
Isogeometric Analysis (IGA) typically adopts tensor-product splines and NURBS as a basis for the approximation of the solution of PDEs. In this work, we investigate to which extent IGA solvers can benefit from the so-called sparse-grids construction in its combination technique form, which was first introduced in the early 90’s in the context of the approximation of high-dimensional PDEs.The tests that we report show that, in accordance to the literature, a sparse-grid construction can indeed be useful if the solution of the PDE at hand is sufficiently smooth. Sparse grids can also be useful in the case of non-smooth solutions when some a-priori knowledge on the location of the singularities of the solution can be exploited to devise suitable non-equispaced meshes. Finally, we remark that sparse grids can be seen as a simple way to parallelize pre-existing serial IGA solvers in a straightforward fashion, which can be beneficial in many practical situations.
A sparse version of IGA solvers
Beck, Joakim
2017-07-30
Isogeometric Analysis (IGA) typically adopts tensor-product splines and NURBS as a basis for the approximation of the solution of PDEs. In this work, we investigate to which extent IGA solvers can benefit from the so-called sparse-grids construction in its combination technique form, which was first introduced in the early 90s in the context of the approximation of high-dimensional PDEs. The tests that we report show that, in accordance to the literature, a sparse grids construction can indeed be useful if the solution of the PDE at hand is sufficiently smooth. Sparse grids can also be useful in the case of non-smooth solutions when some a-priori knowledge on the location of the singularities of the solution can be exploited to devise suitable non-equispaced meshes. Finally, we remark that sparse grids can be seen as a simple way to parallelize pre-existing serial IGA solvers in a straightforward fashion, which can be beneficial in many practical situations.
A sparse-grid isogeometric solver
Beck, Joakim; Sangalli, Giancarlo; Tamellini, Lorenzo
2018-01-01
Isogeometric Analysis (IGA) typically adopts tensor-product splines and NURBS as a basis for the approximation of the solution of PDEs. In this work, we investigate to which extent IGA solvers can benefit from the so-called sparse-grids construction in its combination technique form, which was first introduced in the early 90’s in the context of the approximation of high-dimensional PDEs.The tests that we report show that, in accordance to the literature, a sparse-grid construction can indeed be useful if the solution of the PDE at hand is sufficiently smooth. Sparse grids can also be useful in the case of non-smooth solutions when some a-priori knowledge on the location of the singularities of the solution can be exploited to devise suitable non-equispaced meshes. Finally, we remark that sparse grids can be seen as a simple way to parallelize pre-existing serial IGA solvers in a straightforward fashion, which can be beneficial in many practical situations.
A sparse version of IGA solvers
Beck, Joakim; Sangalli, Giancarlo; Tamellini, Lorenzo
2017-01-01
Isogeometric Analysis (IGA) typically adopts tensor-product splines and NURBS as a basis for the approximation of the solution of PDEs. In this work, we investigate to which extent IGA solvers can benefit from the so-called sparse-grids construction in its combination technique form, which was first introduced in the early 90s in the context of the approximation of high-dimensional PDEs. The tests that we report show that, in accordance to the literature, a sparse grids construction can indeed be useful if the solution of the PDE at hand is sufficiently smooth. Sparse grids can also be useful in the case of non-smooth solutions when some a-priori knowledge on the location of the singularities of the solution can be exploited to devise suitable non-equispaced meshes. Finally, we remark that sparse grids can be seen as a simple way to parallelize pre-existing serial IGA solvers in a straightforward fashion, which can be beneficial in many practical situations.
New methods for sampling sparse populations
Anna Ringvall
2007-01-01
To improve surveys of sparse objects, methods that use auxiliary information have been suggested. Guided transect sampling uses prior information, e.g., from aerial photographs, for the layout of survey strips. Instead of being laid out straight, the strips will wind between potentially more interesting areas. 3P sampling (probability proportional to prediction) uses...
Component Processes in Analogical Reasoning
Sternberg, Robert J.
1977-01-01
Describes alternative theoretical positions regarding (a) the component information processes used in analogical reasoning and (b) strategies for combining these processes. Also presents results from three experiments on analogical reasoning. (Author/RK)
Inductive, Analogical, and Communicative Generalization
Directory of Open Access Journals (Sweden)
Adri Smaling
2003-03-01
Full Text Available Three forms of inductive generalization - statistical generalization, variation-based generalization and theory-carried generalization - are insufficient concerning case-to-case generalization, which is a form of analogical generalization. The quality of case-to-case generalization needs to be reinforced by setting up explicit analogical argumentation. To evaluate analogical argumentation six criteria are discussed. Good analogical reasoning is an indispensable support to forms of communicative generalization - receptive and responsive (participative generalization — as well as exemplary generalization.
Realization of Miniaturized Multi-/Wideband Microwave Front-Ends
Al Shamaileh, Khair A.
The ever-growing demand toward designing microwave front-end components with enhanced access to the radio spectrum (e.g., multi-/wideband functionality) and improved physical features (e.g., miniaturized circuitry, ease and cost of fabrication) is becoming more paramount than ever before. This dissertation proposes new design methodologies, simulations, and experimental validations of passive front-ends (i.e., antennas, couplers, dividers) at microwave frequencies. The presented design concepts optimize both electrical and physical characteristics without degrading the intended performance. The developed designs are essential to the upcoming wireless technologies. The first proposed component is a compact ultra-wideband (UWB) Wilkinson power divider (WPD). The design procedure is accomplished by replacing the uniform transmission lines in each arm of the conventional single-frequency divider with impedance-varying profiles governed by a truncated Fourier series. While such non-uniform transmission lines (NTLs) are obtained through the even-mode analysis, three isolation resistors are optimized in the odd-mode circuit to achieve proper isolation and output ports matching over the frequency range of interest. The proposed design methodology is systematic, and results in single-layered and compact structures. For verification purposes, an equal split WPD is designed, simulated, and measured. The obtained results show that the input and output ports matching as well as the isolation between the output ports are below --10 dB; whereas the transmission parameters vary between --3.2 dB and --5 dB across the 3.1--10.6 GHz band. The designed divider is expected to find applications in UWB antenna diversity, multiple-input-multiple-output (MIMO) schemes, and antenna arrays feeding networks. The second proposed component is a wideband multi-way Bagley power divider (BPD). Wideband functionality is achieved by replacing the single-frequency matching uniform microstrip lines in
Analogical Reasoning and Computer Programming.
Clement, Catherine A.; And Others
1986-01-01
A study of correlations between analogical reasoning and Logo programming mastery among female high school students related the results of pretests of analogical reasoning to posttests of programming mastery. A significant correlation was found between analogical reasoning and the ability to write subprocedures for use in several different…
Fast Sparse Coding for Range Data Denoising with Sparse Ridges Constraint.
Gao, Zhi; Lao, Mingjie; Sang, Yongsheng; Wen, Fei; Ramesh, Bharath; Zhai, Ruifang
2018-05-06
Light detection and ranging (LiDAR) sensors have been widely deployed on intelligent systems such as unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) to perform localization, obstacle detection, and navigation tasks. Thus, research into range data processing with competitive performance in terms of both accuracy and efficiency has attracted increasing attention. Sparse coding has revolutionized signal processing and led to state-of-the-art performance in a variety of applications. However, dictionary learning, which plays the central role in sparse coding techniques, is computationally demanding, resulting in its limited applicability in real-time systems. In this study, we propose sparse coding algorithms with a fixed pre-learned ridge dictionary to realize range data denoising via leveraging the regularity of laser range measurements in man-made environments. Experiments on both synthesized data and real data demonstrate that our method obtains accuracy comparable to that of sophisticated sparse coding methods, but with much higher computational efficiency.
Analogical scaffolding: Making meaning in physics through representation and analogy
Podolefsky, Noah Solomon
This work reviews the literature on analogy, introduces a new model of analogy, and presents a series of experiments that test and confirm the utility of this model to describe and predict student learning in physics with analogy. Pilot studies demonstrate that representations (e.g., diagrams) can play a key role in students' use of analogy. A new model of analogy, Analogical Scaffolding, is developed to explain these initial empirical results. This model will be described in detail, and then applied to describe and predict the outcomes of further experiments. Two large-scale (N>100) studies will demonstrate that: (1) students taught with analogies, according to the Analogical Scaffolding model, outperform students taught without analogies on pre-post assessments focused on electromagnetic waves; (2) the representational forms used to teach with analogy can play a significant role in student learning, with students in one treatment group outperforming students in other treatment groups by factors of two or three. It will be demonstrated that Analogical Scaffolding can be used to predict these results, as well as finer-grained results such as the types of distracters students choose in different treatment groups, and to describe and analyze student reasoning in interviews. Abstraction in physics is reconsidered using Analogical Scaffolding. An operational definition of abstraction is developed within the Analogical Scaffolding framework and employed to explain (a) why physicists consider some ideas more abstract than others in physics, and (b) how students conceptions of these ideas can be modeled. This new approach to abstraction suggests novel approaches to curriculum design in physics using Analogical Scaffolding.
[Auditory training with wide-band white noise: effects on the recruitment (III)].
Domínguez Ugidos, L J; Rodríguez Morejón, C; Vallés Varela, H; Iparraguirre Bolinaga, V; Knaster del Olmo, J
2001-05-01
The auditory training with wide-band white noise is a methodology for the qualitative recovery of the hearing loss in people suffering from sensorineural hearing loss. It is based on the application of a wide-band white modified noise. In a prospective study, we have assessed the modifications of the recruitment coefficient in a sample of 48 patients who have followed a program of 15 auditory training with wide-band white noise sessions. The average improvement of the recruitment coefficient expressed in percentage is a 7.7498%, which comes up to 23.5249% in the case of a binaural recruitment coefficient. From our results, it can be deduced that the auditory training with wide-band white noise reduces the recruitment. That is to say, the decrease of the recruitment in high intensities both binaurally and in all ears.
Sui, Sai; Ma, Hua; Lv, Yueguang; Wang, Jiafu; Li, Zhiqiang; Zhang, Jieqiu; Xu, Zhuo; Qu, Shaobo
2018-01-22
Arbitrary control of electromagnetic waves remains a significant challenge although it promises many important applications. Here, we proposed a fast optimization method of designing a wideband metasurface without using the Pancharatnam-Berry (PB) phase, of which the elements are non-absorptive and capable of predicting the wideband and smooth phase-shift. In our design method, the metasurface is composed of low-Q-factor resonant elements without using the PB phase, and is optimized by the genetic algorithm and nonlinear fitting method, having the advantages that the far field scattering patterns can be quickly synthesized by the hybrid array patterns. To validate the design method, a wideband low radar cross section metasurface is demonstrated, showing good feasibility and performance of wideband RCS reduction. This work reveals an opportunity arising from a metasurface in effective manipulation of microwave and flexible fast optimal design method.
Bonds, Quenton; Racette, Paul; Durham, Tim (Principal Investigator)
2016-01-01
Presented are the prior accomplishments, current status and path forward for GSFC's Wideband Instrument for Snow Measurement (WISM). This work is a high level overview of the project, presented via Webinar to the IEEE young professionals.
Ultra-Wideband Transceiver for Integrated Communication and Relative Navigation, Phase I
National Aeronautics and Space Administration — The goal of this project is to develop an innovative way of using Time Modulated Ultra Wideband (TM-UWB) transceivers (radios) to provide high performance integrated...
The design of wideband metamaterial absorber at E band based on defect
Wang, L. S.; Xia, D. Y.; Ding, X. Y.; Wang, Y.
2018-01-01
A kind of wideband metamaterial absorber at E band is designed in this paper; it is composed of round metal cells with defect, dielectric substrate and metal film. The electromagnetic parameters of unit cell are calculated by using the finite element method. The results show that the wideband metamaterial absorber presents nearly perfect absorption above 90% with absorption ranging from 65.38GHz to 67.86GHz; the reason of wideband absorption is the overlap of different absorption frequency which is caused by electromagnetic resonance; the size parameters and position of defect has important effect on its absorption property. It has many advantages, such as simply, easy to preparation and so on. It has potential application on aerospace measurement and control, remote data communication, LTE wideband mobile communication and other fields.
Izadi, F A; Bagirov, G
2009-01-01
With its origins stretching back several centuries, discrete calculus is now an increasingly central methodology for many problems related to discrete systems and algorithms. The topics covered here usually arise in many branches of science and technology, especially in discrete mathematics, numerical analysis, statistics and probability theory as well as in electrical engineering, but our viewpoint here is that these topics belong to a much more general realm of mathematics; namely calculus and differential equations because of the remarkable analogy of the subject to this branch of mathemati
ESD analog circuits and design
Voldman, Steven H
2014-01-01
A comprehensive and in-depth review of analog circuit layout, schematic architecture, device, power network and ESD design This book will provide a balanced overview of analog circuit design layout, analog circuit schematic development, architecture of chips, and ESD design. It will start at an introductory level and will bring the reader right up to the state-of-the-art. Two critical design aspects for analog and power integrated circuits are combined. The first design aspect covers analog circuit design techniques to achieve the desired circuit performance. The second and main aspect pres
A sparse electromagnetic imaging scheme using nonlinear landweber iterations
Desmal, Abdulla; Bagci, Hakan
2015-01-01
Development and use of electromagnetic inverse scattering techniques for imagining sparse domains have been on the rise following the recent advancements in solving sparse optimization problems. Existing techniques rely on iteratively converting
Efficient Pseudorecursive Evaluation Schemes for Non-adaptive Sparse Grids
Buse, Gerrit; Pflü ger, Dirk; Jacob, Riko
2014-01-01
In this work we propose novel algorithms for storing and evaluating sparse grid functions, operating on regular (not spatially adaptive), yet potentially dimensionally adaptive grid types. Besides regular sparse grids our approach includes truncated
Improved Sparse Channel Estimation for Cooperative Communication Systems
Directory of Open Access Journals (Sweden)
Guan Gui
2012-01-01
Full Text Available Accurate channel state information (CSI is necessary at receiver for coherent detection in amplify-and-forward (AF cooperative communication systems. To estimate the channel, traditional methods, that is, least squares (LS and least absolute shrinkage and selection operator (LASSO, are based on assumptions of either dense channel or global sparse channel. However, LS-based linear method neglects the inherent sparse structure information while LASSO-based sparse channel method cannot take full advantage of the prior information. Based on the partial sparse assumption of the cooperative channel model, we propose an improved channel estimation method with partial sparse constraint. At first, by using sparse decomposition theory, channel estimation is formulated as a compressive sensing problem. Secondly, the cooperative channel is reconstructed by LASSO with partial sparse constraint. Finally, numerical simulations are carried out to confirm the superiority of proposed methods over global sparse channel estimation methods.
Sparse reconstruction using distribution agnostic bayesian matching pursuit
Masood, Mudassir; Al-Naffouri, Tareq Y.
2013-01-01
A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics
2018-01-19
attributed to the inherent interpolation process in the MFT demodulation approach, which is more error-sensitive to discontinuous waveforms, such as...Multirate Frequency Transformations In the author’s recent work, frequency transformations enacted via multirate signal processing were used for wideband...FM to narrowband FM conversion to enable a wider range of wideband FM signals [9, 11]. The goal of the multirate processing module is to compress the
Wideband noise observed at ground level in the auroral region
International Nuclear Information System (INIS)
Benson, R.F.; Desch, M.D.
1991-01-01
A sideband noise event was detected at ground level from the Andoya Rocket Range in Norway in January 1989. The signals were observed on four commercial communication receivers (tuned to 159, 515, 905, and 1200 kHz), an ionosonde (200-kHz to 3.5-MHz interference-free observations) and a riometer (32.5 MHz). The event, which occurred during a period of magnetic disturbance near magnetic midnight, was the only one observed during nearly 3 weeks of operations. This low frequency-of-occurrence is attributed partly to high local noise levels. The ease with which this event was identified on the ionograms produced by the local ionosonde suggests that routine ionosonde recordings should be inspected in search for such events. Such an effort would enhance existing research directed toward developing techniques for identifying quiet communication channels and help to identify the origin and frequency-of-occurrence of high-latitude wideband noise events. 20 refs
A GPU-Based Wide-Band Radio Spectrometer
Chennamangalam, Jayanth; Scott, Simon; Jones, Glenn; Chen, Hong; Ford, John; Kepley, Amanda; Lorimer, D. R.; Nie, Jun; Prestage, Richard; Roshi, D. Anish; Wagner, Mark; Werthimer, Dan
2014-12-01
The graphics processing unit has become an integral part of astronomical instrumentation, enabling high-performance online data reduction and accelerated online signal processing. In this paper, we describe a wide-band reconfigurable spectrometer built using an off-the-shelf graphics processing unit card. This spectrometer, when configured as a polyphase filter bank, supports a dual-polarisation bandwidth of up to 1.1 GHz (or a single-polarisation bandwidth of up to 2.2 GHz) on the latest generation of graphics processing units. On the other hand, when configured as a direct fast Fourier transform, the spectrometer supports a dual-polarisation bandwidth of up to 1.4 GHz (or a single-polarisation bandwidth of up to 2.8 GHz).
Calculations of a wideband metamaterial absorber using equivalent medium theory
Huang, Xiaojun; Yang, Helin; Wang, Danqi; Yu, Shengqing; Lou, Yanchao; Guo, Ling
2016-08-01
Metamaterial absorbers (MMAs) have drawn increasing attention in many areas due to the fact that they can achieve electromagnetic (EM) waves with unity absorptivity. We demonstrate the design, simulation, experiment and calculation of a wideband MMA based on a loaded double-square-loop (DSL) array of chip resisters. For a normal incidence EM wave, the simulated results show that the absorption of the full width at half maximum is about 9.1 GHz, and the relative bandwidth is 87.1%. Experimental results are in agreement with the simulations. More importantly, equivalent medium theory (EMT) is utilized to calculate the absorptions of the DSL MMA, and the calculated absorptions based on EMT agree with the simulated and measured results. The method based on EMT provides a new way to analysis the mechanism of MMAs.
Resilience of LTE networks against smart jamming attacks: Wideband model
Aziz, Farhan M.
2015-12-03
LTE/LTE-A networks have been successfully providing advanced broadband services to millions of users worldwide. Lately, it has been suggested to use LTE networks for mission-critical applications like public safety, smart grid and military communications. We have previously shown that LTE networks are vulnerable to Denial-of-Service (DOS) and loss of service attacks from smart jammers. In this paper, we extend our previous work on resilience of LTE networks to wideband multipath fading channel, SINR estimation in frequency domain and computation of utilities based on observable parameters under the framework of single-shot and repeated games with asymmetric information. In a single-shot game formulation, network utility is severely compromised at its solutions, i.e. at the Nash Equilibria (NE). We propose evolved repeated-game strategy algorithms to combat smart jamming attacks that can be implemented in existing deployments using current technology. © 2015 IEEE.
Improvement of acoustical characteristics : wideband bamboo based polymer composite
Farid, M.; Purniawan, A.; Rasyida, A.; Ramadhani, M.; Komariyah, S.
2017-07-01
Environmental friendly and comfortable materials are desirable for applications in the automobile interior. The objective of this research was to examine and develop bamboo based polymer composites applied to the sound absorption materials of automobile door panels. Morphological analysis of the polyurethane/bamboo powder composite materials was carried out using scanning electron microscope to reveal the microscopic material behavior and followed by the FTIR and TGA testing. The finding demonstrated that this acoustical polymer composite materials provided a potential wideband sound absorption material. The range of frequency can be controlled between 500 and 4000 Hz with an average of sound absorption coefficient around 0.411 and it met to the door panels criteria.
Wideband and UWB Antennas for Wireless Applications: A Comprehensive Review
Directory of Open Access Journals (Sweden)
Renato Cicchetti
2017-01-01
Full Text Available A comprehensive review concerning the geometry, the manufacturing technologies, the materials, and the numerical techniques, adopted for the analysis and design of wideband and ultrawideband (UWB antennas for wireless applications, is presented. Planar, printed, dielectric, and wearable antennas, achievable on laminate (rigid and flexible, and textile dielectric substrates are taken into account. The performances of small, low-profile, and dielectric resonator antennas are illustrated paying particular attention to the application areas concerning portable devices (mobile phones, tablets, glasses, laptops, wearable computers, etc. and radio base stations. This information provides a guidance to the selection of the different antenna geometries in terms of bandwidth, gain, field polarization, time-domain response, dimensions, and materials useful for their realization and integration in modern communication systems.
A Novel Ropes-DrivenWideband Piezoelectric Vibration Energy Harvester
Directory of Open Access Journals (Sweden)
Jinhui Zhang
2016-12-01
Full Text Available This paper presents a novel piezoelectric vibration energy harvester (PVEH in which a high-frequency generating beam (HFGB is driven by an array of low-frequency driving beams (LFDBs using ropes. Two mechanisms based on frequency upconversion and multimodal harvesting work together to broaden the frequency bandwidth of the proposed vibration energy harvester (VEH. The experimental results show that the output power of generating beam (GB remains unchanged with the increasing number of driving beams (DBs, compared with the traditional arrays of beams vibration energy harvester (AB-VEH, and the output power and bandwidth behavior can be adjusted by parameters such as acceleration, rope margin, and stiffness of LFDBs, which shows the potential to achieve unlimited wideband vibration energy-harvesting for a variable environment.
Ultra-wideband horn antenna with abrupt radiator
McEwan, Thomas E.
1998-01-01
An ultra-wideband horn antenna transmits and receives impulse waveforms for short-range radars and impulse time-of flight systems. The antenna reduces or eliminates various sources of close-in radar clutter, including pulse dispersion and ringing, sidelobe clutter, and feedline coupling into the antenna. Dispersion is minimized with an abrupt launch point radiator element; sidelobe and feedline coupling are minimized by recessing the radiator into a metallic horn. Low frequency cut-off associated with a horn is extended by configuring the radiator drive impedance to approach a short circuit at low frequencies. A tapered feed plate connects at one end to a feedline, and at the other end to a launcher plate which is mounted to an inside wall of the horn. The launcher plate and feed plate join at an abrupt edge which forms the single launch point of the antenna.
Albert Einstein, Analogizer Extraordinaire
CERN. Geneva
2007-01-01
Where does deep insight in physics come from? It is tempting to think that it comes from the purest and most precise of reasoning, following ironclad laws of thought that compel the clear mind completely rigidly. And yet the truth is quite otherwise. One finds, when one looks closely at any major discovery, that the greatest of physicists are, in some sense, the most crazily daring and irrational of all physicists. Albert Einstein exemplifies this thesis in spades. In this talk I will describe the key role, throughout Albert Einstein's fabulously creative life, played by wild guesses made by analogy lacking any basis whatsoever in pure reasoning. In particular, in this year of 2007, the centenary of 1907, I will describe how over the course of two years (1905 through 1907) of pondering, Einstein slowly came, via analogy, to understand the full, radical consequences of the equation that he had first discovered and published in 1905, arguably the most famous equation of all time: E = mc2.
Directory of Open Access Journals (Sweden)
B. Qin
2018-04-01
Full Text Available Tiangong-2 is the first space laboratory in China, which launched in September 15, 2016. Wide-band Imaging Spectrometer is a medium resolution multispectral imager on Tiangong-2. In this paper, the authors introduced the indexes and parameters of Wideband Imaging Spectrometer, and made an objective evaluation about the data quality of Wide-band Imaging Spectrometer in radiation quality, image sharpness and information content, and compared the data quality evaluation results with that of Landsat-8. Although the data quality of Wide-band Imager Spectrometer has a certain disparity with Landsat-8 OLI data in terms of signal to noise ratio, clarity and entropy. Compared with OLI, Wide-band Imager Spectrometer has more bands, narrower bandwidth and wider swath, which make it a useful remote sensing data source in classification and identification of large and medium scale ground objects. In the future, Wide-band Imaging Spectrometer data will be widely applied in land cover classification, ecological environment assessment, marine and coastal zone monitoring, crop identification and classification, and other related areas.
Qin, B.; Li, L.; Li, S.
2018-04-01
Tiangong-2 is the first space laboratory in China, which launched in September 15, 2016. Wide-band Imaging Spectrometer is a medium resolution multispectral imager on Tiangong-2. In this paper, the authors introduced the indexes and parameters of Wideband Imaging Spectrometer, and made an objective evaluation about the data quality of Wide-band Imaging Spectrometer in radiation quality, image sharpness and information content, and compared the data quality evaluation results with that of Landsat-8. Although the data quality of Wide-band Imager Spectrometer has a certain disparity with Landsat-8 OLI data in terms of signal to noise ratio, clarity and entropy. Compared with OLI, Wide-band Imager Spectrometer has more bands, narrower bandwidth and wider swath, which make it a useful remote sensing data source in classification and identification of large and medium scale ground objects. In the future, Wide-band Imaging Spectrometer data will be widely applied in land cover classification, ecological environment assessment, marine and coastal zone monitoring, crop identification and classification, and other related areas.
Design and evaluation of sparse quantization index modulation watermarking schemes
Cornelis, Bruno; Barbarien, Joeri; Dooms, Ann; Munteanu, Adrian; Cornelis, Jan; Schelkens, Peter
2008-08-01
In the past decade the use of digital data has increased significantly. The advantages of digital data are, amongst others, easy editing, fast, cheap and cross-platform distribution and compact storage. The most crucial disadvantages are the unauthorized copying and copyright issues, by which authors and license holders can suffer considerable financial losses. Many inexpensive methods are readily available for editing digital data and, unlike analog information, the reproduction in the digital case is simple and robust. Hence, there is great interest in developing technology that helps to protect the integrity of a digital work and the copyrights of its owners. Watermarking, which is the embedding of a signal (known as the watermark) into the original digital data, is one method that has been proposed for the protection of digital media elements such as audio, video and images. In this article, we examine watermarking schemes for still images, based on selective quantization of the coefficients of a wavelet transformed image, i.e. sparse quantization-index modulation (QIM) watermarking. Different grouping schemes for the wavelet coefficients are evaluated and experimentally verified for robustness against several attacks. Wavelet tree-based grouping schemes yield a slightly improved performance over block-based grouping schemes. Additionally, the impact of the deployment of error correction codes on the most promising configurations is examined. The utilization of BCH-codes (Bose, Ray-Chaudhuri, Hocquenghem) results in an improved robustness as long as the capacity of the error codes is not exceeded (cliff-effect).
Sparse DOA estimation with polynomial rooting
DEFF Research Database (Denmark)
Xenaki, Angeliki; Gerstoft, Peter; Fernandez Grande, Efren
2015-01-01
Direction-of-arrival (DOA) estimation involves the localization of a few sources from a limited number of observations on an array of sensors. Thus, DOA estimation can be formulated as a sparse signal reconstruction problem and solved efficiently with compressive sensing (CS) to achieve highresol......Direction-of-arrival (DOA) estimation involves the localization of a few sources from a limited number of observations on an array of sensors. Thus, DOA estimation can be formulated as a sparse signal reconstruction problem and solved efficiently with compressive sensing (CS) to achieve...... highresolution imaging. Utilizing the dual optimal variables of the CS optimization problem, it is shown with Monte Carlo simulations that the DOAs are accurately reconstructed through polynomial rooting (Root-CS). Polynomial rooting is known to improve the resolution in several other DOA estimation methods...
Sparse learning of stochastic dynamical equations
Boninsegna, Lorenzo; Nüske, Feliks; Clementi, Cecilia
2018-06-01
With the rapid increase of available data for complex systems, there is great interest in the extraction of physically relevant information from massive datasets. Recently, a framework called Sparse Identification of Nonlinear Dynamics (SINDy) has been introduced to identify the governing equations of dynamical systems from simulation data. In this study, we extend SINDy to stochastic dynamical systems which are frequently used to model biophysical processes. We prove the asymptotic correctness of stochastic SINDy in the infinite data limit, both in the original and projected variables. We discuss algorithms to solve the sparse regression problem arising from the practical implementation of SINDy and show that cross validation is an essential tool to determine the right level of sparsity. We demonstrate the proposed methodology on two test systems, namely, the diffusion in a one-dimensional potential and the projected dynamics of a two-dimensional diffusion process.
Sparseness- and continuity-constrained seismic imaging
Herrmann, Felix J.
2005-04-01
Non-linear solution strategies to the least-squares seismic inverse-scattering problem with sparseness and continuity constraints are proposed. Our approach is designed to (i) deal with substantial amounts of additive noise (SNR formulating the solution of the seismic inverse problem in terms of an optimization problem. During the optimization, sparseness on the basis and continuity along the reflectors are imposed by jointly minimizing the l1- and anisotropic diffusion/total-variation norms on the coefficients and reflectivity, respectively. [Joint work with Peyman P. Moghaddam was carried out as part of the SINBAD project, with financial support secured through ITF (the Industry Technology Facilitator) from the following organizations: BG Group, BP, ExxonMobil, and SHELL. Additional funding came from the NSERC Discovery Grants 22R81254.
A density functional for sparse matter
DEFF Research Database (Denmark)
Langreth, D.C.; Lundqvist, Bengt; Chakarova-Kack, S.D.
2009-01-01
forces in molecules, to adsorbed molecules, like benzene, naphthalene, phenol and adenine on graphite, alumina and metals, to polymer and carbon nanotube (CNT) crystals, and hydrogen storage in graphite and metal-organic frameworks (MOFs), and to the structure of DNA and of DNA with intercalators......Sparse matter is abundant and has both strong local bonds and weak nonbonding forces, in particular nonlocal van der Waals (vdW) forces between atoms separated by empty space. It encompasses a broad spectrum of systems, like soft matter, adsorption systems and biostructures. Density-functional...... theory (DFT), long since proven successful for dense matter, seems now to have come to a point, where useful extensions to sparse matter are available. In particular, a functional form, vdW-DF (Dion et al 2004 Phys. Rev. Lett. 92 246401; Thonhauser et al 2007 Phys. Rev. B 76 125112), has been proposed...
Optimal properties of analog perceptrons with excitatory weights.
Directory of Open Access Journals (Sweden)
Claudia Clopath
Full Text Available The cerebellum is a brain structure which has been traditionally devoted to supervised learning. According to this theory, plasticity at the Parallel Fiber (PF to Purkinje Cell (PC synapses is guided by the Climbing fibers (CF, which encode an 'error signal'. Purkinje cells have thus been modeled as perceptrons, learning input/output binary associations. At maximal capacity, a perceptron with excitatory weights expresses a large fraction of zero-weight synapses, in agreement with experimental findings. However, numerous experiments indicate that the firing rate of Purkinje cells varies in an analog, not binary, manner. In this paper, we study the perceptron with analog inputs and outputs. We show that the optimal input has a sparse binary distribution, in good agreement with the burst firing of the Granule cells. In addition, we show that the weight distribution consists of a large fraction of silent synapses, as in previously studied binary perceptron models, and as seen experimentally.
Robust Fringe Projection Profilometry via Sparse Representation.
Budianto; Lun, Daniel P K
2016-04-01
In this paper, a robust fringe projection profilometry (FPP) algorithm using the sparse dictionary learning and sparse coding techniques is proposed. When reconstructing the 3D model of objects, traditional FPP systems often fail to perform if the captured fringe images have a complex scene, such as having multiple and occluded objects. It introduces great difficulty to the phase unwrapping process of an FPP system that can result in serious distortion in the final reconstructed 3D model. For the proposed algorithm, it encodes the period order information, which is essential to phase unwrapping, into some texture patterns and embeds them to the projected fringe patterns. When the encoded fringe image is captured, a modified morphological component analysis and a sparse classification procedure are performed to decode and identify the embedded period order information. It is then used to assist the phase unwrapping process to deal with the different artifacts in the fringe images. Experimental results show that the proposed algorithm can significantly improve the robustness of an FPP system. It performs equally well no matter the fringe images have a simple or complex scene, or are affected due to the ambient lighting of the working environment.
Detecting analogical resemblance without retrieving the source analogy.
Kostic, Bogdan; Cleary, Anne M; Severin, Kaye; Miller, Samuel W
2010-06-01
We examined whether people can detect analogical resemblance to an earlier experimental episode without being able to recall the experimental source of the analogical resemblance. We used four-word analogies (e.g., robin-nest/beaver-dam), in a variation of the recognition-without-cued-recall method (Cleary, 2004). Participants studied word pairs (e.g., robin-nest) and were shown new word pairs at test, half of which analogically related to studied word pairs (e.g., beaver-dam) and half of which did not. For each test pair, participants first attempted to recall an analogically similar pair from the study list. Then, regardless of whether successful recall occurred, participants were prompted to rate the familiarity of the test pair, which was said to indicate the likelihood that a pair that was analogically similar to the test pair had been studied. Across three experiments, participants demonstrated an ability to detect analogical resemblance without recalling the source analogy. Findings are discussed in terms of their potential relevance to the study of analogical reasoning and insight, as well as to the study of familiarity and recognition memory.
Marandi, Ahmadreza; de Klerk, Etienne; Dahl, Joachim
The sparse bounded degree sum-of-squares (sparse-BSOS) hierarchy of Weisser, Lasserre and Toh [arXiv:1607.01151,2016] constructs a sequence of lower bounds for a sparse polynomial optimization problem. Under some assumptions, it is proven by the authors that the sequence converges to the optimal
Ochoa, Agustin
2016-01-01
This book describes a consistent and direct methodology to the analysis and design of analog circuits with particular application to circuits containing feedback. The analysis and design of circuits containing feedback is generally presented by either following a series of examples where each circuit is simplified through the use of insight or experience (someone else’s), or a complete nodal-matrix analysis generating lots of algebra. Neither of these approaches leads to gaining insight into the design process easily. The author develops a systematic approach to circuit analysis, the Driving Point Impedance and Signal Flow Graphs (DPI/SFG) method that does not require a-priori insight to the circuit being considered and results in factored analysis supporting the design function. This approach enables designers to account fully for loading and the bi-directional nature of elements both in the feedback path and in the amplifier itself, properties many times assumed negligible and ignored. Feedback circuits a...
Beginning analog electronics through projects
Singmin, Andrew
2001-01-01
Analog electronics is the simplest way to start a fun, informative, learning program. Beginning Analog Electronics Through Projects, Second Edition was written with the needs of beginning hobbyists and students in mind. This revision of Andrew Singmin's popular Beginning Electronics Through Projects provides practical exercises, building techniques, and ideas for useful electronics projects. Additionally, it features new material on analog and digital electronics, and new projects for troubleshooting test equipment.Published in the tradition of Beginning Electronics Through Projects an
Multi-threaded Sparse Matrix Sparse Matrix Multiplication for Many-Core and GPU Architectures.
Energy Technology Data Exchange (ETDEWEB)
Deveci, Mehmet [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trott, Christian Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rajamanickam, Sivasankaran [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2018-01-01
Sparse Matrix-Matrix multiplication is a key kernel that has applications in several domains such as scientific computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix- matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and data structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.
Children's Development of Analogical Reasoning: Insights from Scene Analogy Problems
Richland, Lindsey E.; Morrison, Robert G.; Holyoak, Keith J.
2006-01-01
We explored how relational complexity and featural distraction, as varied in scene analogy problems, affect children's analogical reasoning performance. Results with 3- and 4-year-olds, 6- and 7-year-olds, 9- to 11-year-olds, and 13- and 14-year-olds indicate that when children can identify the critical structural relations in a scene analogy…
A novel integrated circuit for semiconductor radiation detectors with sparse readout
International Nuclear Information System (INIS)
Zhang Yacong; Chen Zhognjian; Lu Wengao; Zhao Baoying; Ji Lijiu
2008-01-01
A novel fully integrated CMOS readout circuit for semiconductor radiation detector with sparse readout is presented. The new sparse scheme is: when one channel is being read out, the trigger signal from other channels is delayed and then processed. Therefore, the dead time is reduced and so is the error rate. Besides sparse readout, sequential readout is also allowed, which means the analog voltages and addresses of all the channels are read out sequentially once there is a channel triggered. The circuit comprises Charge Sensitive Amplifier (CSA), pulse shaper, peak detect and hold circuit, and digital logic. A test chip of four channels designed in a 0.5 μ DPTM CMOS technology has been taped out. The results of post simulation indicate that the gain is 79.3 mV/fC with a linearity of 99.92%. The power dissipation is 4 mW per channel. Theory analysis and calculation shows that the error probability is approximately 2.5%, which means a reduction of about 37% is obtained compared with the traditional scanning scheme, assuming a 16-channel system with a particle rate of 100 k/s per channel. (authors)
Tolls, Volker; Stringfellow, Guy (Technical Monitor)
2001-01-01
The purpose of this study is to advance the design of the optical setup for a wide-band Optical Modulation Spectrometer (OMS) for use with astronomical heterodyne receiver systems. This report describes the progress of this investigation achieved from March until December 2001.
Directory of Open Access Journals (Sweden)
Sapan eAgarwal
2016-01-01
Full Text Available The exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational advantages of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an NxN crossbar, these two kernels are at a minimum O(N more energy efficient than a digital memory-based architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1. These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N reduction in energy for the entire algorithm. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.
Noniterative MAP reconstruction using sparse matrix representations.
Cao, Guangzhi; Bouman, Charles A; Webb, Kevin J
2009-09-01
We present a method for noniterative maximum a posteriori (MAP) tomographic reconstruction which is based on the use of sparse matrix representations. Our approach is to precompute and store the inverse matrix required for MAP reconstruction. This approach has generally not been used in the past because the inverse matrix is typically large and fully populated (i.e., not sparse). In order to overcome this problem, we introduce two new ideas. The first idea is a novel theory for the lossy source coding of matrix transformations which we refer to as matrix source coding. This theory is based on a distortion metric that reflects the distortions produced in the final matrix-vector product, rather than the distortions in the coded matrix itself. The resulting algorithms are shown to require orthonormal transformations of both the measurement data and the matrix rows and columns before quantization and coding. The second idea is a method for efficiently storing and computing the required orthonormal transformations, which we call a sparse-matrix transform (SMT). The SMT is a generalization of the classical FFT in that it uses butterflies to compute an orthonormal transform; but unlike an FFT, the SMT uses the butterflies in an irregular pattern, and is numerically designed to best approximate the desired transforms. We demonstrate the potential of the noniterative MAP reconstruction with examples from optical tomography. The method requires offline computation to encode the inverse transform. However, once these offline computations are completed, the noniterative MAP algorithm is shown to reduce both storage and computation by well over two orders of magnitude, as compared to a linear iterative reconstruction methods.
Galaxy redshift surveys with sparse sampling
International Nuclear Information System (INIS)
Chiang, Chi-Ting; Wullstein, Philipp; Komatsu, Eiichiro; Jee, Inh; Jeong, Donghui; Blanc, Guillermo A.; Ciardullo, Robin; Gronwall, Caryl; Hagen, Alex; Schneider, Donald P.; Drory, Niv; Fabricius, Maximilian; Landriau, Martin; Finkelstein, Steven; Jogee, Shardha; Cooper, Erin Mentuch; Tuttle, Sarah; Gebhardt, Karl; Hill, Gary J.
2013-01-01
Survey observations of the three-dimensional locations of galaxies are a powerful approach to measure the distribution of matter in the universe, which can be used to learn about the nature of dark energy, physics of inflation, neutrino masses, etc. A competitive survey, however, requires a large volume (e.g., V survey ∼ 10Gpc 3 ) to be covered, and thus tends to be expensive. A ''sparse sampling'' method offers a more affordable solution to this problem: within a survey footprint covering a given survey volume, V survey , we observe only a fraction of the volume. The distribution of observed regions should be chosen such that their separation is smaller than the length scale corresponding to the wavenumber of interest. Then one can recover the power spectrum of galaxies with precision expected for a survey covering a volume of V survey (rather than the volume of the sum of observed regions) with the number density of galaxies given by the total number of observed galaxies divided by V survey (rather than the number density of galaxies within an observed region). We find that regularly-spaced sampling yields an unbiased power spectrum with no window function effect, and deviations from regularly-spaced sampling, which are unavoidable in realistic surveys, introduce calculable window function effects and increase the uncertainties of the recovered power spectrum. On the other hand, we show that the two-point correlation function (pair counting) is not affected by sparse sampling. While we discuss the sparse sampling method within the context of the forthcoming Hobby-Eberly Telescope Dark Energy Experiment, the method is general and can be applied to other galaxy surveys
First results from the Cluster wideband plasma wave investigation
Directory of Open Access Journals (Sweden)
D. A. Gurnett
2001-09-01
Full Text Available In this report we present the first results from the Cluster wideband plasma wave investigation. The four Cluster spacecraft were successfully placed in closely spaced, high-inclination eccentric orbits around the Earth during two separate launches in July – August 2000. Each spacecraft includes a wideband plasma wave instrument designed to provide high-resolution electric and magnetic field wave-forms via both stored data and direct downlinks to the NASA Deep Space Network. Results are presented for three commonly occurring magnetospheric plasma wave phenomena: (1 whistlers, (2 chorus, and (3 auroral kilometric radiation. Lightning-generated whistlers are frequently observed when the spacecraft is inside the plasmasphere. Usually the same whistler can be detected by all spacecraft, indicating that the whistler wave packet extends over a spatial dimension at least as large as the separation distances transverse to the magnetic field, which during these observations were a few hundred km. This is what would be expected for nonducted whistler propagation. No case has been found in which a strong whistler was detected at one spacecraft, with no signal at the other spacecraft, which would indicate ducted propagation. Whistler-mode chorus emissions are also observed in the inner region of the magnetosphere. In contrast to lightning-generated whistlers, the individual chorus elements seldom show a one-to-one correspondence between the spacecraft, indicating that a typical chorus wave packet has dimensions transverse to the magnetic field of only a few hundred km or less. In one case where a good one-to-one correspondence existed, significant frequency variations were observed between the spacecraft, indicating that the frequency of the wave packet may be evolving as the wave propagates. Auroral kilometric radiation, which is an intense radio emission generated along the auroral field lines, is frequently observed over the polar regions. The
First results from the Cluster wideband plasma wave investigation
Directory of Open Access Journals (Sweden)
D. A. Gurnett
Full Text Available In this report we present the first results from the Cluster wideband plasma wave investigation. The four Cluster spacecraft were successfully placed in closely spaced, high-inclination eccentric orbits around the Earth during two separate launches in July – August 2000. Each spacecraft includes a wideband plasma wave instrument designed to provide high-resolution electric and magnetic field wave-forms via both stored data and direct downlinks to the NASA Deep Space Network. Results are presented for three commonly occurring magnetospheric plasma wave phenomena: (1 whistlers, (2 chorus, and (3 auroral kilometric radiation. Lightning-generated whistlers are frequently observed when the spacecraft is inside the plasmasphere. Usually the same whistler can be detected by all spacecraft, indicating that the whistler wave packet extends over a spatial dimension at least as large as the separation distances transverse to the magnetic field, which during these observations were a few hundred km. This is what would be expected for nonducted whistler propagation. No case has been found in which a strong whistler was detected at one spacecraft, with no signal at the other spacecraft, which would indicate ducted propagation. Whistler-mode chorus emissions are also observed in the inner region of the magnetosphere. In contrast to lightning-generated whistlers, the individual chorus elements seldom show a one-to-one correspondence between the spacecraft, indicating that a typical chorus wave packet has dimensions transverse to the magnetic field of only a few hundred km or less. In one case where a good one-to-one correspondence existed, significant frequency variations were observed between the spacecraft, indicating that the frequency of the wave packet may be evolving as the wave propagates. Auroral kilometric radiation, which is an intense radio emission generated along the auroral field lines, is frequently observed over the polar regions. The
A view of Kanerva's sparse distributed memory
Denning, P. J.
1986-01-01
Pentti Kanerva is working on a new class of computers, which are called pattern computers. Pattern computers may close the gap between capabilities of biological organisms to recognize and act on patterns (visual, auditory, tactile, or olfactory) and capabilities of modern computers. Combinations of numeric, symbolic, and pattern computers may one day be capable of sustaining robots. The overview of the requirements for a pattern computer, a summary of Kanerva's Sparse Distributed Memory (SDM), and examples of tasks this computer can be expected to perform well are given.
Wavelets for Sparse Representation of Music
DEFF Research Database (Denmark)
Endelt, Line Ørtoft; Harbo, Anders La-Cour
2004-01-01
We are interested in obtaining a sparse representation of music signals by means of a discrete wavelet transform (DWT). That means we want the energy in the representation to be concentrated in few DWT coefficients. It is well-known that the decay of the DWT coefficients is strongly related...... to the number of vanishing moments of the mother wavelet, and to the smoothness of the signal. In this paper we present the result of applying two classical families of wavelets to a series of musical signals. The purpose is to determine a general relation between the number of vanishing moments of the wavelet...
Sparse dynamics for partial differential equations.
Schaeffer, Hayden; Caflisch, Russel; Hauck, Cory D; Osher, Stanley
2013-04-23
We investigate the approximate dynamics of several differential equations when the solutions are restricted to a sparse subset of a given basis. The restriction is enforced at every time step by simply applying soft thresholding to the coefficients of the basis approximation. By reducing or compressing the information needed to represent the solution at every step, only the essential dynamics are represented. In many cases, there are natural bases derived from the differential equations, which promote sparsity. We find that our method successfully reduces the dynamics of convection equations, diffusion equations, weak shocks, and vorticity equations with high-frequency source terms.
Abnormal Event Detection Using Local Sparse Representation
DEFF Research Database (Denmark)
Ren, Huamin; Moeslund, Thomas B.
2014-01-01
We propose to detect abnormal events via a sparse subspace clustering algorithm. Unlike most existing approaches, which search for optimized normal bases and detect abnormality based on least square error or reconstruction error from the learned normal patterns, we propose an abnormality measurem...... is found that satisfies: the distance between its local space and the normal space is large. We evaluate our method on two public benchmark datasets: UCSD and Subway Entrance datasets. The comparison to the state-of-the-art methods validate our method's effectiveness....
Partitioning sparse rectangular matrices for parallel processing
Energy Technology Data Exchange (ETDEWEB)
Kolda, T.G.
1998-05-01
The authors are interested in partitioning sparse rectangular matrices for parallel processing. The partitioning problem has been well-studied in the square symmetric case, but the rectangular problem has received very little attention. They will formalize the rectangular matrix partitioning problem and discuss several methods for solving it. They will extend the spectral partitioning method for symmetric matrices to the rectangular case and compare this method to three new methods -- the alternating partitioning method and two hybrid methods. The hybrid methods will be shown to be best.
Functional fixedness in a technologically sparse culture.
German, Tim P; Barrett, H Clark
2005-01-01
Problem solving can be inefficient when the solution requires subjects to generate an atypical function for an object and the object's typical function has been primed. Subjects become "fixed" on the design function of the object, and problem solving suffers relative to control conditions in which the object's function is not demonstrated. In the current study, such functional fixedness was demonstrated in a sample of adolescents (mean age of 16 years) among the Shuar of Ecuadorian Amazonia, whose technologically sparse culture provides limited access to large numbers of artifacts with highly specialized functions. This result suggests that design function may universally be the core property of artifact concepts in human semantic memory.
Parallel preconditioning techniques for sparse CG solvers
Energy Technology Data Exchange (ETDEWEB)
Basermann, A.; Reichel, B.; Schelthoff, C. [Central Institute for Applied Mathematics, Juelich (Germany)
1996-12-31
Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role in numerical methods for solving discretized partial differential equations. The large size and the condition of many technical or physical applications in this area result in the need for efficient parallelization and preconditioning techniques of the CG method. In particular for very ill-conditioned matrices, sophisticated preconditioner are necessary to obtain both acceptable convergence and accuracy of CG. Here, we investigate variants of polynomial and incomplete Cholesky preconditioners that markedly reduce the iterations of the simply diagonally scaled CG and are shown to be well suited for massively parallel machines.
Optical analog transmission device
International Nuclear Information System (INIS)
Ikawa, Shinji.
1994-01-01
The present invention concerns a device such as electro-optical conversion elements, optoelectric-electric elements and optical transmission channel, not undergoing deleterious effects on the efficiency of conversion and transmission due to temperature, and aging change. That is, a sine wave superposing means superposes, on a detector signal to be transmitted, a sine-wave signal having a predetermined amplitude and at a frequency lower than that of the detector signal. An optoelectric conversion means converts the electric signal as the signal of the sine-wave signal superposing means into an optical signal and outputs the same to an optical transmitting channel. The optoelectric conversion means converts the transmitted signal to an electric signal. A discriminating means discriminates the electric signal into a detector signal and a sine-wave signal. A calculating means calculates an optical transmitting efficiency of the transmitting channel based on the amplitude of the discriminated sine-wave signal. A processing means compensates an amplitude value of the detector signals discriminated by the discriminating means based on the optical transmission efficiency. As a result, an optical analog transmission device can be attained, which conducts optical transmission at a high accuracy without undergoing the defective effects of the optical transmission efficiency. (I.S.)
Conjecturing via Reconceived Classical Analogy
Lee, Kyeong-Hwa; Sriraman, Bharath
2011-01-01
Analogical reasoning is believed to be an efficient means of problem solving and construction of knowledge during the search for and the analysis of new mathematical objects. However, there is growing concern that despite everyday usage, learners are unable to transfer analogical reasoning to learning situations. This study aims at facilitating…
DEFF Research Database (Denmark)
Bonde, Lars Ole
2014-01-01
Indeholder underkapitlerne: 2.5.1 Musik som analogi 2.5.2 Musik som metafor 2.5.3 Musikkens psykologiske funktioner - en taxonomi og metaforisk lytning til fire baroksatser......Indeholder underkapitlerne: 2.5.1 Musik som analogi 2.5.2 Musik som metafor 2.5.3 Musikkens psykologiske funktioner - en taxonomi og metaforisk lytning til fire baroksatser...
Drawing Analogies in Environmental Education
Affifi, Ramsey
2014-01-01
Reconsidering the origin, process, and outcomes of analogy-making suggests practices for environmental educators who strive to disengage humans from the isolating illusions of dichotomizing frameworks. We can view analogies as outcomes of developmental processes within which human subjectivity is but an element, threading our sense of self back…
International Nuclear Information System (INIS)
Zhang, Chi; Xu, Yiqing; Wei, Xiaoming; Tsia, Kevin K.; Wong, Kenneth K. Y.
2014-01-01
Time-stretch microscopy has emerged as an ultrafast optical imaging concept offering the unprecedented combination of the imaging speed and sensitivity. However, dedicated wideband and coherence optical pulse source with high shot-to-shot stability has been mandated for time-wavelength mapping—the enabling process for ultrahigh speed wavelength-encoded image retrieval. From the practical point of view, exploiting methods to relax the stringent requirements (e.g., temporal stability and coherence) for the source of time-stretch microscopy is thus of great value. In this paper, we demonstrated time-stretch microscopy by reconstructing the time-wavelength mapping sequence from a wideband incoherent source. Utilizing the time-lens focusing mechanism mediated by a narrow-band pulse source, this approach allows generation of a wideband incoherent source, with the spectral efficiency enhanced by a factor of 18. As a proof-of-principle demonstration, time-stretch imaging with the scan rate as high as MHz and diffraction-limited resolution is achieved based on the wideband incoherent source. We note that the concept of time-wavelength sequence reconstruction from wideband incoherent source can also be generalized to any high-speed optical real-time measurements, where wavelength is acted as the information carrier
DEFF Research Database (Denmark)
Han, Xixuan; Clemmensen, Line Katrine Harder
2015-01-01
We propose a general technique for obtaining sparse solutions to generalized eigenvalue problems, and call it Regularized Generalized Eigen-Decomposition (RGED). For decades, Fisher's discriminant criterion has been applied in supervised feature extraction and discriminant analysis, and it is for...
Fast Sparse Coding for Range Data Denoising with Sparse Ridges Constraint
Directory of Open Access Journals (Sweden)
Zhi Gao
2018-05-01
Full Text Available Light detection and ranging (LiDAR sensors have been widely deployed on intelligent systems such as unmanned ground vehicles (UGVs and unmanned aerial vehicles (UAVs to perform localization, obstacle detection, and navigation tasks. Thus, research into range data processing with competitive performance in terms of both accuracy and efficiency has attracted increasing attention. Sparse coding has revolutionized signal processing and led to state-of-the-art performance in a variety of applications. However, dictionary learning, which plays the central role in sparse coding techniques, is computationally demanding, resulting in its limited applicability in real-time systems. In this study, we propose sparse coding algorithms with a fixed pre-learned ridge dictionary to realize range data denoising via leveraging the regularity of laser range measurements in man-made environments. Experiments on both synthesized data and real data demonstrate that our method obtains accuracy comparable to that of sophisticated sparse coding methods, but with much higher computational efficiency.
Interferometric interpolation of sparse marine data
Hanafy, Sherif M.
2013-10-11
We present the theory and numerical results for interferometrically interpolating 2D and 3D marine surface seismic profiles data. For the interpolation of seismic data we use the combination of a recorded Green\\'s function and a model-based Green\\'s function for a water-layer model. Synthetic (2D and 3D) and field (2D) results show that the seismic data with sparse receiver intervals can be accurately interpolated to smaller intervals using multiples in the data. An up- and downgoing separation of both recorded and model-based Green\\'s functions can help in minimizing artefacts in a virtual shot gather. If the up- and downgoing separation is not possible, noticeable artefacts will be generated in the virtual shot gather. As a partial remedy we iteratively use a non-stationary 1D multi-channel matching filter with the interpolated data. Results suggest that a sparse marine seismic survey can yield more information about reflectors if traces are interpolated by interferometry. Comparing our results to those of f-k interpolation shows that the synthetic example gives comparable results while the field example shows better interpolation quality for the interferometric method. © 2013 European Association of Geoscientists & Engineers.
Balanced and sparse Tamo-Barg codes
Halbawi, Wael; Duursma, Iwan; Dau, Hoang; Hassibi, Babak
2017-01-01
We construct balanced and sparse generator matrices for Tamo and Barg's Locally Recoverable Codes (LRCs). More specifically, for a cyclic Tamo-Barg code of length n, dimension k and locality r, we show how to deterministically construct a generator matrix where the number of nonzeros in any two columns differs by at most one, and where the weight of every row is d + r - 1, where d is the minimum distance of the code. Since LRCs are designed mainly for distributed storage systems, the results presented in this work provide a computationally balanced and efficient encoding scheme for these codes. The balanced property ensures that the computational effort exerted by any storage node is essentially the same, whilst the sparse property ensures that this effort is minimal. The work presented in this paper extends a similar result previously established for Reed-Solomon (RS) codes, where it is now known that any cyclic RS code possesses a generator matrix that is balanced as described, but is sparsest, meaning that each row has d nonzeros.
Atmospheric inverse modeling via sparse reconstruction
Hase, Nils; Miller, Scot M.; Maaß, Peter; Notholt, Justus; Palm, Mathias; Warneke, Thorsten
2017-10-01
Many applications in atmospheric science involve ill-posed inverse problems. A crucial component of many inverse problems is the proper formulation of a priori knowledge about the unknown parameters. In most cases, this knowledge is expressed as a Gaussian prior. This formulation often performs well at capturing smoothed, large-scale processes but is often ill equipped to capture localized structures like large point sources or localized hot spots. Over the last decade, scientists from a diverse array of applied mathematics and engineering fields have developed sparse reconstruction techniques to identify localized structures. In this study, we present a new regularization approach for ill-posed inverse problems in atmospheric science. It is based on Tikhonov regularization with sparsity constraint and allows bounds on the parameters. We enforce sparsity using a dictionary representation system. We analyze its performance in an atmospheric inverse modeling scenario by estimating anthropogenic US methane (CH4) emissions from simulated atmospheric measurements. Different measures indicate that our sparse reconstruction approach is better able to capture large point sources or localized hot spots than other methods commonly used in atmospheric inversions. It captures the overall signal equally well but adds details on the grid scale. This feature can be of value for any inverse problem with point or spatially discrete sources. We show an example for source estimation of synthetic methane emissions from the Barnett shale formation.
Balanced and sparse Tamo-Barg codes
Halbawi, Wael
2017-08-29
We construct balanced and sparse generator matrices for Tamo and Barg\\'s Locally Recoverable Codes (LRCs). More specifically, for a cyclic Tamo-Barg code of length n, dimension k and locality r, we show how to deterministically construct a generator matrix where the number of nonzeros in any two columns differs by at most one, and where the weight of every row is d + r - 1, where d is the minimum distance of the code. Since LRCs are designed mainly for distributed storage systems, the results presented in this work provide a computationally balanced and efficient encoding scheme for these codes. The balanced property ensures that the computational effort exerted by any storage node is essentially the same, whilst the sparse property ensures that this effort is minimal. The work presented in this paper extends a similar result previously established for Reed-Solomon (RS) codes, where it is now known that any cyclic RS code possesses a generator matrix that is balanced as described, but is sparsest, meaning that each row has d nonzeros.
Fast switching wideband rectifying circuit for future RF energy harvesting
Asmeida, Akrem; Mustam, Saizalmursidi Md; Abidin, Z. Z.; Ashyap, A. Y. I.
2017-09-01
This paper presents the design and simulation of fast switching microwave rectifying circuit for ultra wideband patch antenna over a dual-frequency band (1.8 GHz for GSM and 2.4 GHz for ISM band). This band was chosen due to its high signal availability in the surrounding environment. New rectifying circuit topology with pair-matching trunks is designed using Advanced Design System (ADS) software. These trunks are interfaced with power divider to achieve good bandwidth, fast switching and high efficiency. The power divider acts as a good isolator between the trunks and its straightforward design structure makes it a good choice for a single feed UWB antenna. The simulated results demonstrate that the maximum output voltage is 2.13 V with an input power of -5 dBm. Moreover, the rectifier offers maximum efficiency of 86% for the input power of -5 dBm at given band, which could easily power up wireless sensor networks (WSN) and other small devices sufficiently.
PERFORMANCE OPTIMIZATION OF COGNITIVE RADIO WITH WIDEBAND SPECTRUM SENSING
Directory of Open Access Journals (Sweden)
E. Saraniya
2014-09-01
Full Text Available Cognitive radio (CR technology allows the unlicensed user to access the licensed spectrum bands. Spectrum sensing is an essential function in cognitive radio to detect the spectrum holes and opportunistically use the underutilized frequency bands without causing interference to primary user (PU. In this paper we are maximizing the throughput capacity of cognitive radio user and hence the performance of spectrum sensing and protection to licensed user improves over a wideband spectrum sensing band. The simulation of cognitive radio is done by analyzing the performance of energy detector spectrum sensing technique to detect primary user and to formulate the optimization using multiband joint detection method (MJD to achieve suitable trade- off between secondary user access and primary user network. The main aim of this paper is to maximize the probability of detection and to decrease the probabilities of miss detection and false alarm. To maximize the throughput it requires minimizing the throughput loss caused by miss detection and the significant reduction in probability of false alarm helps in achieving the spectral efficiency from the secondary user’s perspective. The simulation results show that the performance increases with the MJD method.
Ultra-wideband spectral analysis using S2 technology
International Nuclear Information System (INIS)
Krishna Mohan, R.; Chang, T.; Tian, M.; Bekker, S.; Olson, A.; Ostrander, C.; Khallaayoun, A.; Dollinger, C.; Babbitt, W.R.; Cole, Z.; Reibel, R.R.; Merkel, K.D.; Sun, Y.; Cone, R.; Schlottau, F.; Wagner, K.H.
2007-01-01
This paper outlines the efforts to develop an ultra-wideband spectrum analyzer that takes advantage of the broad spectral response and fine spectral resolution (∼25 kHz) of spatial-spectral (S2) materials. The S2 material can process the full spectrum of broadband microwave transmissions, with adjustable time apertures (down to 100 μs) and fast update rates (up to 1 kHz). A cryogenically cooled Tm:YAG crystal that operates on microwave signals modulated onto a stabilized optical carrier at 793 nm is used as the core for the spectrum analyzer. Efforts to develop novel component technologies that enhance the performance of the system and meet the application requirements are discussed, including an end-to-end device model for parameter optimization. We discuss the characterization of new ultra-wide bandwidth S2 materials. Detection and post-processing module development including the implementation of a novel spectral recovery algorithm using field programmable gate array technology (FPGA) is also discussed
Interference Mitigation for Coexistence of Heterogeneous Ultra-Wideband Systems
Directory of Open Access Journals (Sweden)
Wu Haitao
2006-01-01
Full Text Available Two ultra-wideband (UWB specifications, that is, direct-sequence (DS UWB and multiband-orthogonal frequency division multiplexing (MB-OFDM UWB, have been proposed as the candidates of the IEEE 802.15.3a, competing for the standard of high-speed wireless personal area networks (WPAN. Due to the withdrawal of the standardization process, the two heterogeneous UWB technologies will coexist in the future commercial market. In this paper, we investigate the mutual interference of such coexistence scenarios by physical layer Monte Carlo simulations. The results reveal that the coexistence severely degrades the performance of both UWB systems. Moreover, such interference is asymmetric due to the heterogeneity of the two systems. Therefore, we propose the goodput-oriented utility-based transmit power control (GUTPC algorithm for interference mitigation. The feasible condition and the convergence property of GUTPC are investigated, and the choice of the coefficients is discussed for fairness and efficiency. Numerical results demonstrate that GUTPC improves the goodput of the coexisting systems effectively and fairly with saved power.
Time-Domain Diversity in Ultra-Wideband MIMO Communications
Directory of Open Access Journals (Sweden)
Alain Sibille
2005-03-01
Full Text Available The development of ultra-wideband (UWB communications is impeded by the drastic transmitted power limitations imposed by regulation authorities due to the Ã¢Â€ÂœpollutingÃ¢Â€Â character of these radio emissions with respect to existing services. Technical solutions must be researched in order either to limit the level of spectral pollution by UWB devices or to increase their reception sensitivity. In the present work, we consider pulse-based modulations and investigate time-domain multiple-input multiple-output (MIMO diversity as one such possible solution. The basic principles of time-domain diversity in the extreme (low multipath density or intermediate (dense multipath UWB regimes are addressed, which predict the possibility of a MIMO gain equal to the product NtÃƒÂ—Nr of the numbers of transmit/receive antenna elements when the channel is not too severe. This analysis is confirmed by simulations using a parametric empirical stochastic double-directional channel model. They confirm the potential interest of MIMO approaches solutions in order to bring a valuable performance gain in UWB communications.
Ultra-wideband spectral analysis using S2 technology
Energy Technology Data Exchange (ETDEWEB)
Krishna Mohan, R. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States)]. E-mail: krishna@spectrum.montana.edu; Chang, T. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Tian, M. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Department of Physics, Montana State University, Bozeman, MT 59717 (United States); Bekker, S. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Olson, A. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Ostrander, C. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Khallaayoun, A. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Dollinger, C. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Babbitt, W.R. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Department of Physics, Montana State University, Bozeman, MT 59717 (United States); Cole, Z. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); S2 Corporation, Bozeman, MT 59718 (United States); Reibel, R.R. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); S2 Corporation, Bozeman, MT 59718 (United States); Merkel, K.D. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); S2 Corporation, Bozeman, MT 59718 (United States); Sun, Y. [Department of Physics, Montana State University, Bozeman, MT 59717 (United States); Cone, R. [Department of Physics, Montana State University, Bozeman, MT 59717 (United States); Schlottau, F. [University of Colorado, Boulder, CO 80309 (United States); Wagner, K.H. [University of Colorado, Boulder, CO 80309 (United States)
2007-11-15
This paper outlines the efforts to develop an ultra-wideband spectrum analyzer that takes advantage of the broad spectral response and fine spectral resolution ({approx}25 kHz) of spatial-spectral (S2) materials. The S2 material can process the full spectrum of broadband microwave transmissions, with adjustable time apertures (down to 100 {mu}s) and fast update rates (up to 1 kHz). A cryogenically cooled Tm:YAG crystal that operates on microwave signals modulated onto a stabilized optical carrier at 793 nm is used as the core for the spectrum analyzer. Efforts to develop novel component technologies that enhance the performance of the system and meet the application requirements are discussed, including an end-to-end device model for parameter optimization. We discuss the characterization of new ultra-wide bandwidth S2 materials. Detection and post-processing module development including the implementation of a novel spectral recovery algorithm using field programmable gate array technology (FPGA) is also discussed.
Wideband energy harvesting based on mixed connection of piezoelectric oscillators
Wu, P. H.; Chen, Y. J.; Li, B. Y.; Shu, Y. C.
2017-09-01
An approach for wideband energy harvesting together with power enhancement is proposed by integrating multiple piezoelectric oscillators with mixed parallel-series connection. This gives rise to the feasibility of shifting the operation frequency band to the dominant frequency domain of ambient excitations. There are two types of connection patterns discussed here: the p-type (s-type) is the parallel (series) connection of all sets of oscillators where some of them may be connected in series (parallel). In addition, the standard interface circuit used for electric rectification is adopted here. The analytic estimates of output power are derived and explicitly expressed in terms of different matrix formulations for these two connection patterns. They are subsequently validated and are found in good agreement with numerical simulations and experimental observations. Finally, the experimental results from the mixed connection of 4 piezoelectric oscillators show that the peak power of each array is about 3.4 times higher than that generated by a single piezoelectric oscillator. In addition, the bandwidth of the array capable of switching connection patterns is around 2.8 times wider than that based on a single array configuration. Hence, the effective bandwidth is enlarged without the loss of peak power.
Optimization of Planar Monopole Wideband Antenna for Wireless Communication System.
Shakib, Mohammed Nazmus; Moghavvemi, Mahmoud; Mahadi, Wan Nor Liza
2016-01-01
In this paper, a new compact wideband monopole antenna is presented for wireless communication applications. This antenna comprises of a new radiating patch, a new arc-shaped strip, microstrip feed line, and a notched ground plane. The proposed radiating patch is combined with a rectangular and semi-circular patch and is integrated with a partial ground plane to provide a wide impedance bandwidth. The new arc-shaped strip between the radiating patch and microstrip feed line creates an extra surface on the patch, which helps further widen the bandwidth. Inserting one step notch on the ground plane further enhances the bandwidth. The antenna has a compact size of 16×20×1.6mm3. The measured result indicated that the antenna achieves a 127% bandwidth at VSWR≤2, ranging from 4.9GHz to 22.1GHz. Stable radiation patterns with acceptable gain are achieved. Also, a measured bandwidth of 107.7% at VSWR≤1.5 (5.1-17GHz) is obtained, which is suitable for UWB outdoor propagation. This antenna is compatible with a good number of wireless standards, including UWB band, Wimax 5.4 GHz band, MVDDS (12.2-12.7GHz), and close range radar and satellite communication in the X-band (8-12GHz), and Ku band (12-18GHz).
Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances.
Alarifi, Abdulrahman; Al-Salman, AbdulMalik; Alsaleh, Mansour; Alnafessah, Ahmad; Al-Hadhrami, Suheer; Al-Ammar, Mai A; Al-Khalifa, Hend S
2016-05-16
In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space.
Wideband quin-stable energy harvesting via combined nonlinearity
Directory of Open Access Journals (Sweden)
Chen Wang
2017-04-01
Full Text Available In this work, we propose a wideband quintuple-well potential piezoelectric-based vibration energy harvester using a combined nonlinearity: the magnetic nonlinearity induced by magnetic force and the piecewise-linearity produced by mechanical impact. With extra stable states compared to other multi-stable harvesters, the quin-stable harvester can distribute its potential energy more uniformly, which provides shallower potential wells and results in lower excitation threshold for interwell motion. The mathematical model of this quin-stable harvester is derived and its equivalent piecewise-nonlinear restoring force is measured in the experiment and identified as piecewise polynomials. Numerical simulations and experimental verifications are performed in different levels of sinusoid excitation ranging from 1 to 25 Hz. The results demonstrate that, with lower potential barriers compared with tri-stable counterpart, the quin-stable arrangement can escape potential wells more easily for doing high-energy interwell motion over a wider band of frequencies. Moreover, by utilizing the mechanical stoppers, this harvester can produce significant output voltage under small tip deflections, which results in a high power density and is especially suitable for a compact MEMS approach.
Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances †
Alarifi, Abdulrahman; Al-Salman, AbdulMalik; Alsaleh, Mansour; Alnafessah, Ahmad; Al-Hadhrami, Suheer; Al-Ammar, Mai A.; Al-Khalifa, Hend S.
2016-01-01
In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space. PMID:27196906
Wide-band neutrino beams at 1000 GeV
International Nuclear Information System (INIS)
Malensek, A.; Stutte, L.
1983-01-01
In a previous publication, S. Mori discussed various broad-band neutrino and antineutrino beams using 1000 GeV protons on target. A new beam (SST) has been designed which provides the same neutrino flux as the quadrupole triplet (QT) while suppressing the wrong sign flux by a factor of 18. It also provides more than twice as much high energy antineutrino flux than the sign-selected bare target (SSBT) and in addition, has better neutrino suppression. While it is possible to increase the flux obtained from the single horn system over that previously described, the conclusion which states any horn focussing system seems to be of marginal use for Tevatron neutrino physics, is unchanged. Neutrino and antineutrino event rates and wrong sign backgrounds were computed using NUADA for a 100 metric ton detector of radius 1.5 meters. Due to radiation considerations and the existing transformer location, the horn beam is placed in its usual position inside the Target Tube. All other beams are placed in Fronthall. Thus, for the wide-band Fronthall trains a decay distance of 520 meters is used, versus 400 meters for the horn train
Digital Receiver Design for Transmitted Reference Ultra-Wideband Systems
Directory of Open Access Journals (Sweden)
Wang Yiyin
2009-01-01
Full Text Available Abstract A complete detection, channel estimation, synchronization, and equalization scheme for a transmitted reference (TR ultra-wideband (UWB system is proposed in this paper. The scheme is based on a data model which admits a moderate data rate and takes both the interframe interference (IFI and the intersymbol interference (ISI into consideration. Moreover, the bias caused by the interpulse interference (IPI in one frame is also taken into account. Based on the analysis of the stochastic properties of the received signals, several detectors are studied and evaluated. Furthermore, a data-aided two-stage synchronization strategy is proposed, which obtains sample-level timing in the range of one symbol at the first stage and then pursues symbol-level synchronization by looking for the header at the second stage. Three channel estimators are derived to achieve joint channel and timing estimates for the first stage, namely, the linear minimum mean square error (LMMSE estimator, the least squares (LS estimator, and the matched filter (MF. We check the performance of different combinations of channel estimation and equalization schemes and try to find the best combination, that is, the one providing a good tradeoff between complexity and performance.
Digital Receiver Design for Transmitted Reference Ultra-Wideband Systems
Directory of Open Access Journals (Sweden)
Yiyin Wang
2009-01-01
Full Text Available A complete detection, channel estimation, synchronization, and equalization scheme for a transmitted reference (TR ultra-wideband (UWB system is proposed in this paper. The scheme is based on a data model which admits a moderate data rate and takes both the interframe interference (IFI and the intersymbol interference (ISI into consideration. Moreover, the bias caused by the interpulse interference (IPI in one frame is also taken into account. Based on the analysis of the stochastic properties of the received signals, several detectors are studied and evaluated. Furthermore, a data-aided two-stage synchronization strategy is proposed, which obtains sample-level timing in the range of one symbol at the first stage and then pursues symbol-level synchronization by looking for the header at the second stage. Three channel estimators are derived to achieve joint channel and timing estimates for the first stage, namely, the linear minimum mean square error (LMMSE estimator, the least squares (LS estimator, and the matched filter (MF. We check the performance of different combinations of channel estimation and equalization schemes and try to find the best combination, that is, the one providing a good tradeoff between complexity and performance.
Ultra-Wideband Tracking System Design for Relative Navigation
Ni, Jianjun David; Arndt, Dickey; Bgo, Phong; Dekome, Kent; Dusl, John
2011-01-01
This presentation briefly discusses a design effort for a prototype ultra-wideband (UWB) time-difference-of-arrival (TDOA) tracking system that is currently under development at NASA Johnson Space Center (JSC). The system is being designed for use in localization and navigation of a rover in a GPS deprived environment for surface missions. In one application enabled by the UWB tracking, a robotic vehicle carrying equipments can autonomously follow a crewed rover from work site to work site such that resources can be carried from one landing mission to the next thereby saving up-mass. The UWB Systems Group at JSC has developed a UWB TDOA High Resolution Proximity Tracking System which can achieve sub-inch tracking accuracy of a target within the radius of the tracking baseline [1]. By extending the tracking capability beyond the radius of the tracking baseline, a tracking system is being designed to enable relative navigation between two vehicles for surface missions. A prototype UWB TDOA tracking system has been designed, implemented, tested, and proven feasible for relative navigation of robotic vehicles. Future work includes testing the system with the application code to increase the tracking update rate and evaluating the linear tracking baseline to improve the flexibility of antenna mounting on the following vehicle.
Ultra-Wideband Printed Slot Radiators with Controllable Frequency Characteristics
Directory of Open Access Journals (Sweden)
S. L. Chernyshev
2015-01-01
Full Text Available We have studied the possibility of creating ultra-wideband (UWB antennas with controlled frequency response of matching based on the printed slot antenna Vivaldi by introducing controlled resonators directly into the structure of the radiator. In the area of irregular slotline there are printed switched resonators with variable capacitance (varactor model, which allow tuning the frequency characteristics for each state of switching cavities, providing bandpass and band-barrage properties of the antenna. The investigation of reconfigurable printed resonators in the system of reconfigurable resonators of a bandpass filter is conducted. The paper considers filter to provide restructuring in the band (3-9 GHz. Electrodynamic simulation of the device was carried out in the time domain using a finite integration method. A bandstop reconfigurable filter is also investigated. The filter located on the substrate opposite the slit is based on tunable L-shaped resonator that has one end connected to the short-circuitor through the board metallization; the other end remains open and is brought into the region of interaction with the slotline. Such filter provides an effective narrow-band suppression and can be easily tuned to the desired frequency channel. The combination of these two types of filters allows you to create a controlled print Vivaldi slot antenna with combined properties. The paper investigates parameters of the scattering and radiation pattern of the antenna in different modes.
Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances
Directory of Open Access Journals (Sweden)
Abdulrahman Alarifi
2016-05-01
Full Text Available In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space.
A Wideband Channel Model for Intravehicular Nomadic Systems
Directory of Open Access Journals (Sweden)
François Bellens
2011-01-01
Full Text Available The increase in electronic entertainment equipments within vehicles has rendered the idea of replacing the wired links with intra-vehicle personal area networks. Ultra-wideband (UWB seems an appropriate candidate technology to meet the required data rates for interconnecting such devices. In particular, the multiband OFDM (MB-OFDM is able to provide very high transfer rates (up to 480 MBps over relatively short distances and low transmit power. In order to evaluate the performances of UWB systems within vehicles, a reliable channel model is needed. In this paper, a nomadic system where a base station placed in the center of the dashboard wants to communicate with fixed devices placed at the rear seat is investigated. A single-input single-output (SISO channel model for intra-vehicular communication (IVC systems is proposed, based on reverberation chamber theory. The model is based on measurements conducted in real traffic conditions, with a varying number of passengers in the car. Temporal variations of the wireless channels are also characterized and parametrized. The proposed model is validated by comparing model-independent statistics with the measurements.
Instabilities simulations with wideband feedback systems: CMAD, HEADTAIL, WARP
International Nuclear Information System (INIS)
Li, Kevin; Cesaratto, J; Fox, J D; Pivi, M; Rivetta, C; Rumolo, G
2013-01-01
Transverse mode coupling (TMCI) and electron cloud instabilities (ECI) pose fundamental limitations on the acceptable beam intensities in the SPS at CERN. This in turn limits the ultimate achievable luminosity in the LHC. Therefore, future luminosity upgrades foresee methods for evading TMCI as well as ECI. Proposed approaches within the LHC Injector Upgrade (LIU) project include new optics with reduced transition energy as well as vacuum chamber coating techniques. As a complementary option, high bandwidth feedback systems may provide instability mitigation by actively damping the intra-bunch motion of unstable modes. In an effort to evaluate the potentials and limitations of such feedback systems and to characterise some of the specifications, a numerical model of a realistic feedback system has been developed and integrated into available instabilities simulation codes. Together with the implementation of this new feedback system model, CMAD and HEADTAIL have been used to investigate the impact of different wideband feedback systems on ECI in the SPS. In this paper, we present some details on the numerical model of the realistic feedback system and its implementation as well as the results obtained from the simulation study using this model together with the instability codes. (author)
2017-11-01
on Bio -Inspired Optimization Techniques by Canh Ly, Nghia Tran, and Ozlem Kilic Approved for public release; distribution is...Research Laboratory Methodology for Designing and Developing a New Ultra-Wideband Antenna Based on Bio -Inspired Optimization Techniques by...SUBTITLE Methodology for Designing and Developing a New Ultra-Wideband Antenna Based on Bio -Inspired Optimization Techniques 5a. CONTRACT NUMBER
Parallel sparse direct solver for integrated circuit simulation
Chen, Xiaoming; Yang, Huazhong
2017-01-01
This book describes algorithmic methods and parallelization techniques to design a parallel sparse direct solver which is specifically targeted at integrated circuit simulation problems. The authors describe a complete flow and detailed parallel algorithms of the sparse direct solver. They also show how to improve the performance by simple but effective numerical techniques. The sparse direct solver techniques described can be applied to any SPICE-like integrated circuit simulator and have been proven to be high-performance in actual circuit simulation. Readers will benefit from the state-of-the-art parallel integrated circuit simulation techniques described in this book, especially the latest parallel sparse matrix solution techniques. · Introduces complicated algorithms of sparse linear solvers, using concise principles and simple examples, without complex theory or lengthy derivations; · Describes a parallel sparse direct solver that can be adopted to accelerate any SPICE-like integrated circuit simulato...
A new method for wideband characterization of resonator-based sensing platforms
International Nuclear Information System (INIS)
Munir, Farasat; Wathen, Adam; Hunt, William D.
2011-01-01
A new approach to the electronic instrumentation for extracting data from resonator-based sensing devices (e.g., microelectromechanical, piezoelectric, electrochemical, and acoustic) is suggested and demonstrated here. Traditionally, oscillator-based circuitry is employed to monitor shift in the resonance frequency of the resonator. These circuits give a single point measurement at the frequency where the oscillation criterion is met. However, the resonator response itself is broadband and contains much more information than a single point measurement. Here, we present a method for the broadband characterization of a resonator using white noise as an excitation signal. The resonator is used in a two-port filter configuration, and the resonator output is subjected to frequency spectrum analysis. The result is a wideband spectral map analogous to the magnitude of the S21 parameters of a conventional filter. Compared to other sources for broadband excitation (e.g., frequency chirp, multisine, or narrow time domain pulse), the white noise source requires no design of the input signal and is readily available for very wide bandwidths (1 MHz-3 GHz). Moreover, it offers simplicity in circuit design as it does not require precise impedance matching; whereas such requirements are very strict for oscillator-based circuit systems, and can be difficult to fulfill. This results in a measurement system that does not require calibration, which is a significant advantage over oscillator circuits. Simulation results are first presented for verification of the proposed system, followed by measurement results with a prototype implementation. A 434 MHz surface acoustic wave (SAW) resonator and a 5 MHz quartz crystal microbalance (QCM) are measured using the proposed method, and the results are compared to measurements taken by a conventional bench-top network analyzer. Maximum relative differences in the measured resonance frequencies of the SAW and QCM resonators are 0.0004% and 0
A Sparse Approximate Inverse Preconditioner for Nonsymmetric Linear Systems
Czech Academy of Sciences Publication Activity Database
Benzi, M.; Tůma, Miroslav
1998-01-01
Roč. 19, č. 3 (1998), s. 968-994 ISSN 1064-8275 R&D Projects: GA ČR GA201/93/0067; GA AV ČR IAA230401 Keywords : large sparse systems * interative methods * preconditioning * approximate inverse * sparse linear systems * sparse matrices * incomplete factorizations * conjugate gradient -type methods Subject RIV: BA - General Mathematics Impact factor: 1.378, year: 1998
Pelgrom, Marcel J M
2010-01-01
The design of an analog-to-digital converter or digital-to-analog converter is one of the most fascinating tasks in micro-electronics. In a converter the analog world with all its intricacies meets the realm of the formal digital abstraction. Both disciplines must be understood for an optimum conversion solution. In a converter also system challenges meet technology opportunities. Modern systems rely on analog-to-digital converters as an essential part of the complex chain to access the physical world. And processors need the ultimate performance of digital-to-analog converters to present the results of their complex algorithms. The same progress in CMOS technology that enables these VLSI digital systems creates new challenges for analog-to-digital converters: lower signal swings, less power and variability issues. Last but not least, the analog-to-digital converter must follow the cost reduction trend. These changing boundary conditions require micro-electronics engineers to consider their design choices for...
Analog fourier transform channelizer and OFDM receiver
2007-01-01
An OFDM receiver having an analog multiplier based I-Q channelizing filter, samples and holds consecutive analog I-Q samples of an I-Q baseband, the I-Q basebands having OFDM sub-channels. A lattice of analog I-Q multipliers and analog I-Q summers concurrently receives the held analog I-Q samples, performs analog I-Q multiplications and analog I-Q additions to concurrently generate a plurality of analog I-Q output signals, representing an N-point discrete Fourier transform of the held analog ...
Evaluation of strip-line pick-up system for the SPS wideband transverse feedback system
Kotzian, G; Steinhagen, R J; Valuch, D; Wehrle, U
2017-01-01
The proposed SPS Wideband Transverse Feedback sys- tem requires a wide-band pick-up system to be able to de- tect intra-bunch motion within the SPS proton bunches, captured and accelerated in a 200 MHz bucket. We present the electro-magnetic design of transverse beam position pick-up options optimised for installation in the SPS and evaluate their performance reach with respect to direct time domain sampling of the intra-bunch motion. The analy- sis also discusses the achieved subsystem responses of the associated cabling with new low dispersion smooth wall coaxial cables, wide-band generation of intensity and posi- tion signals by means of 180 degree RF hybrids as well as passive techniques to electronically suppress the beam off- set signal, needed to optimise the dynamic range and posi- tion resolution of the planned digital intra-bunch feedback system.
An Ultra-wideband and Polarization-independent Metasurface for RCS Reduction.
Su, Pei; Zhao, Yongjiu; Jia, Shengli; Shi, Wenwen; Wang, Hongli
2016-02-11
In this paper, an ultra-wideband and polarization-independent metasurface for radar cross section (RCS) reduction is proposed. The unit cell of the metasurface operates in a linear cross-polarization scheme in a broad band. The phase and amplitude of cross-polarized reflection can be separately controlled by its geometry and rotation angle. Based on the diffuse reflection theory, a 3-bit coding metasurface is designed to reduce the RCS in an ultra-wide band. The wideband property of the metasurface benefits from the wideband cross polarization conversion and flexible phase modulation. In addition, the polarization-independent feature of the metasurface is achieved by tailoring the rotation angle of each element. Both the simulated and measured results demonstrate that the proposed metasurface can reduce the RCS significantly in an ultra-wide frequency band for both normal and oblique incidences, which makes it promising in the applications such as electromagnetic cloaking.
A New Time-Hopping Multiple Access Communication System Simulator: Application to Ultra-Wideband
Directory of Open Access Journals (Sweden)
José M. Páez-Borrallo
2005-03-01
Full Text Available Time-hopping ultra-wideband technology presents some very attractive features for future indoor wireless systems in terms of achievable transmission rate and multiple access capabilities. This paper develops an algorithm to design time-hopping system simulators specially suitable for ultra-wideband, which takes advantage of some of the specific characteristics of this kind of systems. The algorithm allows an improvement of both the time capabilities and the achievable sampling rate and can be used to research into the influence of different parameters on the performance of the system. An additional result is the validation of a new general performance formula for time-hopping ultra-wideband systems with multipath channels.
A Novel Compact Wideband TSA Array for Near-Surface Ice Sheet Penetrating Radar Applications
Zhang, Feng; Liu, Xiaojun; Fang, Guangyou
2014-03-01
A novel compact tapered slot antenna (TSA) array for near-surface ice sheet penetrating radar applications is presented. This TSA array is composed of eight compact antenna elements which are etched on two 480mm × 283mm FR4 substrates. Each antenna element is fed by a wideband coplanar waveguide (CPW) to coupled strip-line (CPS) balun. The two antenna substrates are connected together with a metallic baffle. To obtain wideband properties, another two metallic baffles are used along broadsides of the array. This array is fed by a 1 × 8 wideband power divider. The measured S11 of the array is less than -10dB in the band of 500MHz-2GHz, and the measured gain is more than 6dBi in the whole band which agrees well with the simulated results.
Wideband propagation measurements at 30.3 GHz through a pecan orchard in Texas
Papazian, Peter B.; Jones, David L.; Espeland, Richard H.
1992-09-01
Wideband propagation measurements were made in a pecan orchard in Texas during April and August of 1990 to examine the propagation characteristics of millimeter-wave signals through vegetation. Measurements were made on tree obstructed paths with and without leaves. The study presents narrowband attenuation data at 9.6 and 28.8 GHz as well as wideband impulse response measurements at 30.3 GHz. The wideband probe (Violette et al., 1983), provides amplitude and delay of reflected and scattered signals and bit-error rate. This is accomplished using a 500 MBit/sec pseudo-random code to BPSK modulate a 28.8 GHz carrier. The channel impulse response is then extracted by cross correlating the received pseudo-random sequence with a locally generated replica.
Design of an Ultra-wideband Pseudo Random Coded MIMO Radar Based on Radio Frequency Switches
Directory of Open Access Journals (Sweden)
Su Hai
2017-02-01
Full Text Available A Multiple-Input Multiple-Output (MIMO ultra-wideband radar can detect the range and azimuth information of targets in real time. It is widely used for geological surveys, life rescue, through-wall tracking, and other military or civil fields. This paper presents the design of an ultra-wideband pseudo random coded MIMO radar that is based on Radio Frequency (RF switches and implements a MIMO radar system. RF switches are employed to reduce cost and complexity of the system. As the switch pressure value is limited, the peak power of the transmitting signal is 18 dBm. The ultra-wideband radar echo is obtained by hybrid sampling, and pulse compression is computed by Digital Signal Processors (DSPs embedded in an Field-Programmable Gate Array (FPGA to simplify the signal process. The experiment illustrates that the radar system can detect the range and azimuth information of targets in real time.
8th conference on Ultra-Wideband Short-Pulse Electromagnetics
Tyo, J. Scott; Baum, Carl E; Ultra-Wideband Short-Pulse Electromagnetics 8; UWBSP8
2007-01-01
The purpose of the Ultra-Wideband Short-Pulse Electromagnetics Conference series is to focus on advanced technologies for the generation, radiation and detection of ultra-wideband short pulse signals, taking into account their propagation and scattering from and coupling to targets of interest. This Conference series reports on developments in supporting mathematical and numerical methods and presents current and potential future applications of the technology. Ultra-Wideband Short-Pulse Electromagnetics 8 is based on the American Electromagnetics 2006 conference held from June 3-7 in Albuquerque, New Mexico. Topical areas covered in this volume include pulse radiation and measurement, scattering theory, target detection and identification, antennas, signal processing, and communications.
Dose-shaping using targeted sparse optimization
Energy Technology Data Exchange (ETDEWEB)
Sayre, George A.; Ruan, Dan [Department of Radiation Oncology, University of California - Los Angeles School of Medicine, 200 Medical Plaza, Los Angeles, California 90095 (United States)
2013-07-15
Purpose: Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, the authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method.Methods: In designing the energy minimization objective (E{sub tot}{sup sparse}), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L{sub 1} norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E{sub tot
Dose-shaping using targeted sparse optimization
International Nuclear Information System (INIS)
Sayre, George A.; Ruan, Dan
2013-01-01
Purpose: Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, the authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method.Methods: In designing the energy minimization objective (E tot sparse ), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L 1 norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E tot sparse improves
Dose-shaping using targeted sparse optimization.
Sayre, George A; Ruan, Dan
2013-07-01
Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, the authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method. In designing the energy minimization objective (E tot (sparse)), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L1 norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E tot (sparse) improves tradeoff between
Data analysis in high-dimensional sparse spaces
DEFF Research Database (Denmark)
Clemmensen, Line Katrine Harder
classification techniques for high-dimensional problems are presented: Sparse discriminant analysis, sparse mixture discriminant analysis and orthogonality constrained support vector machines. The first two introduces sparseness to the well known linear and mixture discriminant analysis and thereby provide low...... are applied to classifications of fish species, ear canal impressions used in the hearing aid industry, microbiological fungi species, and various cancerous tissues and healthy tissues. In addition, novel applications of sparse regressions (also called the elastic net) to the medical, concrete, and food...
Greedy vs. L1 convex optimization in sparse coding
DEFF Research Database (Denmark)
Ren, Huamin; Pan, Hong; Olsen, Søren Ingvor
2015-01-01
Sparse representation has been applied successfully in many image analysis applications, including abnormal event detection, in which a baseline is to learn a dictionary from the training data and detect anomalies from its sparse codes. During this procedure, sparse codes which can be achieved...... solutions. Considering the property of abnormal event detection, i.e., only normal videos are used as training data due to practical reasons, effective codes in classification application may not perform well in abnormality detection. Therefore, we compare the sparse codes and comprehensively evaluate...... their performance from various aspects to better understand their applicability, including computation time, reconstruction error, sparsity, detection...
Molecular modeling of fentanyl analogs
Directory of Open Access Journals (Sweden)
LJILJANA DOSEN-MICOVIC
2004-11-01
Full Text Available Fentanyl is a highly potent and clinically widely used narcotic analgesic. A large number of its analogs have been synthesized, some of which (sufentanil and alfentanyl are also in clinical use. Theoretical studies, in recent years, afforded a better understanding of the structure-activity relationships of this class of opiates and allowed insight into the molecular mechanism of the interactions of fentanyl analogs with their receptors. An overview of the current computational techniques for modeling fentanyl analogs, their receptors and ligand-receptor interactions is presented in this paper.
Pazos, Gonzalo; Rivadulla, Marcos L; Pérez-García, Xenxo; Gandara, Zoila; Pérez, Manuel
2014-01-01
The Gemini analogs are the last significant contribution to the family of vitamin D derivatives in medicine, for the treatment of cancer. The first Gemini analog was characterized by two symmetric side chains at C-20. Following numerous modifications, the most active analog bears a C-23-triple bond, C-26, 27- hexafluoro substituents on one side chain and a terminal trideuteromethylhydroxy group on the other side chain. This progression was possible due to improvements in the synthetic methods for the preparation of these derivatives, which allowed for increasing molecular complexity and complete diastereoselective control at C-20 and the substituted sidechains.
Directory of Open Access Journals (Sweden)
Markus Allén
2012-01-01
Full Text Available In modern wideband communication receivers, the large input-signal dynamics is a fundamental problem. Unintentional signal clipping occurs, if the receiver front-end with the analog-to-digital interface cannot respond to rapidly varying conditions. This paper discusses digital postprocessing compensation of such unintentional clipping in multiband OFDMA receivers. The proposed method iteratively mitigates the clipping distortion by exploiting the symbol decisions. The performance of the proposed method is illustrated with various computer simulations and also verified by concrete laboratory measurements with commercially available analog-to-digital hardware. It is shown that the clipping compensation algorithm implemented in a turbo decoding OFDM receiver is able to remove almost all the clipping distortion even under significant clipping in fading channel circumstances. That is to say, it is possible to nearly recover the receiver performance to the level, which would be achieved in the equivalent nonclipped situation.
Design and Implementation of Wideband Exciter for an Ultra-high Resolution Airborne SAR System
Directory of Open Access Journals (Sweden)
Jia Ying-xin
2013-03-01
Full Text Available According to an ultra-high resolution airborne SAR system with better than 0.1 m resolution, a wideband Linear Frequency Modulated (LFM pulse compression exciter with 14.8 GHz carrier and 3.2 GHz bandwidth is designed and implemented. The selection of signal generation scheme and some key technique points for wideband LFM waveform is presented in detail. Then, an acute test and analysis of the LFM signal is performed. The final airborne experiments demonstrate the validity of the LFM source which is one of the subsystems in an ultra-high resolution airborne SAR system.
Wideband Radar Echo Frequency-domain Simulation and Analysis for High Speed Moving Targets
Directory of Open Access Journals (Sweden)
Ning Chao
2014-04-01
Full Text Available A frequency-domain method is proposed for wideband radar echo simulation of high-speed moving targets. Based on the physical process of electromagnetic waves observing a moving target, a frequency-domain echo model of wideband radar is constructed, and the block diagram of the radar echo simulation in frequency-domain is presented. Then, the impacts of radial velocity and slant range on the matching filtering of LFM radar are analyzed, and some quantitative conclusions on the shift and expansion of the radar profiles are obtained. Simulation results illustrate the correctness and efficiency of the proposed method.
Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide
DEFF Research Database (Denmark)
Xiao, Binggang; Li, Sheng-Hua; Xiao, Sanshui
2016-01-01
Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN and satel......Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN...
Wideband Dual-Polarization Patch Antenna Array With Parallel Strip Line Balun Feeding
DEFF Research Database (Denmark)
Zhang, Jin; Lin, Xianqi; Nie, Liying
2016-01-01
A wideband dual-polarization patch antenna array is proposed in this letter. The array is fed by a parallel strip line balun, which is adopted to generate 180° phase shift in a wide frequency range. In addition, this balun has simple structure, very small phase shift error, and good ports isolati...... is higher than 30 dB. The simulation and measurement turns out to be similar. This antenna array can be used in TD-LTE base stations, and the design methods are also useful to other wideband microstrip antennas....
Sanad, Mohamed; Hassan, Noha
2014-01-01
A dual resonant antenna configuration is developed for multistandard multifunction mobile handsets and portable computers. Only two wideband resonant antennas can cover most of the LTE spectrums in portable communication equipment. The bandwidth that can be covered by each antenna exceeds 70% without using any matching or tuning circuits, with efficiencies that reach 80%. Thus, a dual configuration of them is capable of covering up to 39 LTE (4G) bands besides the existing 2G and 3G bands. 2×2 MIMO configurations have been also developed for the two wideband antennas with a maximum isolation and a minimum correlation coefficient between the primary and the diversity antennas.
Directory of Open Access Journals (Sweden)
Mohamed Sanad
2014-01-01
Full Text Available A dual resonant antenna configuration is developed for multistandard multifunction mobile handsets and portable computers. Only two wideband resonant antennas can cover most of the LTE spectrums in portable communication equipment. The bandwidth that can be covered by each antenna exceeds 70% without using any matching or tuning circuits, with efficiencies that reach 80%. Thus, a dual configuration of them is capable of covering up to 39 LTE (4G bands besides the existing 2G and 3G bands. 2×2 MIMO configurations have been also developed for the two wideband antennas with a maximum isolation and a minimum correlation coefficient between the primary and the diversity antennas.
Sparse Bayesian Learning for Nonstationary Data Sources
Fujimaki, Ryohei; Yairi, Takehisa; Machida, Kazuo
This paper proposes an online Sparse Bayesian Learning (SBL) algorithm for modeling nonstationary data sources. Although most learning algorithms implicitly assume that a data source does not change over time (stationary), one in the real world usually does due to such various factors as dynamically changing environments, device degradation, sudden failures, etc (nonstationary). The proposed algorithm can be made useable for stationary online SBL by setting time decay parameters to zero, and as such it can be interpreted as a single unified framework for online SBL for use with stationary and nonstationary data sources. Tests both on four types of benchmark problems and on actual stock price data have shown it to perform well.
Narrowband interference parameterization for sparse Bayesian recovery
Ali, Anum
2015-09-11
This paper addresses the problem of narrowband interference (NBI) in SC-FDMA systems by using tools from compressed sensing and stochastic geometry. The proposed NBI cancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a Bayesian sparse recovery procedure. This is done by keeping a few randomly chosen sub-carriers data free to sense the NBI signal at the receiver. As Bayesian recovery requires knowledge of some NBI parameters (i.e., mean, variance and sparsity rate), we use tools from stochastic geometry to obtain analytical expressions for the required parameters. Our simulation results validate the analysis and depict suitability of the proposed recovery method for NBI mitigation. © 2015 IEEE.
Modern algorithms for large sparse eigenvalue problems
International Nuclear Information System (INIS)
Meyer, A.
1987-01-01
The volume is written for mathematicians interested in (numerical) linear algebra and in the solution of large sparse eigenvalue problems, as well as for specialists in engineering, who use the considered algorithms in the investigation of eigenoscillations of structures, in reactor physics, etc. Some variants of the algorithms based on the idea of a gradient-type direction of movement are presented and their convergence properties are discussed. From this, a general strategy for the direct use of preconditionings for the eigenvalue problem is derived. In this new approach the necessity of the solution of large linear systems is entirely avoided. Hence, these methods represent a new alternative to some other modern eigenvalue algorithms, as they show a slightly slower convergence on the one hand but essentially lower numerical and data processing problems on the other hand. A brief description and comparison of some well-known methods (i.e. simultaneous iteration, Lanczos algorithm) completes this volume. (author)
Sparse random matrices: The eigenvalue spectrum revisited
International Nuclear Information System (INIS)
Semerjian, Guilhem; Cugliandolo, Leticia F.
2003-08-01
We revisit the derivation of the density of states of sparse random matrices. We derive a recursion relation that allows one to compute the spectrum of the matrix of incidence for finite trees that determines completely the low concentration limit. Using the iterative scheme introduced by Biroli and Monasson [J. Phys. A 32, L255 (1999)] we find an approximate expression for the density of states expected to hold exactly in the opposite limit of large but finite concentration. The combination of the two methods yields a very simple geometric interpretation of the tails of the spectrum. We test the analytic results with numerical simulations and we suggest an indirect numerical method to explore the tails of the spectrum. (author)
ESTIMATION OF FUNCTIONALS OF SPARSE COVARIANCE MATRICES.
Fan, Jianqing; Rigollet, Philippe; Wang, Weichen
High-dimensional statistical tests often ignore correlations to gain simplicity and stability leading to null distributions that depend on functionals of correlation matrices such as their Frobenius norm and other ℓ r norms. Motivated by the computation of critical values of such tests, we investigate the difficulty of estimation the functionals of sparse correlation matrices. Specifically, we show that simple plug-in procedures based on thresholded estimators of correlation matrices are sparsity-adaptive and minimax optimal over a large class of correlation matrices. Akin to previous results on functional estimation, the minimax rates exhibit an elbow phenomenon. Our results are further illustrated in simulated data as well as an empirical study of data arising in financial econometrics.
Miniature Laboratory for Detecting Sparse Biomolecules
Lin, Ying; Yu, Nan
2005-01-01
A miniature laboratory system has been proposed for use in the field to detect sparsely distributed biomolecules. By emphasizing concentration and sorting of specimens prior to detection, the underlying system concept would make it possible to attain high detection sensitivities without the need to develop ever more sensitive biosensors. The original purpose of the proposal is to aid the search for signs of life on a remote planet by enabling the detection of specimens as sparse as a few molecules or microbes in a large amount of soil, dust, rocks, water/ice, or other raw sample material. Some version of the system could prove useful on Earth for remote sensing of biological contamination, including agents of biological warfare. Processing in this system would begin with dissolution of the raw sample material in a sample-separation vessel. The solution in the vessel would contain floating microscopic magnetic beads coated with substances that could engage in chemical reactions with various target functional groups that are parts of target molecules. The chemical reactions would cause the targeted molecules to be captured on the surfaces of the beads. By use of a controlled magnetic field, the beads would be concentrated in a specified location in the vessel. Once the beads were thus concentrated, the rest of the solution would be discarded. This procedure would obviate the filtration steps and thereby also eliminate the filter-clogging difficulties of typical prior sample-concentration schemes. For ferrous dust/soil samples, the dissolution would be done first in a separate vessel before the solution is transferred to the microbead-containing vessel.
Analog filters in nanometer CMOS
Uhrmann, Heimo; Zimmermann, Horst
2014-01-01
Starting from the basics of analog filters and the poor transistor characteristics in nanometer CMOS 10 high-performance analog filters developed by the authors in 120 nm and 65 nm CMOS are described extensively. Among them are gm-C filters, current-mode filters, and active filters for system-on-chip realization for Bluetooth, WCDMA, UWB, DVB-H, and LTE applications. For the active filters several operational amplifier designs are described. The book, furthermore, contains a review of the newest state of research on low-voltage low-power analog filters. To cover the topic of the book comprehensively, linearization issues and measurement methods for the characterization of advanced analog filters are introduced in addition. Numerous elaborate illustrations promote an easy comprehension. This book will be of value to engineers and researchers in industry as well as scientists and Ph.D students at universities. The book is also recommendable to graduate students specializing on nanoelectronics, microelectronics ...
Wideband microwave generation with GaAs photoconductive switches
Druce, R. L.; Pocha, M. D.; Griffin, K. L.; Stein, J. M.; Obannon, B. J. J.
1991-07-01
We are using solid state photoconductive switches to generate wideband microwave pulses with peak powers to 20 MW. A parallel-plate Blumlein transmission line is used to directly feed an exponential taper antenna to produce single pulses with rise times of 200 ps and pulse durations of 340 ps (FWHM). Voltages up to 21 kV have been generated in a 1 cm tall, 12 cm wide parallel-plate line. With the switches operated in linear mode, we have demonstrated phasing of several switches to generate a coherent wave. Generated and radiated signals agree very well with numerical calculations. Radiation efficiencies approach 30 percent. The Blumlein dielectric can be changed to produce a damped waveform, thereby modifying the bandwidth of the signal. We have generated damped waveforms of up to 3 cycles using this method. The parallel-plate geometry lends itself to coupling to an antenna structure to radiate efficiently. The geometry also lends itself to expanding the generator in height and width. We have stacked two generators to nearly double the output power without degrading the pulse characteristics. Applications of ultrashort microwave pulses require a high repetition rate and long life from the generator. Life times of greater than 10(exp 5) shots have been seen occasionally at low to medium power densities. As the power density of a solid state photoconductive switch is increased, device life decreases. We have the capability to test devices at a repetition rate of 30 Hz and voltages to 25 kV. Preliminary data indicates that repeated pulse biasing (without switching) of large LEC grown devices in a slab geometry with fields as low as 30 kV/cm damages the switch and eventually leads to failure.
Wideband microwave generation with GaAs photoconductive switches
Energy Technology Data Exchange (ETDEWEB)
Druce, R.L.; Pocha, M.D.; Griffin, K.L. (Lawrence Livermore National Lab., CA (United States)); Stein, J.M. (Rockwell International Corp., Albuquerque, NM (United States)); O' Bannon, B.J.J. (Rockwell International Corp., Anaheim, CA (United States))
1991-01-01
We are using solid state photoconductive switches to generate wideband microwave pulses with peak powers to 20 MW. A parallel-plate Blumlein transmission line is used to directly feed an exponential taper antenna to produce single pulses with rise times of 200 ps and pulse durations of 340 ps (FWHM). Voltages up to 21 kV have been generated in a 1 cm tall, 12 cm wide parallel-plate line. With the switches operated in linear mode, we have demonstrated phasing of several switches to generate a coherent wave. Generated and radiated signals agree very well with numerical calculations. Radiation efficiencies approach 30%. The Blumlein dielectric can be changed to produce a damped waveform, thereby modifying the bandwidth of the signal. We have generated damped waveforms of up to 3 cycles using this method. The parallel-plate geometry lends itself to coupling to an antenna structure to radiate efficiently. The geometry also lends itself to expanding the generator in height and width. We have stacked two generators to nearly double the output power without degrading the pulse characteristics. Applications of ultrashort microwave pulses (UWB radar, HPM weapons) require a high repetition rate and long life from the generator. Life times of >10{sup 5} shots have been seen occasionally at low to medium power densities. As the power density of a solid state photoconductive switch is increased, device life decreases. We have the capability to test devices at a repetition rate of 30 Hz and voltages to 25 kV. Preliminary data indicates that repeated pulse biasing (without switching) of large LEC grown devices in a slab geometry with fields as low as 30 kV/cm damages the switch and eventually leads to failure. 6 refs., 10 figs.
Wideband perfect coherent absorber based on white-light cavity
Kotlicki, Omer; Scheuer, Jacob
2015-03-01
Coherent Perfect Absorbers (CPAs) are optical cavities which can be described as time-reversed lasers where light waves that enter the cavity, coherently interfere and react with the intra-cavity losses to yield perfect absorption. In contrast to lasers, which benefit from high coherency and narrow spectral linewidths, for absorbers these properties are often undesirable as absorption at a single frequency is highly susceptible to spectral noise and inappropriate for most practical applications. Recently, a new class of cavities, characterized by a spectrally wide resonance has been proposed. Such resonators, often referred to as White Light Cavities (WLCs), include an intra-cavity superluminal phase element, designed to provide a phase response with a slope that is opposite in sign and equal in magnitude to that of light propagation through the empty cavity. Consequently, the resonance phase condition in WLCs is satisfied over a band of frequencies providing a spectrally wide resonance. WLCs have drawn much attention due to their attractiveness for various applications such as ultra-sensitive sensors and optical buffering components. Nevertheless, WLCs exhibit inherent losses that are often undesirable. Here we introduce a simple wideband CPA device that is based on the WLC concept along with a complete analytical analysis. We present analytical and FDTD simulations of a practical, highly compact (12µm), Silicon based WLC-CPA that exhibits a flat and wide absorption profile (40nm) and demonstrate its usefulness as an optical pulse terminator (>35db isolation) and an all optical modulator that span the entire C-Band and exhibit high immunity to spectral noise.
Ultra-Wideband Optical Modulation Spectrometer (OMS) Development
Gardner, Jonathan (Technical Monitor); Tolls, Volker
2004-01-01
The optical modulation spectrometer (OMS) is a novel, highly efficient, low mass backend for heterodyne receiver systems. Current and future heterodyne receiver systems operating at frequencies up to a few THz require broadband spectrometer backends to achieve spectral resolutions of R approximately 10(exp 5) to 10(exp 6) to carry out many important astronomical investigations. Among these are observations of broad emission and absorption lines from extra-galactic objects at high redshifts, spectral line surveys, and observations of planetary atmospheres. Many of these lines are pressure or velocity broadened with either large half-widths or line wings extending over several GHz. Current backend systems can cover the needed bandwidth only by combining the output of several spectrometers, each with typically up to 1 GHz bandwidth, or by combining several frequency-shifted spectra taken with a single spectrometer. An ultra-wideband optical modulation spectrometer with 10 - 40 GHz bandwidth will enable broadband ob- servations without the limitations and disadvantages of hybrid spectrometers. Spectrometers like the OMS will be important for both ground-based observatories and future space missions like the Single Aperture Far-Infrared Telescope (SAFIR) which might carry IR/submm array heterodyne receiver systems requiring a spectrometer for each array pixel. Small size, low mass and small power consumption are extremely important for space missions. This report summarizes the specifications developed for the OMS and lists already identified commercial parts. The report starts with a review of the principle of operation, then describes the most important components and their specifications which were derived from theory, and finishes with a conclusion and outlook.
Photonic Beamformer Model Based on Analog Fiber-Optic Links’ Components
International Nuclear Information System (INIS)
Volkov, V A; Gordeev, D A; Ivanov, S I; Lavrov, A P; Saenko, I I
2016-01-01
The model of photonic beamformer for wideband microwave phased array antenna is investigated. The main features of the photonic beamformer model based on true-time-delay technique, DWDM technology and fiber chromatic dispersion are briefly analyzed. The performance characteristics of the key components of photonic beamformer for phased array antenna in the receive mode are examined. The beamformer model composed of the components available on the market of fiber-optic analog communication links is designed and tentatively investigated. Experimental demonstration of the designed model beamforming features includes actual measurement of 5-element microwave linear array antenna far-field patterns in 6-16 GHz frequency range for antenna pattern steering up to 40°. The results of experimental testing show good accordance with the calculation estimates. (paper)
Analog elements for transuranic chemistries
International Nuclear Information System (INIS)
Weimer, W.C.
1982-01-01
The analytical technique for measuring trace concentrations of the analog rare earth elements has been refined for optimal detection. The technique has been used to determine the rare earth concentrations in a series of geological and biological materials, including samples harvested from controlled lysimeter investigations. These studies have demonstrated that any of the trivalent rare earth elements may be used as analog elements for the trivalent transuranics, americium and curium
CMOS Analog IC Design: Fundamentals
Bruun, Erik
2018-01-01
This book is intended for use as the main textbook for an introductory course in CMOS analog integrated circuit design. It is aimed at electronics engineering students who have followed basic courses in mathematics, physics, circuit theory, electronics and signal processing. It takes the students directly from a basic level to a level where they can start working on simple analog IC design projects or continue their studies using more advanced textbooks in the field. A distinct feature of thi...
Analogical proportions: another logical view
Prade, Henri; Richard, Gilles
This paper investigates the logical formalization of a restricted form of analogical reasoning based on analogical proportions, i.e. statements of the form a is to b as c is to d. Starting from a naive set theoretic interpretation, we highlight the existence of two noticeable companion proportions: one states that a is to b the converse of what c is to d (reverse analogy), while the other called paralogical proportion expresses that what a and b have in common, c and d have it also. We identify the characteristic postulates of the three types of proportions and examine their consequences from an abstract viewpoint. We further study the properties of the set theoretic interpretation and of the Boolean logic interpretation, and we provide another light on the understanding of the role of permutations in the modeling of the three types of proportions. Finally, we address the use of these proportions as a basis for inference in a propositional setting, and relate it to more general schemes of analogical reasoning. The differences between analogy, reverse-analogy, and paralogy is still emphasized in a three-valued setting, which is also briefly presented.
Moody, Daniela; Wohlberg, Brendt
2018-01-02
An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.
Sparse Source EEG Imaging with the Variational Garrote
DEFF Research Database (Denmark)
Hansen, Sofie Therese; Stahlhut, Carsten; Hansen, Lars Kai
2013-01-01
EEG imaging, the estimation of the cortical source distribution from scalp electrode measurements, poses an extremely ill-posed inverse problem. Recent work by Delorme et al. (2012) supports the hypothesis that distributed source solutions are sparse. We show that direct search for sparse solutions...
Support agnostic Bayesian matching pursuit for block sparse signals
Masood, Mudassir; Al-Naffouri, Tareq Y.
2013-01-01
priori knowledge of block partition and utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean square error (MMSE) estimate of the block-sparse signal
Local posterior concentration rate for multilevel sparse sequences
Belitser, E.N.; Nurushev, N.
2017-01-01
We consider empirical Bayesian inference in the many normal means model in the situation when the high-dimensional mean vector is multilevel sparse, that is,most of the entries of the parameter vector are some fixed values. For instance, the traditional sparse signal is a particular case (with one
Joint Group Sparse PCA for Compressed Hyperspectral Imaging.
Khan, Zohaib; Shafait, Faisal; Mian, Ajmal
2015-12-01
A sparse principal component analysis (PCA) seeks a sparse linear combination of input features (variables), so that the derived features still explain most of the variations in the data. A group sparse PCA introduces structural constraints on the features in seeking such a linear combination. Collectively, the derived principal components may still require measuring all the input features. We present a joint group sparse PCA (JGSPCA) algorithm, which forces the basic coefficients corresponding to a group of features to be jointly sparse. Joint sparsity ensures that the complete basis involves only a sparse set of input features, whereas the group sparsity ensures that the structural integrity of the features is maximally preserved. We evaluate the JGSPCA algorithm on the problems of compressed hyperspectral imaging and face recognition. Compressed sensing results show that the proposed method consistently outperforms sparse PCA and group sparse PCA in reconstructing the hyperspectral scenes of natural and man-made objects. The efficacy of the proposed compressed sensing method is further demonstrated in band selection for face recognition.
Confidence of model based shape reconstruction from sparse data
DEFF Research Database (Denmark)
Baka, N.; de Bruijne, Marleen; Reiber, J. H. C.
2010-01-01
Statistical shape models (SSM) are commonly applied for plausible interpolation of missing data in medical imaging. However, when fitting a shape model to sparse information, many solutions may fit the available data. In this paper we derive a constrained SSM to fit noisy sparse input landmarks...
Comparison of Methods for Sparse Representation of Musical Signals
DEFF Research Database (Denmark)
Endelt, Line Ørtoft; la Cour-Harbo, Anders
2005-01-01
by a number of sparseness measures and results are shown on the ℓ1 norm of the coefficients, using a dictionary containing a Dirac basis, a Discrete Cosine Transform, and a Wavelet Packet. Evaluated only on the sparseness Matching Pursuit is the best method, and it is also relatively fast....
Robust Face Recognition Via Gabor Feature and Sparse Representation
Directory of Open Access Journals (Sweden)
Hao Yu-Juan
2016-01-01
Full Text Available Sparse representation based on compressed sensing theory has been widely used in the field of face recognition, and has achieved good recognition results. but the face feature extraction based on sparse representation is too simple, and the sparse coefficient is not sparse. In this paper, we improve the classification algorithm based on the fusion of sparse representation and Gabor feature, and then improved algorithm for Gabor feature which overcomes the problem of large dimension of the vector dimension, reduces the computation and storage cost, and enhances the robustness of the algorithm to the changes of the environment.The classification efficiency of sparse representation is determined by the collaborative representation,we simplify the sparse constraint based on L1 norm to the least square constraint, which makes the sparse coefficients both positive and reduce the complexity of the algorithm. Experimental results show that the proposed method is robust to illumination, facial expression and pose variations of face recognition, and the recognition rate of the algorithm is improved.
Sparse Frequency Waveform Design for Radar-Embedded Communication
Directory of Open Access Journals (Sweden)
Chaoyun Mai
2016-01-01
Full Text Available According to the Tag application with function of covert communication, a method for sparse frequency waveform design based on radar-embedded communication is proposed. Firstly, sparse frequency waveforms are designed based on power spectral density fitting and quasi-Newton method. Secondly, the eigenvalue decomposition of the sparse frequency waveform sequence is used to get the dominant space. Finally the communication waveforms are designed through the projection of orthogonal pseudorandom vectors in the vertical subspace. Compared with the linear frequency modulation waveform, the sparse frequency waveform can further improve the bandwidth occupation of communication signals, thus achieving higher communication rate. A certain correlation exists between the reciprocally orthogonal communication signals samples and the sparse frequency waveform, which guarantees the low SER (signal error rate and LPI (low probability of intercept. The simulation results verify the effectiveness of this method.
Producing and Recognizing Analogical Relations
Lipkens, Regina; Hayes, Steven C
2009-01-01
Analogical reasoning is an important component of intelligent behavior, and a key test of any approach to human language and cognition. Only a limited amount of empirical work has been conducted from a behavior analytic point of view, most of that within Relational Frame Theory (RFT), which views analogy as a matter of deriving relations among relations. The present series of four studies expands previous work by exploring the applicability of this model of analogy to topography-based rather than merely selection-based responses and by extending the work into additional relations, including nonsymmetrical ones. In each of the four studies participants pretrained in contextual control over nonarbitrary stimulus relations of sameness and opposition, or of sameness, smaller than, and larger than, learned arbitrary stimulus relations in the presence of these relational cues and derived analogies involving directly trained relations and derived relations of mutual and combinatorial entailment, measured using a variety of productive and selection-based measures. In Experiment 1 participants successfully recognized analogies among stimulus networks containing same and opposite relations; in Experiment 2 analogy was successfully used to extend derived relations to pairs of novel stimuli; in Experiment 3 the procedure used in Experiment 1 was extended to nonsymmetrical comparative relations; in Experiment 4 the procedure used in Experiment 2 was extended to nonsymmetrical comparative relations. Although not every participant showed the effects predicted, overall the procedures occasioned relational responses consistent with an RFT account that have not yet been demonstrated in a behavior-analytic laboratory setting, including productive responding on the basis of analogies. PMID:19230515
Relaxations to Sparse Optimization Problems and Applications
Skau, Erik West
Parsimony is a fundamental property that is applied to many characteristics in a variety of fields. Of particular interest are optimization problems that apply rank, dimensionality, or support in a parsimonious manner. In this thesis we study some optimization problems and their relaxations, and focus on properties and qualities of the solutions of these problems. The Gramian tensor decomposition problem attempts to decompose a symmetric tensor as a sum of rank one tensors.We approach the Gramian tensor decomposition problem with a relaxation to a semidefinite program. We study conditions which ensure that the solution of the relaxed semidefinite problem gives the minimal Gramian rank decomposition. Sparse representations with learned dictionaries are one of the leading image modeling techniques for image restoration. When learning these dictionaries from a set of training images, the sparsity parameter of the dictionary learning algorithm strongly influences the content of the dictionary atoms.We describe geometrically the content of trained dictionaries and how it changes with the sparsity parameter.We use statistical analysis to characterize how the different content is used in sparse representations. Finally, a method to control the structure of the dictionaries is demonstrated, allowing us to learn a dictionary which can later be tailored for specific applications. Variations of dictionary learning can be broadly applied to a variety of applications.We explore a pansharpening problem with a triple factorization variant of coupled dictionary learning. Another application of dictionary learning is computer vision. Computer vision relies heavily on object detection, which we explore with a hierarchical convolutional dictionary learning model. Data fusion of disparate modalities is a growing topic of interest.We do a case study to demonstrate the benefit of using social media data with satellite imagery to estimate hazard extents. In this case study analysis we
Neto, A.; Cavallo, D.; Gerini, G.
2011-01-01
Most phased arrays are designed using infinite array theory, which does not account for edge effects. However, this approximation might not be adequate for the design of wideband arrays, for which truncation effects are more significant than in traditional narrow-band arrays. In particular, edge
Design of an ultra-wideband ground-penetrating radar system using impulse radiating antennas
Rhebergen, J.B.; Zwamborn, A.P.M.; Giri, D.V.
1998-01-01
At TNO-FEL, one of the research programs is to explore the use of ultra-wideband (UWB) electromagnetic fields in a bi-static ground-penetrating radar (GPR) system for the detection, location and identification of buried items of unexploded ordnance (e.g. land mines). In the present paper we describe
Design of an ultra-wideband ground-penetrating radar system using impulse radiating antennas
Rhebergen, J.B.; Zwamborn, A.P.M.; Giri, D.V.
1999-01-01
At TNO-FEL, one of the research programs is to explore the use of ultra-wideband (UWB) electromagnetic fields in a bi-static ground-penetrating radar (GPR) system for the detection, location and identification of buried items of unexploded ordnance (e.g. land mines). In the present paper we describe
Iterative equalization for OFDM systems over wideband Multi-Scale Multi-Lag channels
Xu, T.; Tang, Z.; Remis, R.; Leus, G.
2012-01-01
OFDM suffers from inter-carrier interference (ICI) when the channel is time varying. This article seeks to quantify the amount of interference resulting from wideband OFDM channels, which are assumed to follow the multi-scale multi-lag (MSML) model. The MSML channel model results in full channel
Paper-based inkjet-printed ultra-wideband fractal antennas
Maza, Armando Rodriguez; Cook, Benjamin Stassen; Jabbour, Ghassan E.; Shamim, Atif
2012-01-01
For the first time, paper-based inkjet-printed ultra-wideband (UWB) fractal antennas are presented. Two new designs, a miniaturised UWB monopole, which utilises a fractal matching network and is the smallest reported inkjet-printed UWB printed
Noise-based frequency offset modulation in wideband frequency-selective fading channels
Meijerink, Arjan; Cotton, S.L.; Bentum, Marinus Jan; Scanlon, W.G.
2009-01-01
A frequency offset modulation scheme using wideband noise carriers is considered. The main advantage of such a scheme is that it enables fast receiver synchronization without channel adaptation, while providing robustness to multipath fading and in-band interference. This is important for low-power
Xuyang, CHEN; Fangfang, SHEN; Yanming, LIU; Wei, AI; Xiaoping, LI
2018-06-01
A plasma-based stable, ultra-wideband electromagnetic (EM) wave absorber structure is studied in this paper for stealth applications. The stability is maintained by a multi-layer structure with several plasma layers and dielectric layers distributed alternately. The plasma in each plasma layer is designed to be uniform, whereas it has a discrete nonuniform distribution from the overall view of the structure. The nonuniform distribution of the plasma is the key to obtaining ultra-wideband wave absorption. A discrete Epstein distribution model is put forward to constrain the nonuniform electron density of the plasma layers, by which the wave absorption range is extended to the ultra-wideband. Then, the scattering matrix method (SMM) is employed to analyze the electromagnetic reflection and absorption of the absorber structure. In the simulation, the validation of the proposed structure and model in ultra-wideband EM wave absorption is first illustrated by comparing the nonuniform plasma model with the uniform case. Then, the influence of various parameters on the EM wave reflection of the plasma are simulated and analyzed in detail, verifying the EM wave absorption performance of the absorber. The proposed structure and model are expected to be superior in some realistic applications, such as supersonic aircraft.
Enhanced bit rate-distance product impulse radio ultra-wideband over fiber link
DEFF Research Database (Denmark)
Rodes Lopez, Roberto; Jensen, Jesper Bevensee; Caballero Jambrina, Antonio
2010-01-01
We report on a record distance and bit rate-wireless impulse radio (IR) ultra-wideband (UWB) link with combined transmission over a 20 km long fiber link. We are able to improve the compliance with the regulated frequency emission mask and achieve bit rate-distance products as high as 16 Gbit/s·m....
Range extension and channel capacity increase in impulse-radio ultra-wideband communications
DEFF Research Database (Denmark)
Rodes Lopez, Roberto; Yu, Xianbin; Caballero Jambrina, Antonio
2010-01-01
We theoretically analyze the channel capacity of a 5th-order Gaussian pulse-based ultra-wideband (UWB) system and experimentally demonstrate 2 Gbit/s UWB-over-fiber transmission systems incorporating wireless transmission. Both electrical and photonic UWB pulse generation methods are employed...
Wideband impedance measurements and modeling of DC motors for EMI predictions
Diouf, F.; Leferink, Frank Bernardus Johannes; Duval, Fabrice; Bensetti, Mohamed
2015-01-01
In electromagnetic interference prediction, dc motors are usually modeled as a source and a series impedance. Previous researches only include the impedance of the armature, while neglecting the effect of the motor's rotation. This paper aims at measuring and modeling the wideband impedance of a dc
A wideband high-linearity RF receiver front-end in CMOS
Arkesteijn, V.J.; Klumperink, Eric A.M.; Nauta, Bram
This paper presents a wideband high-linearity RF receiver-front-end, implemented in standard 0.18 μm CMOS technology. The design employs a noise-canceling LNA in combination with two passive mixers, followed by lowpass-filtering and amplification at IF. The achieved bandwidth is >2 GHz, with a noise
Wide-band CMOS low-noise amplifier exploiting thermal noise canceling
Bruccoleri, F.; Klumperink, Eric A.M.; Nauta, Bram
Known elementary wide-band amplifiers suffer from a fundamental tradeoff between noise figure (NF) and source impedance matching, which limits the NF to values typically above 3 dB. Global negative feedback can be used to break this tradeoff, however, at the price of potential instability. In
Wideband CMOS receivers exploiting simultaneous output balancing and noise/distortion canceling
Blaakmeer, S.C.; Klumperink, Eric A.M.; Leenaerts, D.M.W.; Nauta, Bram
2008-01-01
Abstract— This paper deals with the problem of realizing wideband receiver front-ends in downscaled CMOSTechnologies, which are highly wanted for multi-standard radio receivers and cognitive radio applications. Instead of using many narrowband inductor based receivers, we prefer the use of one
Compact Wideband and Low-Profile Antenna Mountable on Large Metallic Surfaces
DEFF Research Database (Denmark)
Zhang, Shuai; Pedersen, Gert F.
2017-01-01
This paper proposes a compact wideband and low-profile antenna mountable on large metallic surfaces. Six rows of coupled microstrip resonators with different lengths are printed on a Teflon block. The lengths of the microstrip resonators in different rows are gradually reduced along the end-fire...
Wideband two-port beam splitter of a binary fused-silica phase grating.
Wang, Bo; Zhou, Changhe; Feng, Jijun; Ru, Huayi; Zheng, Jiangjun
2008-08-01
The usual beam splitter of multilayer-coated film with a wideband spectrum is not easy to achieve. We describe the realization of a wideband transmission two-port beam splitter based on a binary fused-silica phase grating. To achieve high efficiency and equality in the diffracted 0th and -1st orders, the grating profile parameters are optimized using rigorous coupled-wave analysis at a wavelength of 1550 nm. Holographic recording and the inductively coupled plasma dry etching technique are used to fabricate the fused-silica beam splitter grating. The measured efficiency of (45% x 2) = 90% diffracted into the both orders can be obtained with the fabricated grating under Littrow mounting. The physical mechanism of such a wideband two-port beam splitter grating can be well explained by the modal method based on two-beam interference of the modes excited by the incident wave. With the high damage threshold, low coefficient of thermal expansion, and wideband high efficiency, the presented beam splitter etched in fused silica should be a useful optical element for a variety of practical applications.
Wide-band residual phase-noise measurements on 40-GHz monolithic mode-locked lasers
DEFF Research Database (Denmark)
Larsson, David; Hvam, Jørn Märcher
2005-01-01
We have performed wide-band residual phase-noise measurements on semiconductor 40-GHz mode-locked lasers by employing electrical waveguide components for the radio-frequency circuit. The intrinsic timing jitters of lasers with one, two, and three quantum wells (QW) are compared and our design......-QW laser. There is good agreement between the measured results and existing theory....
DEFF Research Database (Denmark)
Grakhova, Elizaveta P.; Rommel, Simon; Jurado-Navas, Antonio
2016-01-01
Ultra-wideband impulse-radio wireless transmission under the stringent conditions and complex shape of the Russian spectral emission mask is experimentally demonstrated for the first time. Transmission of 1Gbit/s and 1.25Gbit/s signals over distances of 6m and 3m is achieved with a BER below 3.8×10-3....
Fast multichannel analog storage system
International Nuclear Information System (INIS)
Freytag, D.R.
1982-11-01
A Multichannel Analog Storage System based on a commercial 32-channel parallel in/serial out (PISO) analog shift register is described. The basic unit is a single width CAMAC module containing 512 analog cells and the associated logic for data storage and subsequent readout. At sampling rates of up to 30 MHz the signals are strobed directly into the PISO. At higher rates signals are strobed into a fast presampling stage and subsequently transferred in block form into an array of PISO's. Sampling rates of 300 MHz have been achieved with the present device and 1000 MHz are possible with improved signal drivers. The system is well suited for simultaneous handling of many signal channels with moderate numbers of samples in each channel. RMS noise over full scale signal has been measured as 1:3000 (approx. = 11 bit). However, nonlinearities in the response and differences in sensitivity of the analog cells require an elaborate calibration system in order to realize 11 bit accuracy for the analog information
Sparse alignment for robust tensor learning.
Lai, Zhihui; Wong, Wai Keung; Xu, Yong; Zhao, Cairong; Sun, Mingming
2014-10-01
Multilinear/tensor extensions of manifold learning based algorithms have been widely used in computer vision and pattern recognition. This paper first provides a systematic analysis of the multilinear extensions for the most popular methods by using alignment techniques, thereby obtaining a general tensor alignment framework. From this framework, it is easy to show that the manifold learning based tensor learning methods are intrinsically different from the alignment techniques. Based on the alignment framework, a robust tensor learning method called sparse tensor alignment (STA) is then proposed for unsupervised tensor feature extraction. Different from the existing tensor learning methods, L1- and L2-norms are introduced to enhance the robustness in the alignment step of the STA. The advantage of the proposed technique is that the difficulty in selecting the size of the local neighborhood can be avoided in the manifold learning based tensor feature extraction algorithms. Although STA is an unsupervised learning method, the sparsity encodes the discriminative information in the alignment step and provides the robustness of STA. Extensive experiments on the well-known image databases as well as action and hand gesture databases by encoding object images as tensors demonstrate that the proposed STA algorithm gives the most competitive performance when compared with the tensor-based unsupervised learning methods.
Regression analysis of sparse asynchronous longitudinal data.
Cao, Hongyuan; Zeng, Donglin; Fine, Jason P
2015-09-01
We consider estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent responses and covariates are observed intermittently within subjects. Unlike with synchronous data, where the response and covariates are observed at the same time point, with asynchronous data, the observation times are mismatched. Simple kernel-weighted estimating equations are proposed for generalized linear models with either time invariant or time-dependent coefficients under smoothness assumptions for the covariate processes which are similar to those for synchronous data. For models with either time invariant or time-dependent coefficients, the estimators are consistent and asymptotically normal but converge at slower rates than those achieved with synchronous data. Simulation studies evidence that the methods perform well with realistic sample sizes and may be superior to a naive application of methods for synchronous data based on an ad hoc last value carried forward approach. The practical utility of the methods is illustrated on data from a study on human immunodeficiency virus.
Duplex scanning using sparse data sequences
DEFF Research Database (Denmark)
Møllenbach, S. K.; Jensen, Jørgen Arendt
2008-01-01
reconstruction of the missing samples possible. The periodic pattern has the length T = M + A samples, where M are for B-mode and A for velocity estimation. The missing samples can now be reconstructed using a filter bank. One filter bank reconstructs one missing sample, so the number of filter banks corresponds...... to M. The number of sub filters in every filter bank is the same as A. Every sub filter contains fractional delay (FD) filter and an interpolation function. Many different sequences can be selected to adapt the B-mode frame rate needed. The drawback of the method is that the maximum velocity detectable......, the fprf and the resolution are 15 MHz, 3.5 kHz, and 12 bit sample (8 kHz and 16 bit for the Carotid artery). The resulting data contains 8000 RF lines with 128 samples at a depth of 45 mm for the vein and 50 mm for Aorta. Sparse sequences are constructed from the full data sequences to have both...
Transformer fault diagnosis using continuous sparse autoencoder.
Wang, Lukun; Zhao, Xiaoying; Pei, Jiangnan; Tang, Gongyou
2016-01-01
This paper proposes a novel continuous sparse autoencoder (CSAE) which can be used in unsupervised feature learning. The CSAE adds Gaussian stochastic unit into activation function to extract features of nonlinear data. In this paper, CSAE is applied to solve the problem of transformer fault recognition. Firstly, based on dissolved gas analysis method, IEC three ratios are calculated by the concentrations of dissolved gases. Then IEC three ratios data is normalized to reduce data singularity and improve training speed. Secondly, deep belief network is established by two layers of CSAE and one layer of back propagation (BP) network. Thirdly, CSAE is adopted to unsupervised training and getting features. Then BP network is used for supervised training and getting transformer fault. Finally, the experimental data from IEC TC 10 dataset aims to illustrate the effectiveness of the presented approach. Comparative experiments clearly show that CSAE can extract features from the original data, and achieve a superior correct differentiation rate on transformer fault diagnosis.
Joint Sparse Recovery With Semisupervised MUSIC
Wen, Zaidao; Hou, Biao; Jiao, Licheng
2017-05-01
Discrete multiple signal classification (MUSIC) with its low computational cost and mild condition requirement becomes a significant noniterative algorithm for joint sparse recovery (JSR). However, it fails in rank defective problem caused by coherent or limited amount of multiple measurement vectors (MMVs). In this letter, we provide a novel sight to address this problem by interpreting JSR as a binary classification problem with respect to atoms. Meanwhile, MUSIC essentially constructs a supervised classifier based on the labeled MMVs so that its performance will heavily depend on the quality and quantity of these training samples. From this viewpoint, we develop a semisupervised MUSIC (SS-MUSIC) in the spirit of machine learning, which declares that the insufficient supervised information in the training samples can be compensated from those unlabeled atoms. Instead of constructing a classifier in a fully supervised manner, we iteratively refine a semisupervised classifier by exploiting the labeled MMVs and some reliable unlabeled atoms simultaneously. Through this way, the required conditions and iterations can be greatly relaxed and reduced. Numerical experimental results demonstrate that SS-MUSIC can achieve much better recovery performances than other MUSIC extended algorithms as well as some typical greedy algorithms for JSR in terms of iterations and recovery probability.
SLAP, Large Sparse Linear System Solution Package
International Nuclear Information System (INIS)
Greenbaum, A.
1987-01-01
1 - Description of program or function: SLAP is a set of routines for solving large sparse systems of linear equations. One need not store the entire matrix - only the nonzero elements and their row and column numbers. Any nonzero structure is acceptable, so the linear system solver need not be modified when the structure of the matrix changes. Auxiliary storage space is acquired and released within the routines themselves by use of the LRLTRAN POINTER statement. 2 - Method of solution: SLAP contains one direct solver, a band matrix factorization and solution routine, BAND, and several interactive solvers. The iterative routines are as follows: JACOBI, Jacobi iteration; GS, Gauss-Seidel Iteration; ILUIR, incomplete LU decomposition with iterative refinement; DSCG and ICCG, diagonal scaling and incomplete Cholesky decomposition with conjugate gradient iteration (for symmetric positive definite matrices only); DSCGN and ILUGGN, diagonal scaling and incomplete LU decomposition with conjugate gradient interaction on the normal equations; DSBCG and ILUBCG, diagonal scaling and incomplete LU decomposition with bi-conjugate gradient iteration; and DSOMN and ILUOMN, diagonal scaling and incomplete LU decomposition with ORTHOMIN iteration
Analog electronics for radiation detection
2016-01-01
Analog Electronics for Radiation Detection showcases the latest advances in readout electronics for particle, or radiation, detectors. Featuring chapters written by international experts in their respective fields, this authoritative text: Defines the main design parameters of front-end circuitry developed in microelectronics technologies Explains the basis for the use of complementary metal oxide semiconductor (CMOS) image sensors for the detection of charged particles and other non-consumer applications Delivers an in-depth review of analog-to-digital converters (ADCs), evaluating the pros and cons of ADCs integrated at the pixel, column, and per-chip levels Describes incremental sigma delta ADCs, time-to-digital converter (TDC) architectures, and digital pulse-processing techniques complementary to analog processing Examines the fundamental parameters and front-end types associated with silicon photomultipliers used for single visible-light photon detection Discusses pixel sensors ...
Natural analogs for Yucca Mountain
International Nuclear Information System (INIS)
Murphy, W.M.
1995-01-01
High-level radioactive waste in the US, spent fuels from commercial reactors and nuclear materials generated by defense activities, will remain potentially hazardous for thousands of years. Demonstrable long-term stability of certain geologic and geochemical systems motivates and sustains the concept that high-level waste can be safely isolated in geologic repositories for requisite periods of time. Each geologic repository is unique in its properties and performance with reguard to isolation of nuclear wastes. Studies of processes analogous to waste-form alteration and radioelement transport in environments analogous to Yucca Mountain are being conducted at two sites, described in this article to illustrate uses of natural analog data: the Nopal I uranium deposit in the Sierra Pena Blanca, Mexico, and the Akrotiri archaeological site on the island of Santorini, Greece
Synthetic Analogs of Phospholipid Metabolites as Antimalarials.
1979-07-01
phosphatidic acid analogs containing ether and phosphonate groups; completely non- hydrolyzable lecithin analogs containing phosphinate and ether groups...substance is a completely non- hydrolyzable analog of lecithin containing ether and phosphonate moieties instead of the normally labile carboxylic and...and also ant-i-phospholipase C (clostridial enzyme) activity. This substance Is a completely non- hydrolyzable analog of lecithin containing ether
Object tracking by occlusion detection via structured sparse learning
Zhang, Tianzhu
2013-06-01
Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object\\'s track. This is the case when significant occlusion occurs. To accommodate for non-sparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that our tracker consistently outperforms the state-of-the-art. © 2013 IEEE.
Manifold regularization for sparse unmixing of hyperspectral images.
Liu, Junmin; Zhang, Chunxia; Zhang, Jiangshe; Li, Huirong; Gao, Yuelin
2016-01-01
Recently, sparse unmixing has been successfully applied to spectral mixture analysis of remotely sensed hyperspectral images. Based on the assumption that the observed image signatures can be expressed in the form of linear combinations of a number of pure spectral signatures known in advance, unmixing of each mixed pixel in the scene is to find an optimal subset of signatures in a very large spectral library, which is cast into the framework of sparse regression. However, traditional sparse regression models, such as collaborative sparse regression , ignore the intrinsic geometric structure in the hyperspectral data. In this paper, we propose a novel model, called manifold regularized collaborative sparse regression , by introducing a manifold regularization to the collaborative sparse regression model. The manifold regularization utilizes a graph Laplacian to incorporate the locally geometrical structure of the hyperspectral data. An algorithm based on alternating direction method of multipliers has been developed for the manifold regularized collaborative sparse regression model. Experimental results on both the simulated and real hyperspectral data sets have demonstrated the effectiveness of our proposed model.
A network of spiking neurons for computing sparse representations in an energy-efficient way.
Hu, Tao; Genkin, Alexander; Chklovskii, Dmitri B
2012-11-01
Computing sparse redundant representations is an important problem in both applied mathematics and neuroscience. In many applications, this problem must be solved in an energy-efficient way. Here, we propose a hybrid distributed algorithm (HDA), which solves this problem on a network of simple nodes communicating by low-bandwidth channels. HDA nodes perform both gradient-descent-like steps on analog internal variables and coordinate-descent-like steps via quantized external variables communicated to each other. Interestingly, the operation is equivalent to a network of integrate-and-fire neurons, suggesting that HDA may serve as a model of neural computation. We show that the numerical performance of HDA is on par with existing algorithms. In the asymptotic regime, the representation error of HDA decays with time, t, as 1/t. HDA is stable against time-varying noise; specifically, the representation error decays as 1/√t for gaussian white noise.
A comprehensive study of sparse codes on abnormality detection
DEFF Research Database (Denmark)
Ren, Huamin; Pan, Hong; Olsen, Søren Ingvor
2017-01-01
Sparse representation has been applied successfully in abnor-mal event detection, in which the baseline is to learn a dic-tionary accompanied by sparse codes. While much empha-sis is put on discriminative dictionary construction, there areno comparative studies of sparse codes regarding abnormal-ity...... detection. We comprehensively study two types of sparsecodes solutions - greedy algorithms and convex L1-norm so-lutions - and their impact on abnormality detection perfor-mance. We also propose our framework of combining sparsecodes with different detection methods. Our comparative ex-periments are carried...
Electromagnetic Formation Flight (EMFF) for Sparse Aperture Arrays
Kwon, Daniel W.; Miller, David W.; Sedwick, Raymond J.
2004-01-01
Traditional methods of actuating spacecraft in sparse aperture arrays use propellant as a reaction mass. For formation flying systems, propellant becomes a critical consumable which can be quickly exhausted while maintaining relative orientation. Additional problems posed by propellant include optical contamination, plume impingement, thermal emission, and vibration excitation. For these missions where control of relative degrees of freedom is important, we consider using a system of electromagnets, in concert with reaction wheels, to replace the consumables. Electromagnetic Formation Flight sparse apertures, powered by solar energy, are designed differently from traditional propulsion systems, which are based on V. This paper investigates the design of sparse apertures both inside and outside the Earth's gravity field.
Sparse Principal Component Analysis in Medical Shape Modeling
DEFF Research Database (Denmark)
Sjöstrand, Karl; Stegmann, Mikkel Bille; Larsen, Rasmus
2006-01-01
Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims...... analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of sufficiently small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA...
National Research Council Canada - National Science Library
Natarajan, V; Chatterjee, D
2004-01-01
This paper presents effects of substrate permittivity and thickness on the performance characteristics like impedance bandwidth, radiation efficiency and gain of a single-layer, wideband, U-slot antenna...
Lé tourneau, Pierre-David; Wu, Ying; Papanicolaou, George; Garnier, Josselin; Darve, Eric
2016-01-01
We present a wideband fast algorithm capable of accurately computing the full numerical solution of the problem of acoustic scattering of waves by multiple finite-sized bodies such as spherical scatterers in three dimensions. By full solution, we
Multichannel analog temperature sensing system
International Nuclear Information System (INIS)
Gribble, R.
1985-08-01
A multichannel system that protects the numerous and costly water-cooled magnet coils on the translation section of the FRX-C/T magnetic fusion experiment is described. The system comprises a thermistor for each coil, a constant current circuit for each thermistor, and a multichannel analog-to-digital converter interfaced to the computer
49205 ANALOGE OG DIGITALE FILTRE
DEFF Research Database (Denmark)
Gaunholt, Hans
1997-01-01
Theese lecture notes treats the fundamental theory and the most commonly used design methods for passive- active and digital filters with special emphasis on microelectronic realizations. The lecture notes covers 75% of the material taught in the course 49205 Analog and Digital Filters...
Drawing Analogies to Deepen Learning
Fava, Michelle
2017-01-01
This article offers examples of how drawing can facilitate thinking skills that promote analogical reasoning to enable deeper learning. The instructional design applies cognitive principles, briefly described here. The workshops were developed iteratively, through feedback from student and teacher participants. Elements of the UK National…
DEFF Research Database (Denmark)
Osadchiy, Alexey Vladimirovich; Yu, Xianbin; Yin, Xiaoli
2010-01-01
In this paper we propose and experimentally demonstrate the principle of coherent label detection for dynamic routing of wavelength division multiplexed impulse radio ultra-wideband signals by using four-tone spectral amplitude coded labels.......In this paper we propose and experimentally demonstrate the principle of coherent label detection for dynamic routing of wavelength division multiplexed impulse radio ultra-wideband signals by using four-tone spectral amplitude coded labels....
Bayesian analogy with relational transformations.
Lu, Hongjing; Chen, Dawn; Holyoak, Keith J
2012-07-01
How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce Bayesian analogy with relational transformations (BART) and apply the model to the task of learning first-order comparative relations (e.g., larger, smaller, fiercer, meeker) from a set of animal pairs. Inputs are coded by vectors of continuous-valued features, based either on human magnitude ratings, normed feature ratings (De Deyne et al., 2008), or outputs of the topics model (Griffiths, Steyvers, & Tenenbaum, 2007). Bootstrapping from empirical priors, the model is able to induce first-order relations represented as probabilistic weight distributions, even when given positive examples only. These learned representations allow classification of novel instantiations of the relations and yield a symbolic distance effect of the sort obtained with both humans and other primates. BART then transforms its learned weight distributions by importance-guided mapping, thereby placing distinct dimensions into correspondence. These transformed representations allow BART to reliably solve 4-term analogies (e.g., larger:smaller::fiercer:meeker), a type of reasoning that is arguably specific to humans. Our results provide a proof-of-concept that structured analogies can be solved with representations induced from unstructured feature vectors by mechanisms that operate in a largely bottom-up fashion. We discuss potential implications for algorithmic and neural models of relational thinking, as well as for the evolution of abstract thought. Copyright 2012 APA, all rights reserved.
Crows spontaneously exhibit analogical reasoning.
Smirnova, Anna; Zorina, Zoya; Obozova, Tanya; Wasserman, Edward
2015-01-19
Analogical reasoning is vital to advanced cognition and behavioral adaptation. Many theorists deem analogical thinking to be uniquely human and to be foundational to categorization, creative problem solving, and scientific discovery. Comparative psychologists have long been interested in the species generality of analogical reasoning, but they initially found it difficult to obtain empirical support for such thinking in nonhuman animals (for pioneering efforts, see [2, 3]). Researchers have since mustered considerable evidence and argument that relational matching-to-sample (RMTS) effectively captures the essence of analogy, in which the relevant logical arguments are presented visually. In RMTS, choice of test pair BB would be correct if the sample pair were AA, whereas choice of test pair EF would be correct if the sample pair were CD. Critically, no items in the correct test pair physically match items in the sample pair, thus demanding that only relational sameness or differentness is available to support accurate choice responding. Initial evidence suggested that only humans and apes can successfully learn RMTS with pairs of sample and test items; however, monkeys have subsequently done so. Here, we report that crows too exhibit relational matching behavior. Even more importantly, crows spontaneously display relational responding without ever having been trained on RMTS; they had only been trained on identity matching-to-sample (IMTS). Such robust and uninstructed relational matching behavior represents the most convincing evidence yet of analogical reasoning in a nonprimate species, as apes alone have spontaneously exhibited RMTS behavior after only IMTS training. Copyright © 2015 Elsevier Ltd. All rights reserved.
High Order Tensor Formulation for Convolutional Sparse Coding
Bibi, Adel Aamer; Ghanem, Bernard
2017-01-01
Convolutional sparse coding (CSC) has gained attention for its successful role as a reconstruction and a classification tool in the computer vision and machine learning community. Current CSC methods can only reconstruct singlefeature 2D images
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
Desmal, Abdulla; Bagci, Hakan
2014-01-01
with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm
Multiple instance learning tracking method with local sparse representation
Xie, Chengjun; Tan, Jieqing; Chen, Peng; Zhang, Jie; Helg, Lei
2013-01-01
as training data for the MIL framework. First, local image patches of a target object are represented as sparse codes with an overcomplete dictionary, where the adaptive representation can be helpful in overcoming partial occlusion in object tracking. Then MIL
Low-rank sparse learning for robust visual tracking
Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra
2012-01-01
In this paper, we propose a new particle-filter based tracking algorithm that exploits the relationship between particles (candidate targets). By representing particles as sparse linear combinations of dictionary templates, this algorithm
Robust visual tracking via multi-task sparse learning
Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra
2012-01-01
In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear combinations of dictionary templates
Sparse Machine Learning Methods for Understanding Large Text Corpora
National Aeronautics and Space Administration — Sparse machine learning has recently emerged as powerful tool to obtain models of high-dimensional data with high degree of interpretability, at low computational...
Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering
Sicat, Ronell Barrera; Kruger, Jens; Moller, Torsten; Hadwiger, Markus
2014-01-01
This paper presents a new multi-resolution volume representation called sparse pdf volumes, which enables consistent multi-resolution volume rendering based on probability density functions (pdfs) of voxel neighborhoods. These pdfs are defined
Sparse Linear Solver for Power System Analysis Using FPGA
National Research Council Canada - National Science Library
Johnson, J. R; Nagvajara, P; Nwankpa, C
2005-01-01
.... Numerical solution to load flow equations are typically computed using Newton-Raphson iteration, and the most time consuming component of the computation is the solution of a sparse linear system...
Support agnostic Bayesian matching pursuit for block sparse signals
Masood, Mudassir
2013-05-01
A fast matching pursuit method using a Bayesian approach is introduced for block-sparse signal recovery. This method performs Bayesian estimates of block-sparse signals even when the distribution of active blocks is non-Gaussian or unknown. It is agnostic to the distribution of active blocks in the signal and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data and no user intervention is required. The method requires a priori knowledge of block partition and utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean square error (MMSE) estimate of the block-sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.
Detection of Pitting in Gears Using a Deep Sparse Autoencoder
Directory of Open Access Journals (Sweden)
Yongzhi Qu
2017-05-01
Full Text Available In this paper; a new method for gear pitting fault detection is presented. The presented method is developed based on a deep sparse autoencoder. The method integrates dictionary learning in sparse coding into a stacked autoencoder network. Sparse coding with dictionary learning is viewed as an adaptive feature extraction method for machinery fault diagnosis. An autoencoder is an unsupervised machine learning technique. A stacked autoencoder network with multiple hidden layers is considered to be a deep learning network. The presented method uses a stacked autoencoder network to perform the dictionary learning in sparse coding and extract features from raw vibration data automatically. These features are then used to perform gear pitting fault detection. The presented method is validated with vibration data collected from gear tests with pitting faults in a gearbox test rig and compared with an existing deep learning-based approach.
Sparse logistic principal components analysis for binary data
Lee, Seokho; Huang, Jianhua Z.; Hu, Jianhua
2010-01-01
with a criterion function motivated from a penalized Bernoulli likelihood. A Majorization-Minimization algorithm is developed to efficiently solve the optimization problem. The effectiveness of the proposed sparse logistic PCA method is illustrated
Sparse reconstruction using distribution agnostic bayesian matching pursuit
Masood, Mudassir
2013-11-01
A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data if not available. The method utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean-square error (MMSE) estimate of the sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.
Occlusion detection via structured sparse learning for robust object tracking
Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra
2014-01-01
occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our
Object tracking by occlusion detection via structured sparse learning
Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra
2013-01-01
occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that our tracker
Sparse Vector Distributions and Recovery from Compressed Sensing
DEFF Research Database (Denmark)
Sturm, Bob L.
It is well known that the performance of sparse vector recovery algorithms from compressive measurements can depend on the distribution underlying the non-zero elements of a sparse vector. However, the extent of these effects has yet to be explored, and formally presented. In this paper, I...... empirically investigate this dependence for seven distributions and fifteen recovery algorithms. The two morals of this work are: 1) any judgement of the recovery performance of one algorithm over that of another must be prefaced by the conditions for which this is observed to be true, including sparse vector...... distributions, and the criterion for exact recovery; and 2) a recovery algorithm must be selected carefully based on what distribution one expects to underlie the sensed sparse signal....
Sparse encoding of automatic visual association in hippocampal networks
DEFF Research Database (Denmark)
Hulme, Oliver J; Skov, Martin; Chadwick, Martin J
2014-01-01
Intelligent action entails exploiting predictions about associations between elements of ones environment. The hippocampus and mediotemporal cortex are endowed with the network topology, physiology, and neurochemistry to automatically and sparsely code sensori-cognitive associations that can...
Efficient collaborative sparse channel estimation in massive MIMO
Masood, Mudassir; Afify, Laila H.; Al-Naffouri, Tareq Y.
2015-01-01
We propose a method for estimation of sparse frequency selective channels within MIMO-OFDM systems. These channels are independently sparse and share a common support. The method estimates the impulse response for each channel observed by the antennas at the receiver. Estimation is performed in a coordinated manner by sharing minimal information among neighboring antennas to achieve results better than many contemporary methods. Simulations demonstrate the superior performance of the proposed method.
Fast convolutional sparse coding using matrix inversion lemma
Czech Academy of Sciences Publication Activity Database
Šorel, Michal; Šroubek, Filip
2016-01-01
Roč. 55, č. 1 (2016), s. 44-51 ISSN 1051-2004 R&D Projects: GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : Convolutional sparse coding * Feature learning * Deconvolution networks * Shift-invariant sparse coding Subject RIV: JD - Computer Applications, Robotics Impact factor: 2.337, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/sorel-0459332.pdf
Discussion of CoSA: Clustering of Sparse Approximations
Energy Technology Data Exchange (ETDEWEB)
Armstrong, Derek Elswick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-03-07
The purpose of this talk is to discuss the possible applications of CoSA (Clustering of Sparse Approximations) to the exploitation of HSI (HyperSpectral Imagery) data. CoSA is presented by Moody et al. in the Journal of Applied Remote Sensing (“Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries”, Vol. 8, 2014) and is based on machine learning techniques.
Efficient collaborative sparse channel estimation in massive MIMO
Masood, Mudassir
2015-08-12
We propose a method for estimation of sparse frequency selective channels within MIMO-OFDM systems. These channels are independently sparse and share a common support. The method estimates the impulse response for each channel observed by the antennas at the receiver. Estimation is performed in a coordinated manner by sharing minimal information among neighboring antennas to achieve results better than many contemporary methods. Simulations demonstrate the superior performance of the proposed method.
A flexible framework for sparse simultaneous component based data integration
Directory of Open Access Journals (Sweden)
Van Deun Katrijn
2011-11-01
Full Text Available Abstract 1 Background High throughput data are complex and methods that reveal structure underlying the data are most useful. Principal component analysis, frequently implemented as a singular value decomposition, is a popular technique in this respect. Nowadays often the challenge is to reveal structure in several sources of information (e.g., transcriptomics, proteomics that are available for the same biological entities under study. Simultaneous component methods are most promising in this respect. However, the interpretation of the principal and simultaneous components is often daunting because contributions of each of the biomolecules (transcripts, proteins have to be taken into account. 2 Results We propose a sparse simultaneous component method that makes many of the parameters redundant by shrinking them to zero. It includes principal component analysis, sparse principal component analysis, and ordinary simultaneous component analysis as special cases. Several penalties can be tuned that account in different ways for the block structure present in the integrated data. This yields known sparse approaches as the lasso, the ridge penalty, the elastic net, the group lasso, sparse group lasso, and elitist lasso. In addition, the algorithmic results can be easily transposed to the context of regression. Metabolomics data obtained with two measurement platforms for the same set of Escherichia coli samples are used to illustrate the proposed methodology and the properties of different penalties with respect to sparseness across and within data blocks. 3 Conclusion Sparse simultaneous component analysis is a useful method for data integration: First, simultaneous analyses of multiple blocks offer advantages over sequential and separate analyses and second, interpretation of the results is highly facilitated by their sparseness. The approach offered is flexible and allows to take the block structure in different ways into account. As such
A flexible framework for sparse simultaneous component based data integration.
Van Deun, Katrijn; Wilderjans, Tom F; van den Berg, Robert A; Antoniadis, Anestis; Van Mechelen, Iven
2011-11-15
High throughput data are complex and methods that reveal structure underlying the data are most useful. Principal component analysis, frequently implemented as a singular value decomposition, is a popular technique in this respect. Nowadays often the challenge is to reveal structure in several sources of information (e.g., transcriptomics, proteomics) that are available for the same biological entities under study. Simultaneous component methods are most promising in this respect. However, the interpretation of the principal and simultaneous components is often daunting because contributions of each of the biomolecules (transcripts, proteins) have to be taken into account. We propose a sparse simultaneous component method that makes many of the parameters redundant by shrinking them to zero. It includes principal component analysis, sparse principal component analysis, and ordinary simultaneous component analysis as special cases. Several penalties can be tuned that account in different ways for the block structure present in the integrated data. This yields known sparse approaches as the lasso, the ridge penalty, the elastic net, the group lasso, sparse group lasso, and elitist lasso. In addition, the algorithmic results can be easily transposed to the context of regression. Metabolomics data obtained with two measurement platforms for the same set of Escherichia coli samples are used to illustrate the proposed methodology and the properties of different penalties with respect to sparseness across and within data blocks. Sparse simultaneous component analysis is a useful method for data integration: First, simultaneous analyses of multiple blocks offer advantages over sequential and separate analyses and second, interpretation of the results is highly facilitated by their sparseness. The approach offered is flexible and allows to take the block structure in different ways into account. As such, structures can be found that are exclusively tied to one data platform
In-Storage Embedded Accelerator for Sparse Pattern Processing
Jun, Sang-Woo; Nguyen, Huy T.; Gadepally, Vijay N.; Arvind
2016-01-01
We present a novel architecture for sparse pattern processing, using flash storage with embedded accelerators. Sparse pattern processing on large data sets is the essence of applications such as document search, natural language processing, bioinformatics, subgraph matching, machine learning, and graph processing. One slice of our prototype accelerator is capable of handling up to 1TB of data, and experiments show that it can outperform C/C++ software solutions on a 16-core system at a fracti...
Process Knowledge Discovery Using Sparse Principal Component Analysis
DEFF Research Database (Denmark)
Gao, Huihui; Gajjar, Shriram; Kulahci, Murat
2016-01-01
As the goals of ensuring process safety and energy efficiency become ever more challenging, engineers increasingly rely on data collected from such processes for informed decision making. During recent decades, extracting and interpreting valuable process information from large historical data sets...... SPCA approach that helps uncover the underlying process knowledge regarding variable relations. This approach systematically determines the optimal sparse loadings for each sparse PC while improving interpretability and minimizing information loss. The salient features of the proposed approach...
Occlusion detection via structured sparse learning for robust object tracking
Zhang, Tianzhu
2014-01-01
Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios, these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object’s track. This is the case when significant occlusion occurs. To accommodate for nonsparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our proposed tracker consistently outperforms the state-of-the-art trackers.
Exhaustive Search for Sparse Variable Selection in Linear Regression
Igarashi, Yasuhiko; Takenaka, Hikaru; Nakanishi-Ohno, Yoshinori; Uemura, Makoto; Ikeda, Shiro; Okada, Masato
2018-04-01
We propose a K-sparse exhaustive search (ES-K) method and a K-sparse approximate exhaustive search method (AES-K) for selecting variables in linear regression. With these methods, K-sparse combinations of variables are tested exhaustively assuming that the optimal combination of explanatory variables is K-sparse. By collecting the results of exhaustively computing ES-K, various approximate methods for selecting sparse variables can be summarized as density of states. With this density of states, we can compare different methods for selecting sparse variables such as relaxation and sampling. For large problems where the combinatorial explosion of explanatory variables is crucial, the AES-K method enables density of states to be effectively reconstructed by using the replica-exchange Monte Carlo method and the multiple histogram method. Applying the ES-K and AES-K methods to type Ia supernova data, we confirmed the conventional understanding in astronomy when an appropriate K is given beforehand. However, we found the difficulty to determine K from the data. Using virtual measurement and analysis, we argue that this is caused by data shortage.
Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle
Directory of Open Access Journals (Sweden)
Xiangwei Xing
2014-01-01
Full Text Available As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC has attracted much attention in synthetic aperture radar (SAR automatic target recognition (ATR recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA, in which the correlation between the vehicle’s aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle’s aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.
Structure-aware Local Sparse Coding for Visual Tracking
Qi, Yuankai
2018-01-24
Sparse coding has been applied to visual tracking and related vision problems with demonstrated success in recent years. Existing tracking methods based on local sparse coding sample patches from a target candidate and sparsely encode these using a dictionary consisting of patches sampled from target template images. The discriminative strength of existing methods based on local sparse coding is limited as spatial structure constraints among the template patches are not exploited. To address this problem, we propose a structure-aware local sparse coding algorithm which encodes a target candidate using templates with both global and local sparsity constraints. For robust tracking, we show local regions of a candidate region should be encoded only with the corresponding local regions of the target templates that are the most similar from the global view. Thus, a more precise and discriminative sparse representation is obtained to account for appearance changes. To alleviate the issues with tracking drifts, we design an effective template update scheme. Extensive experiments on challenging image sequences demonstrate the effectiveness of the proposed algorithm against numerous stateof- the-art methods.
Vector sparse representation of color image using quaternion matrix analysis.
Xu, Yi; Yu, Licheng; Xu, Hongteng; Zhang, Hao; Nguyen, Truong
2015-04-01
Traditional sparse image models treat color image pixel as a scalar, which represents color channels separately or concatenate color channels as a monochrome image. In this paper, we propose a vector sparse representation model for color images using quaternion matrix analysis. As a new tool for color image representation, its potential applications in several image-processing tasks are presented, including color image reconstruction, denoising, inpainting, and super-resolution. The proposed model represents the color image as a quaternion matrix, where a quaternion-based dictionary learning algorithm is presented using the K-quaternion singular value decomposition (QSVD) (generalized K-means clustering for QSVD) method. It conducts the sparse basis selection in quaternion space, which uniformly transforms the channel images to an orthogonal color space. In this new color space, it is significant that the inherent color structures can be completely preserved during vector reconstruction. Moreover, the proposed sparse model is more efficient comparing with the current sparse models for image restoration tasks due to lower redundancy between the atoms of different color channels. The experimental results demonstrate that the proposed sparse image model avoids the hue bias issue successfully and shows its potential as a general and powerful tool in color image analysis and processing domain.
Sparse Reconstruction Schemes for Nonlinear Electromagnetic Imaging
Desmal, Abdulla
2016-03-01
synthetically generated or actually measured scattered fields, show that the images recovered by these sparsity-regularized methods are sharper and more accurate than those produced by existing methods. The methods developed in this work have potential application areas ranging from oil/gas reservoir engineering to biological imaging where sparse domains naturally exist.
Analog circuit design art, science and personalities
Williams, Jim
1991-01-01
This book is far more than just another tutorial or reference guide - it's a tour through the world of analog design, combining theory and applications with the philosophies behind the design process. Readers will learn how leading analog circuit designers approach problems and how they think about solutions to those problems. They'll also learn about the `analog way' - a broad, flexible method of thinking about analog design tasks.A comprehensive and useful guide to analog theory and applications. Covers visualizing the operation of analog circuits. Looks at how to rap
Sana, Furrukh
2016-01-01
precision technique for the monitoring of human respiratory movements by exploiting the sparsity of wireless ultra-wideband signals. The proposed technique provides a novel methodology of overcoming the Nyquist sampling constraint and enables robust
Pelgrom, Marcel
2017-01-01
This textbook is appropriate for use in graduate-level curricula in analog-to-digital conversion, as well as for practicing engineers in need of a state-of-the-art reference on data converters. It discusses various analog-to-digital conversion principles, including sampling, quantization, reference generation, nyquist architectures and sigma-delta modulation. This book presents an overview of the state of the art in this field and focuses on issues of optimizing accuracy and speed, while reducing the power level. This new, third edition emphasizes novel calibration concepts, the specific requirements of new systems, the consequences of 22-nm technology and the need for a more statistical approach to accuracy. Pedagogical enhancements to this edition include additional, new exercises, solved examples to introduce all key, new concepts and warnings, remarks and hints, from a practitioner’s perspective, wherever appropriate. Considerable background information and practical tips, from designing a PCB, to lay-o...
High Performance Wideband CMOS CCI and its Application in Inductance Simulator Design
Directory of Open Access Journals (Sweden)
ARSLAN, E.
2012-08-01
Full Text Available In this paper, a new, differential pair based, low-voltage, high performance and wideband CMOS first generation current conveyor (CCI is proposed. The proposed CCI has high voltage swings on ports X and Y and very low equivalent impedance on port X due to super source follower configuration. It also has high voltage swings (close to supply voltages on input and output ports and wideband current and voltage transfer ratios. Furthermore, two novel grounded inductance simulator circuits are proposed as application examples. Using HSpice, it is shown that the simulation results of the proposed CCI and also of the presented inductance simulators are in very good agreement with the expected ones.
Inkjet Printing of Paper-Based Wideband and High Gain Antennas
Cook, Benjamin
2011-12-07
This thesis represents a major contribution to wideband and high gain inkjet-printed antennas on paper. This work includes the complete characterization of the inkjet printing process for passive microwave devices on paper substrate as well as several ultra-wideband and high gain antenna designs. The characterization work includes the electrical characterization of the permittivity and loss tangent for paper substrate through 10 GHz, ink conductivity data for variable sintering conditions, and minimum feature sizes obtainable by today’s current inkjet processes for metallic nanoparticles. For the first time ever, inkjet-printed antennas are demonstrated that operate over the entire UWB band and demonstrate gains up to 8dB. This work also presents the first fractal-based inkjet-printed antennas with enhanced bandwidth and reduced production costs, and a novel slow wave log periodic dipole array which shows minimizations of 20% in width over conventional log periodic antennas.
Generation of flat wideband chaos with suppressed time delay signature by using optical time lens.
Jiang, Ning; Wang, Chao; Xue, Chenpeng; Li, Guilan; Lin, Shuqing; Qiu, Kun
2017-06-26
We propose a flat wideband chaos generation scheme that shows excellent time delay signature suppression effect, by injecting the chaotic output of general external cavity semiconductor laser into an optical time lens module composed of a phase modulator and two dispersive units. The numerical results demonstrate that by properly setting the parameters of the driving signal of phase modulator and the accumulated dispersion of dispersive units, the relaxation oscillation in chaos can be eliminated, wideband chaos generation with an efficient bandwidth up to several tens of GHz can be achieved, and the RF spectrum of generated chaotic signal is nearly as flat as uniform distribution. Moreover, the periodicity of chaos induced by the external cavity modes can be simultaneously destructed by the optical time lens module, based on this the time delay signature can be completely suppressed.
The Large Office Environment - Measurement and Modeling of the Wideband Radio Channel
DEFF Research Database (Denmark)
Andersen, Jørgen Bach; Nielsen, Jesper Ødum; Bauch, Gerhard
2006-01-01
In a future 4G or WLAN wideband application we can imagine multiple users in a large office environment con-sisting of a single room with partitions. Up to now, indoor radio channel measurement and modelling has mainly concentrated on scenarios with several office rooms and corridors. We present...... here measurements at 5.8GHz for 100 MHz bandwidth and a novel modelling approach for the wideband radio channel in a large office room envi-ronment. An acoustic like reverberation theory is pro-posed that allows to specify a tapped delay line model just from the room dimensions and an average...... calculated from the measurements. The pro-posed model can likely also be applied to indoor hot spot scenarios....
Coding/modulation trade-offs for Shuttle wideband data links
Batson, B. H.; Huth, G. K.; Trumpis, B. D.
1974-01-01
This paper describes various modulation and coding schemes which are potentially applicable to the Shuttle wideband data relay communications link. This link will be capable of accommodating up to 50 Mbps of scientific data and will be subject to a power constraint which forces the use of channel coding. Although convolutionally encoded coherent binary PSK is the tentative signal design choice for the wideband data relay link, FM techniques are of interest because of the associated hardware simplicity and because an FM system is already planned to be available for transmission of television via relay satellite to the ground. Binary and M-ary FSK are considered as candidate modulation techniques, and both coherent and noncoherent ground station detection schemes are examined. The potential use of convolutional coding is considered in conjunction with each of the candidate modulation techniques.
35 Gb/s Ultra-wideband Technology for Advanced Communications
DEFF Research Database (Denmark)
Puerta Ramírez, Rafael; Vegas Olmos, Juan José; Tafur Monroy, Idelfonso
be applied, evolving from classic spectral inefficient pulsebased systems to more advanced and flexible modulation schemes. Ultra-wideband technology is suitable for low-power high-speed wireless communication systems over short distances, and is an appealing alternative for next generation networks ranging......The fast development of electronics and portable devices, intended mainly for multimedia applications, is increasing exponentially the data traffic demands per user. To cope with these new data demands in limited bandwidth systems, new technologies must be explored and new transmission schemes must...... from high-speed wireless personal area networks, to the internet of things applications. Its popularity stems from the fact that they can be used as an overlay to existing systems, without interference, operating in parallel to existing wireless systems, which perceive ultra-wideband emissions...
Micro-Doppler Ambiguity Resolution for Wideband Terahertz Radar Using Intra-Pulse Interference.
Yang, Qi; Qin, Yuliang; Deng, Bin; Wang, Hongqiang; You, Peng
2017-04-29
Micro-Doppler, induced by micro-motion of targets, is an important characteristic of target recognition once extracted via parameter estimation methods. However, micro-Doppler is usually too significant to result in ambiguity in the terahertz band because of its relatively high carrier frequency. Thus, a micro-Doppler ambiguity resolution method for wideband terahertz radar using intra-pulse interference is proposed in this paper. The micro-Doppler can be reduced several dozen times its true value to avoid ambiguity through intra-pulse interference processing. The effectiveness of this method is proved by experiments based on a 0.22 THz wideband radar system, and its high estimation precision and excellent noise immunity are verified by Monte Carlo simulation.
Multiband and wideband monopole antenna for GSM900 and other wireless applications
Abutarboush, Hattan; Nasif, H.; Nilavalan, Rajagopal; Cheung, Sing Wai
2012-01-01
In this letter, the design of a compact monopole antenna for multiband and wideband operations is proposed. The antenna has three distinct frequency bands, centered at 0.94, 2.7, and 4.75 GHz. The antenna has a compact size of only 30×40×1.57 mm$ 3 including the ground plane. The multiband and wideband operations are achieved by using an E-shaped slot on the ground plane. The design procedure is also discussed. The frequency bands can be independently controlled by using the parameters of the E-slot. The impedance bandwidth, current distributions, radiation patterns, gain, and efficiency of the antenna are studied by computer simulation and measurements. © 2011 IEEE.
10th and 11th conference on Ultra-Wideband Short-Pulse Electromagnetics
Mokole, Eric; UWB SP 10; UWB SP 11
2014-01-01
This book presents contributions of deep technical content and high scientific quality in the areas of electromagnetic theory, scattering, UWB antennas, UWB systems, ground penetrating radar (GPR), UWB communications, pulsed-power generation, time-domain computational electromagnetics, UWB compatibility, target detection and discrimination, propagation through dispersive media, and wavelet and multi-resolution techniques. Ultra-wideband (UWB), short-pulse (SP) electromagnetics are now being used for an increasingly wide variety of applications, including collision avoidance radar, concealed object detection, and communications. Notable progress in UWB and SP technologies has been achieved by investigations of their theoretical bases and improvements in solid-state manufacturing, computers, and digitizers. UWB radar systems are also being used for mine clearing, oil pipeline inspections, archeology, geology, and electronic effects testing. Like previous books in this series, Ultra-Wideband Short-Pulse Electrom...
Spatial Dynamic Wideband Modeling of the MIMO Satellite-to-Earth Channel
Directory of Open Access Journals (Sweden)
Andreas Lehner
2014-01-01
response (CIR time series depending on the movement profile of a land mobile terminal is presented in this paper. Based on high precise wideband measurements in L-band the model reproduces the correlated shadowing and multipath conditions in rich detail. The model includes time and space variant echo signals appearing and disappearing in dependence on the receive antenna position and movement, and the actual azimuths and elevations to the various signal sources. Attenuation and path delays relative to the hypothetical line of sight (LOS ensure usability for ranging purposes. Parameters for car and pedestrian applications in urban and suburban environments are provided. The channel characteristics are determined independently of the transmitted signal. Therefore the usability, for example, for GPS and GALILEO, as well as wideband communication services from hovering platforms, is given.
Wideband radar cross section reduction using two-dimensional phase gradient metasurfaces
Energy Technology Data Exchange (ETDEWEB)
Li, Yongfeng; Qu, Shaobo; Wang, Jiafu; Chen, Hongya [College of Science, Air Force Engineering University, Xi' an, Shaanxi 710051 (China); Zhang, Jieqiu [College of Science, Air Force Engineering University, Xi' an, Shaanxi 710051 (China); Electronic Materials Research Laboratory, Key Laboratory of Ministry of Education, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Xu, Zhuo [Electronic Materials Research Laboratory, Key Laboratory of Ministry of Education, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Zhang, Anxue [School of Electronics and Information Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China)
2014-06-02
Phase gradient metasurface (PGMs) are artificial surfaces that can provide pre-defined in-plane wave-vectors to manipulate the directions of refracted/reflected waves. In this Letter, we propose to achieve wideband radar cross section (RCS) reduction using two-dimensional (2D) PGMs. A 2D PGM was designed using a square combination of 49 split-ring sub-unit cells. The PGM can provide additional wave-vectors along the two in-plane directions simultaneously, leading to either surface wave conversion, deflected reflection, or diffuse reflection. Both the simulation and experiment results verified the wide-band, polarization-independent, high-efficiency RCS reduction induced by the 2D PGM.
Ultra-wideband wireless receiver front-end for high-speed indoor applications
Directory of Open Access Journals (Sweden)
Zhe-Yang Huang
2014-12-01
Full Text Available Low-noise, ultra-wideband (UWB wireless receiver front-end circuits were presented in this study. A two-stage common-source low-noise amplifier with wideband input impedance matching network, an active-balun and a double-balanced down-conversion mixer were adopted in the UWB wireless receiver front-end. The proposed wireless receiver front-end circuits were implemented in 0.18 μm radio-frequency-CMOS process. The maximum down-conversion power gain of the front-end is 25.8 dB; minimum single-sideband noise figure of the front-end is 4.9 dB over complete UWB band ranging from 3.1 to 10.6 GHz. Power consumption including buffers is 39.2 mW.
Comparison of fundamental and wideband harmonic contrast imaging of liver tumors.
Forsberg, F; Liu, J B; Chiou, H J; Rawool, N M; Parker, L; Goldberg, B B
2000-03-01
Wideband harmonic imaging (with phase inversion for improved tissue suppression) was compared to fundamental imaging in vivo. Four woodchucks with naturally occurring liver tumors were injected with Imagent (Alliance Pharmaceutical Corp., San Diego, CA). Randomized combinations of dose (0.05, 0.2 and 0.4 ml/kg) and acoustic output power (AO; 5, 25 and 63% or MI Siemens Medical Systems, Issaquah, WA). Tumor vascularity, conspicuity and contrast enhancement were rated by three independent observers. Imagent produced marked tumor enhancement and improved depiction of neovascularity at all dosages and AO settings in both modes. Tumor vascularity and enhancement correlated with mode, dose and AO (P < 0.002). Fundamental imaging produced more enhancement (P < 0.05), but tumor vascularity and conspicuity were best appreciated in harmonic mode (P < 0.05). Under the conditions studied here, the best approach was wideband harmonic imaging with 0.2 ml/kg of Imagent at an AO of 25%.
7th conference on ultra-wideband, short-pulse electromagnetics
Schenk, Uwe; Nitsch, Daniel; Sabath, Frank; Ultra-Wideband, Short-Pulse Electromagnetics 7; UWBSP7
2007-01-01
Ultra-wideband (UWB), short-pulse (SP) electromagnetics are now being used for an increasingly wide variety of applications, including collision avoidance radar, concealed object detection, and communications. Notable progress in UWB and SP technologies has been achieved by investigations of their theoretical bases and improvements in solid-state manufacturing, computers, and digitizers. UWB radar systems are also being used for mine clearing, oil pipeline inspections, archeology, geology, and electronic effects testing. Ultra-Wideband Short-Pulse Electromagnetics 7 presents selected papers of deep technical content and high scientific quality from the UWB-SP7 Conference, including wide-ranging contributions on electromagnetic theory, scattering, UWB antennas, UWB systems, ground penetrating radar (GPR), UWB communications, pulsed-power generation, time-domain computational electromagnetics, UWB compatibility, target detection and discrimination, propagation through dispersive media, and wavelet and multi-res...
A low-noise, wideband, integrated CMOS transimpedance preamplifier for photodiode applications
International Nuclear Information System (INIS)
Binkley, D.M.; Paulus, M.J.; Casey, M.E.; Rochelle, J.M.
1992-01-01
In this paper, a low-noise, wideband, integrated CMOS transimpedance preamplifier is presented for silicon avalanche photodiode (APD) applications. The preamplifier, fabricated in a standard 2μ CMOS technology, features a transimpedance gain of 45 kΩ, a risetime of 22 ns, a series noise of 1.6nV/Hz 1/2 , and a wideband equivalent input-noise current of 12 nA for a source capacitance of 12 pF. The measured 22 Na timing resolution of 9.2-ns FWHM and energy resolution of 22.4% FWHM for the RCA C30994 BGO/APD detector module coupled to the preamplifier is comparable to the performance reported using charge-sensitive preamplifiers. This illustrates that transimpedance preamplifiers should be considered for APD applications, especially where APD noise current dominates noise from feedback resistors in the 1--kΩ to 50-kΩ range
Design of a Compact Wideband Antenna Array for Microwave Imaging Applications
Directory of Open Access Journals (Sweden)
J. Puskely
2013-12-01
Full Text Available In the paper, wideband antenna arrays aimed at microwave imaging applications and SAR applications operating at Ka band were designed. The antenna array feeding network is realized by a low-loss SIW technology. Moreover, we have replaced the large feed network comprised of various T and Y junctions by a simple broadband network of compact size to more reduce losses in the substrate integrated waveguide and also save space on the PCB. The designed power 8-way divider is complemented by a wideband substrate integrated waveguide to a grounded coplanar waveguide transition and directly connected to the antenna elements. The measured results of antenna array are consistent with our simulation. Obtained results of the developed array demonstrated improvement compared to previously developed binary feed networks with microstrip or SIW splitters.
Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide
DEFF Research Database (Denmark)
Xiao, Binggang; Li, Sheng-Hua; Xiao, Sanshui
2016-01-01
Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN and satel...... and satellite communication signals. Due to planar structures proposed here, it is easy to integrate in the microwave integrated systems, which can play an important role in the microwave communication circuit and system.......Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN...
Dual-polarization, wideband microstrip antenna array for airborne C-band SAR
DEFF Research Database (Denmark)
Granholm, Johan; Skou, Niels
2000-01-01
The paper describes the development of a C-band, dual linear polarization wideband antenna array, for use in the next-generation of the Danish airborne polarimetric synthetic aperture radar (SAR) system. The array is made of probe-fed, stacked microstrip patches. The design and performance of the...... of the basic stacked patch element, operating from 4.9 GHz to 5.7 GHz, and a 2×2 element test array of these, are described.......The paper describes the development of a C-band, dual linear polarization wideband antenna array, for use in the next-generation of the Danish airborne polarimetric synthetic aperture radar (SAR) system. The array is made of probe-fed, stacked microstrip patches. The design and performance...
Wideband radar cross section reduction using two-dimensional phase gradient metasurfaces
International Nuclear Information System (INIS)
Li, Yongfeng; Qu, Shaobo; Wang, Jiafu; Chen, Hongya; Zhang, Jieqiu; Xu, Zhuo; Zhang, Anxue
2014-01-01
Phase gradient metasurface (PGMs) are artificial surfaces that can provide pre-defined in-plane wave-vectors to manipulate the directions of refracted/reflected waves. In this Letter, we propose to achieve wideband radar cross section (RCS) reduction using two-dimensional (2D) PGMs. A 2D PGM was designed using a square combination of 49 split-ring sub-unit cells. The PGM can provide additional wave-vectors along the two in-plane directions simultaneously, leading to either surface wave conversion, deflected reflection, or diffuse reflection. Both the simulation and experiment results verified the wide-band, polarization-independent, high-efficiency RCS reduction induced by the 2D PGM.
Effects of Compound K-Distributed Sea Clutter on Angle Measurement of Wideband Monopulse Radar
Directory of Open Access Journals (Sweden)
Hong Zhu
2017-01-01
Full Text Available The effects of compound K-distributed sea clutter on angle measurement of wideband monopulse radar are investigated in this paper. We apply the conditional probability density function (pdf of monopulse ratio (MR error to analyze these effects. Based on the angle measurement procedure of the wideband monopulse radar, this conditional pdf is first deduced in detail for the case of compound K-distributed sea clutter plus noise. Herein, the spatial correlation of the texture components for each channel clutter and the correlation of the texture components between the sum and difference channel clutters are considered, and two extreme situations for each of them are tackled. Referring to the measured sea clutter data, angle measurement performances in various K-distributed sea clutter plus noise circumstances are simulated, and the effects of compound K-distributed sea clutter on angle measurement are discussed.
Wideband laser locking to an atomic reference with modulation transfer spectroscopy.
Negnevitsky, V; Turner, L D
2013-02-11
We demonstrate that conventional modulated spectroscopy apparatus, used for laser frequency stabilization in many atomic physics laboratories, can be enhanced to provide a wideband lock delivering deep suppression of frequency noise across the acoustic range. Using an acousto-optic modulator driven with an agile oscillator, we show that wideband frequency modulation of the pump laser in modulation transfer spectroscopy produces the unique single lock-point spectrum previously demonstrated with electro-optic phase modulation. We achieve a laser lock with 100 kHz feedback bandwidth, limited by our laser control electronics. This bandwidth is sufficient to reduce frequency noise by 30 dB across the acoustic range and narrows the imputed linewidth by a factor of five.
Analogies between antiferromagnets and antiferroelectrics
International Nuclear Information System (INIS)
Enz, C.P.; Matthias, B.T.
1980-01-01
Ferro- and antiferromagnetism in the Laves phase TiBesub(2-x) Cusub(x) occurs for 0.1 4 H 2 PO 4 and its solid solutions with TlH 2 PO 4 and with the ferroelectric KH 2 PO 4 are discussed as function of deuteration and of pressure. Another analogy as function of pressure is established with the antiferroelectric perovskite PbZrO 3 . (author)
Novel phosphanucleoside analogs of dideoxynucleosides
Czech Academy of Sciences Publication Activity Database
Páv, Ondřej; Buděšínský, Miloš; Rosenberg, Ivan
2017-01-01
Roč. 73, č. 34 (2017), s. 5220-5228 ISSN 0040-4020 R&D Projects: GA ČR(CZ) GA17-12703S; GA ČR GA13-26526S; GA MZd NV15-31604A Institutional support: RVO:61388963 Keywords : phosphanucleoside * nucleoside analog * ring-closing metathesis * stereoselective hydroboration * chiral resolution Subject RIV: CC - Organic Chemistry OBOR OECD: Organic chemistry Impact factor: 2.651, year: 2016
Electrostatic analogy for symmetron gravity
Ogden, Lillie; Brown, Katherine; Mathur, Harsh; Rovelli, Kevin
2017-12-01
The symmetron model is a scalar-tensor theory of gravity with a screening mechanism that suppresses the effect of the symmetron field at high densities characteristic of the Solar System and laboratory scales but allows it to act with gravitational strength at low density on the cosmological scale. We elucidate the screening mechanism by showing that in the quasistatic Newtonian limit there are precise analogies between symmetron gravity and electrostatics for both strong and weak screening. For strong screening we find that large dense bodies behave in a manner analogous to perfect conductors in electrostatics. Based on this analogy we find that the symmetron field exhibits a lightning rod effect wherein the field gradients are enhanced near the ends of pointed or elongated objects. An ellipsoid placed in a uniform symmetron gradient is shown to experience a torque. By symmetry there is no gravitational torque in this case. Hence this effect unmasks the symmetron and might serve as the basis for future laboratory experiments. The symmetron force between a point mass and a large dense body includes a component corresponding to the interaction of the point mass with its image in the larger body. None of these effects have counterparts in the Newtonian limit of Einstein gravity. We discuss the similarities between symmetron gravity and the chameleon model as well as the differences between the two.
Spectrally-Precoded OFDM for 5G Wideband Operation in Fragmented sub-6GHz Spectrum
Pitaval, Renaud-Alexandre; Popović, Branislav M.; Mohamad, Medhat; Nilsson, Rickard; van de Beek, Jaap
2016-01-01
We consider spectrally-precoded OFDM waveforms for 5G wideband transmission in sub-6GHz band. In this densely packed spectrum, a low out-of-band (OOB) waveform is a critical 5G component to achieve the promised high spectral efficiency. By precoding data symbols before OFDM modulation, it is possible to achieve extremely low out-of-band emission with very sharp spectrum transition enabling an efficient and flexible usage of frequency resources. Spectrally-precoded OFDM shows promising results...
High-speed ultra-wideband wireless signals over fiber systems: photonic generation and DSP detection
DEFF Research Database (Denmark)
Yu, Xianbin; Gibbon, Timothy Braidwood; Tafur Monroy, Idelfonso
2009-01-01
We firstly review the efforts in the literature on ultra-wideband (UWB)-over-fiber systems. Secondly, we present experimental results on photonic generation of high-speed UWB signals by both direct modulation and external optical injecting an uncooled semiconductor laser. Furthermore, we introduce...... the use of digital signal processing (DSP) technology to receive the generated UWB signal at 781.25 Mbit/s. Error-free transmission is achieved....
Spatial Dynamic Wideband Modeling of the MIMO Satellite-to-Earth Channel
Lehner, Andreas; Steingass, Alexander
2014-01-01
A novel MIMO (multiple input multiple output) satellite channel model that allows the generation of associated channel impulse response (CIR) time series depending on the movement profile of a land mobile terminal is presented in this paper. Based on high precise wideband measurements in L-band the model reproduces the correlated shadowing and multipath conditions in rich detail. The model includes time and space variant echo signals appearing and disappearing in dependence on the receive ...
A Wideband and Compact Circularly-Polarized Rectenna for Low Power Application
Okba , Abderrahim; Takacs , Alexandru; Aubert , Hervé; Bellion , Anthony; Grenana , D
2017-01-01
International audience; This paper presents a wideband and compact circularly polarized rectenna composed by an Archimedean spiral antenna that covers the S and C frequency bands and a silicon Schottky diode. This rectenna (rectifier + antenna) is used for electromagnetic energy harvesting over a wide frequency band, in order to power autonomous wireless sensors used for satellite health monitoring. For low incident power densities (around 14 µW/cm²) the measured efficiency of at least 19% be...
Energy Technology Data Exchange (ETDEWEB)
Guryev, I. V., E-mail: guryev@ieee.org; Sukhoivanov, I. A., E-mail: guryev@ieee.org; Andrade Lucio, J. A., E-mail: guryev@ieee.org; Manzano, O. Ibarra, E-mail: guryev@ieee.org; Rodriguez, E. Vargaz, E-mail: guryev@ieee.org; Gonzales, D. Claudio, E-mail: guryev@ieee.org; Chavez, R. I. Mata, E-mail: guryev@ieee.org; Gurieva, N. S., E-mail: guryev@ieee.org [University of Guanajuato, Engineering division (Mexico)
2014-05-15
In our work, we investigated the wideband optical filter on the basis of nonlinear photonic crystal. The all-optical flip-flop using ultra-short pulses with duration lower than 200 fs is obtained in such filters. Here we pay special attention to the stability problem of the nonlinear element. To investigate this problem, the temporal response demonstrating the flip-flop have been computed within the certain range of the wavelengths as well as at different input power.
Wide-band CMOS low-noise amplifier exploiting thermal noise canceling
Bruccoleri, F.; Klumperink, Eric A.M.; Nauta, Bram
2004-01-01
Known elementary wide-band amplifiers suffer from a fundamental tradeoff between noise figure (NF) and source impedance matching, which limits the NF to values typically above 3 dB. Global negative feedback can be used to break this tradeoff, however, at the price of potential instability. In contrast, this paper presents a feedforward noise-canceling technique, which allows for simultaneous noise and impedance matching, while canceling the noise and distortion contributions of the matching d...
Semi-blind identification of wideband MIMO channels via stochastic sampling
Andrieu, Christophe; Piechocki, Robert J.; McGeehan, Joe P.; Armour, Simon M.
2003-01-01
In this paper we address the problem of wide-band multiple-input multiple-output (MIMO) channel (multidimensional time invariant FIR filter) identification using Markov chains Monte Carlo methods. Towards this end we develop a novel stochastic sampling technique that produces a sequence of multidimensional channel samples. The method is semi-blind in the sense that it uses a very short training sequence. In such a framework the problem is no longer analytically tractable; hence we resort to s...
Wideband Small-Signal Input dq Admittance Modeling of Six-Pulse Diode Rectifiers
DEFF Research Database (Denmark)
Yue, Xiaolong; Wang, Xiongfei; Blaabjerg, Frede
2018-01-01
This paper studies the wideband small-signal input dq admittance of six-pulse diode rectifiers. Considering the frequency coupling introduced by ripple frequency harmonics of d-and q-channel switching function, the proposed model successfully predicts the small-signal input dq admittance of six......-pulse diode rectifiers in high frequency regions that existing models fail to explain. Simulation and experimental results verify the accuracy of the proposed model....
Ultra - Wideband, zero visual signature RF vest antenna for man-portable radios
Lebaric, Jovan E.; Adler, Richard W.; Limbert, Matthew E.
2001-01-01
This paper presents the recent research of the COMbat Wear INtegration (COMWIN) RF Vest antenna presented at MILCOM2000. This version of the ultra-wideband VHF/UHF (30 MHz to 500 MHz) vest antenna, designated as MK-III, is integrated into the existing dismounted Marine/Soldier Kevlar flak vest and has no visual signature. This antenna is one of the three COMWIN antennas developed at the Naval Postgraduate School (NPS) for the Joint Tactical Radio System applications. ...
Age and Gender Effects on Wideband Absorbance in Adults with Normal Outer and Middle Ear Function
Mazlan, Rafidah; Kei, Joseph; Ya, Cheng Li; Yusof, Wan Nur Hanim Mohd; Saim, Lokman; Zhao, Fei
2015-01-01
Purpose: This study examined the effects of age and gender on wideband energy absorbance in adults with normal middle ear function. Method: Forty young adults (14 men, 26 women, aged 20-38 years), 31 middle-aged adults (16 men, 15 women, aged 42-64 years), and 30 older adults (20 men, 10 women, aged 65-82 years) were assessed. Energy absorbance…
The Development of Analogical Reasoning Processes.
Sternberg, Robert J.; Rifkin, Bathsheva
1979-01-01
Two experiments were conducted to test the generalizability to children of a theory of analogical reasoning processes, originally proposed for adults, and to examine the development of analogical reasoning processes in terms of five proposed sources of cognitive development. (MP)
16-channel analog store and multiplexer unit
Energy Technology Data Exchange (ETDEWEB)
Brossard, M; Kulka, Z [Clermont-Ferrand-2 Univ., 63 - Aubiere (France). Lab. de Physique Corpusculaire
1979-03-15
A 16-channel analog store and multiplexer unit is described. The unit enables storing and selection of analog information which is then digitally encoded by single ADC. This solution becomes economically attractive particularly in multidetector pulse height analysis systems.
Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
K. Yao
2007-12-01
Full Text Available We investigate the maximum likelihood (ML direction-of-arrival (DOA estimation of multiple wideband sources in the presence of unknown nonuniform sensor noise. New closed-form expression for the direction estimation CramÃƒÂ©r-Rao-Bound (CRB has been derived. The performance of the conventional wideband uniform ML estimator under nonuniform noise has been studied. In order to mitigate the performance degradation caused by the nonuniformity of the noise, a new deterministic wideband nonuniform ML DOA estimator is derived and two associated processing algorithms are proposed. The first algorithm is based on an iterative procedure which stepwise concentrates the log-likelihood function with respect to the DOAs and the noise nuisance parameters, while the second is a noniterative algorithm that maximizes the derived approximately concentrated log-likelihood function. The performance of the proposed algorithms is tested through extensive computer simulations. Simulation results show the stepwise-concentrated ML algorithm (SC-ML requires only a few iterations to converge and both the SC-ML and the approximately-concentrated ML algorithm (AC-ML attain a solution close to the derived CRB at high signal-to-noise ratio.
A wideband optical monitor for a planetary-rotation coating-system
International Nuclear Information System (INIS)
Campanelli, M.B.; Smith, D.J.
1998-01-01
A substrate-specific, through-planet, wideband optical coating monitor is being developed to increase production yield and the understanding of physical vapor deposition (PVD) coatings fabricated in the Optical Manufacturing Laboratory at the University of Rochester's Laboratory for Laser Energetics. In-situ wideband optical monitoring of planetary rotation systems allows direct monitoring of large, expensive substrates with complex layering schemes. The optical monitor discussed here is under development for coating several large (e.g., 80.7 x 41.7 x 9.0 cm) polarizers for the National Ignition Facility. Wideband optical monitoring of the production substrates is used in concert with an array of crystal monitors for process control, film parameter evaluation, and error detection with associated design reoptimization. The geometry of a planetary rotation system, which produces good uniformity across large substrates, makes optical monitoring more difficult. Triggering and timing techniques for data acquisition become key to the process because the optical coating is available only intermittently for monitoring. Failure to properly consider the effects of the system dynamics during data retrieval and processing may result in significant decreases in the spectral data's reliability. Improved data accuracy allows better determination of film thicknesses, indices, and inhomogeneities and enables in-situ error detection for design reoptimization
Wideband excitation in nonlinear vibro-acoustic modulation for damage detection
Klepka, A.; Adamczyk, M.; Pieczonka, L.; Staszewski, W. J.
2016-04-01
The paper discusses the use of wideband excitation in nonlinear vibro-acoustic modulation technique (VAM) used for damage detection. In its original form, two mono-harmonic signals (low and high frequency) are used for excitation. The low frequency excitation is typically selected based on a modal analysis test and high frequency excitation is selected arbitrarily in the ultrasonic frequency range. This paper presents a different approach with use of wideband excitation signals. The proposed approach gives the possibility to simplify the testing procedure by omitting the modal test used to determine the value of low frequency excitation. Simultaneous use of wideband excitation for high frequency solves the ambiguity related to the selection of the frequency of acoustic wave. Broadband excitation signals require, however, more elaborate signal processing methods to determine the intensity of modulation for a given bandwidth. The paper discusses the proposed approach and the related signal processing procedure. Experimental validation of the proposed technique is performed on a laminated composite plate with a barely visible impact damage that was generated in an impact test. Piezoceramic actuators are used for vibration excitation and a scanning laser vibrometer is used for noncontact data acquisition.
Robust Nearfield Wideband Beamforming Design Based on Adaptive-Weighted Convex Optimization
Directory of Open Access Journals (Sweden)
Guo Ye-Cai
2017-01-01
Full Text Available Nearfield wideband beamformers for microphone arrays have wide applications in multichannel speech enhancement. The nearfield wideband beamformer design based on convex optimization is one of the typical representatives of robust approaches. However, in this approach, the coefficient of convex optimization is a constant, which has not used all the freedom provided by the weighting coefficient efficiently. Therefore, it is still necessary to further improve the performance. To solve this problem, we developed a robust nearfield wideband beamformer design approach based on adaptive-weighted convex optimization. The proposed approach defines an adaptive-weighted function by the adaptive array signal processing theory and adjusts its value flexibly, which has improved the beamforming performance. During each process of the adaptive updating of the weighting function, the convex optimization problem can be formulated as a SOCP (Second-Order Cone Program problem, which could be solved efficiently using the well-established interior-point methods. This method is suitable for the case where the sound source is in the nearfield range, can work well in the presence of microphone mismatches, and is applicable to arbitrary array geometries. Several design examples are presented to verify the effectiveness of the proposed approach and the correctness of the theoretical analysis.
Atheism and Analogy: Aquinas Against the Atheists
Linford, Daniel J.
2014-01-01
In the 13th century, Thomas Aquinas developed two models for how humans may speak of God - either by the analogy of proportion or by the analogy of proportionality. Aquinas's doctrines initiated a theological debate concerning analogy that spanned several centuries. In the 18th century, there appeared two closely related arguments for atheism which both utilized analogy for their own purposes. In this thesis, I show that one argument, articulated by the French materialist Paul-Henri Thiry Bar...
Enhancing programming logic thinking using analogy mapping
Sukamto, R. A.; Megasari, R.
2018-05-01
Programming logic thinking is the most important competence for computer science students. However, programming is one of the difficult subject in computer science program. This paper reports our work about enhancing students' programming logic thinking using Analogy Mapping for basic programming subject. Analogy Mapping is a computer application which converts source code into analogies images. This research used time series evaluation and the result showed that Analogy Mapping can enhance students' programming logic thinking.
Orgill, Mary Kay; Thomas, Megan
2007-01-01
Science classes are full of abstract or challenging concepts that are easier to understand if an analogy is used to illustrate the points. Effective analogies motivate students, clarify students' thinking, help students overcome misconceptions, and give students ways to visualize abstract concepts. When they are used appropriately, analogies can…
Science Teachers' Analogical Reasoning
Mozzer, Nilmara Braga; Justi, Rosária
2013-01-01
Analogies can play a relevant role in students' learning. However, for the effective use of analogies, teachers should not only have a well-prepared repertoire of validated analogies, which could serve as bridges between the students' prior knowledge and the scientific knowledge they desire them to understand, but also know how to…
The Micro-Category Account of Analogy
Green, Adam E.; Fugelsang, Jonathan A.; Kraemer, David J. M.; Dunbar, Kevin N.
2008-01-01
Here, we investigate how activation of mental representations of categories during analogical reasoning influences subsequent cognitive processing. Specifically, we present and test the central predictions of the "Micro-Category" account of analogy. This account emphasizes the role of categories in aligning terms for analogical mapping. In a…
Image fusion via nonlocal sparse K-SVD dictionary learning.
Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang
2016-03-01
Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.
Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.
Wang, Ping; Jiang, Jin-Yang; Li, Na; Luo, Han-Wu; Li, Fang; Cui, Shi-Gang
2017-07-01
It is possible to recover a signal below the Nyquist sampling limit using a compressive sensing technique in ultrasound imaging. However, the reconstruction enabled by common sparse transform approaches does not achieve satisfactory results. Considering the ultrasound echo signal's features of attenuation, repetition, and superposition, a sparse dictionary with the emission pulse signal is proposed. Sparse coefficients in the proposed dictionary have high sparsity. Images reconstructed with this dictionary were compared with those obtained with the three other common transforms, namely, discrete Fourier transform, discrete cosine transform, and discrete wavelet transform. The performance of the proposed dictionary was analyzed via a simulation and experimental data. The mean absolute error (MAE) was used to quantify the quality of the reconstructions. Experimental results indicate that the MAE associated with the proposed dictionary was always the smallest, the reconstruction time required was the shortest, and the lateral resolution and contrast of the reconstructed images were also the closest to the original images. The proposed sparse dictionary performed better than the other three sparse transforms. With the same sampling rate, the proposed dictionary achieved excellent reconstruction quality.
A sparse matrix based full-configuration interaction algorithm
International Nuclear Information System (INIS)
Rolik, Zoltan; Szabados, Agnes; Surjan, Peter R.
2008-01-01
We present an algorithm related to the full-configuration interaction (FCI) method that makes complete use of the sparse nature of the coefficient vector representing the many-electron wave function in a determinantal basis. Main achievements of the presented sparse FCI (SFCI) algorithm are (i) development of an iteration procedure that avoids the storage of FCI size vectors; (ii) development of an efficient algorithm to evaluate the effect of the Hamiltonian when both the initial and the product vectors are sparse. As a result of point (i) large disk operations can be skipped which otherwise may be a bottleneck of the procedure. At point (ii) we progress by adopting the implementation of the linear transformation by Olsen et al. [J. Chem Phys. 89, 2185 (1988)] for the sparse case, getting the algorithm applicable to larger systems and faster at the same time. The error of a SFCI calculation depends only on the dropout thresholds for the sparse vectors, and can be tuned by controlling the amount of system memory passed to the procedure. The algorithm permits to perform FCI calculations on single node workstations for systems previously accessible only by supercomputers
X-ray computed tomography using curvelet sparse regularization.
Wieczorek, Matthias; Frikel, Jürgen; Vogel, Jakob; Eggl, Elena; Kopp, Felix; Noël, Peter B; Pfeiffer, Franz; Demaret, Laurent; Lasser, Tobias
2015-04-01
Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method's strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.
Selectivity and sparseness in randomly connected balanced networks.
Directory of Open Access Journals (Sweden)
Cengiz Pehlevan
Full Text Available Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the "paradoxical" effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.
Low-count PET image restoration using sparse representation
Li, Tao; Jiang, Changhui; Gao, Juan; Yang, Yongfeng; Liang, Dong; Liu, Xin; Zheng, Hairong; Hu, Zhanli
2018-04-01
In the field of positron emission tomography (PET), reconstructed images are often blurry and contain noise. These problems are primarily caused by the low resolution of projection data. Solving this problem by improving hardware is an expensive solution, and therefore, we attempted to develop a solution based on optimizing several related algorithms in both the reconstruction and image post-processing domains. As sparse technology is widely used, sparse prediction is increasingly applied to solve this problem. In this paper, we propose a new sparse method to process low-resolution PET images. Two dictionaries (D1 for low-resolution PET images and D2 for high-resolution PET images) are learned from a group real PET image data sets. Among these two dictionaries, D1 is used to obtain a sparse representation for each patch of the input PET image. Then, a high-resolution PET image is generated from this sparse representation using D2. Experimental results indicate that the proposed method exhibits a stable and superior ability to enhance image resolution and recover image details. Quantitatively, this method achieves better performance than traditional methods. This proposed strategy is a new and efficient approach for improving the quality of PET images.
Sparse BLIP: BLind Iterative Parallel imaging reconstruction using compressed sensing.
She, Huajun; Chen, Rong-Rong; Liang, Dong; DiBella, Edward V R; Ying, Leslie
2014-02-01
To develop a sensitivity-based parallel imaging reconstruction method to reconstruct iteratively both the coil sensitivities and MR image simultaneously based on their prior information. Parallel magnetic resonance imaging reconstruction problem can be formulated as a multichannel sampling problem where solutions are sought analytically. However, the channel functions given by the coil sensitivities in parallel imaging are not known exactly and the estimation error usually leads to artifacts. In this study, we propose a new reconstruction algorithm, termed Sparse BLind Iterative Parallel, for blind iterative parallel imaging reconstruction using compressed sensing. The proposed algorithm reconstructs both the sensitivity functions and the image simultaneously from undersampled data. It enforces the sparseness constraint in the image as done in compressed sensing, but is different from compressed sensing in that the sensing matrix is unknown and additional constraint is enforced on the sensitivities as well. Both phantom and in vivo imaging experiments were carried out with retrospective undersampling to evaluate the performance of the proposed method. Experiments show improvement in Sparse BLind Iterative Parallel reconstruction when compared with Sparse SENSE, JSENSE, IRGN-TV, and L1-SPIRiT reconstructions with the same number of measurements. The proposed Sparse BLind Iterative Parallel algorithm reduces the reconstruction errors when compared to the state-of-the-art parallel imaging methods. Copyright © 2013 Wiley Periodicals, Inc.
Chrysikou, Evangelia G; Thompson-Schill, Sharon L
2010-06-01
Abstract The proposed theory can account for analogies based on learned relationships between elements in the source and target domains. However, its explanatory power regarding the discovery of new relationships during analogical reasoning is limited. We offer an alternative perspective for the role of PFC in analogical thought that may better address different types of analogical mappings.
Practical analog electronics for technicians
Kimber, W A
2013-01-01
'Practical Analog Electronics for Technicians' not only provides an accessible introduction to electronics, but also supplies all the problems and practical activities needed to gain hands-on knowledge and experience. This emphasis on practice is surprisingly unusual in electronics texts, and has already gained Will Kimber popularity through the companion volume, 'Practical Digital Electronics for Technicians'. Written to cover the Advanced GNVQ optional unit in electronics, this book is also ideal for BTEC National, A-level electronics and City & Guilds courses. Together with 'Practical Digit
Resistive RAMs as analog trimming elements
Aziza, H.; Perez, A.; Portal, J. M.
2018-04-01
This work investigates the use of Resistive Random Access Memory (RRAM) as an analog trimming device. The analog storage feature of the RRAM cell is evaluated and the ability of the RRAM to hold several resistance states is exploited to propose analog trim elements. To modulate the memory cell resistance, a series of short programming pulses are applied across the RRAM cell allowing a fine calibration of the RRAM resistance. The RRAM non volatility feature makes the analog device powers up already calibrated for the system in which the analog trimmed structure is embedded. To validate the concept, a test structure consisting of a voltage reference is evaluated.
Analog and mixed-signal electronics
Stephan, Karl
2015-01-01
A practical guide to analog and mixed-signal electronics, with an emphasis on design problems and applications This book provides an in-depth coverage of essential analog and mixed-signal topics such as power amplifiers, active filters, noise and dynamic range, analog-to-digital and digital-to-analog conversion techniques, phase-locked loops, and switching power supplies. Readers will learn the basics of linear systems, types of nonlinearities and their effects, op-amp circuits, the high-gain analog filter-amplifier, and signal generation. The author uses system design examples to motivate
Analog circuit design art, science, and personalities
Williams, Jim
1991-01-01
Analog Circuit Design: Art, Science, and Personalities discusses the many approaches and styles in the practice of analog circuit design. The book is written in an informal yet informative manner, making it easily understandable to those new in the field. The selection covers the definition, history, current practice, and future direction of analog design; the practice proper; and the styles in analog circuit design. The book also includes the problems usually encountered in analog circuit design; approach to feedback loop design; and other different techniques and applications. The text is
On the Automatic Parallelization of Sparse and Irregular Fortran Programs
Directory of Open Access Journals (Sweden)
Yuan Lin
1999-01-01
Full Text Available Automatic parallelization is usually believed to be less effective at exploiting implicit parallelism in sparse/irregular programs than in their dense/regular counterparts. However, not much is really known because there have been few research reports on this topic. In this work, we have studied the possibility of using an automatic parallelizing compiler to detect the parallelism in sparse/irregular programs. The study with a collection of sparse/irregular programs led us to some common loop patterns. Based on these patterns new techniques were derived that produced good speedups when manually applied to our benchmark codes. More importantly, these parallelization methods can be implemented in a parallelizing compiler and can be applied automatically.
Joint sparse representation for robust multimodal biometrics recognition.
Shekhar, Sumit; Patel, Vishal M; Nasrabadi, Nasser M; Chellappa, Rama
2014-01-01
Traditional biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attention. We propose a multimodal sparse representation method, which represents the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. Thus, we simultaneously take into account correlations as well as coupling information among biometric modalities. A multimodal quality measure is also proposed to weigh each modality as it gets fused. Furthermore, we also kernelize the algorithm to handle nonlinearity in data. The optimization problem is solved using an efficient alternative direction method. Various experiments show that the proposed method compares favorably with competing fusion-based methods.
Sparse Representation Denoising for Radar High Resolution Range Profiling
Directory of Open Access Journals (Sweden)
Min Li
2014-01-01
Full Text Available Radar high resolution range profile has attracted considerable attention in radar automatic target recognition. In practice, radar return is usually contaminated by noise, which results in profile distortion and recognition performance degradation. To deal with this problem, in this paper, a novel denoising method based on sparse representation is proposed to remove the Gaussian white additive noise. The return is sparsely described in the Fourier redundant dictionary and the denoising problem is described as a sparse representation model. Noise level of the return, which is crucial to the denoising performance but often unknown, is estimated by performing subspace method on the sliding subsequence correlation matrix. Sliding window process enables noise level estimation using only one observation sequence, not only guaranteeing estimation efficiency but also avoiding the influence of profile time-shift sensitivity. Experimental results show that the proposed method can effectively improve the signal-to-noise ratio of the return, leading to a high-quality profile.
A Projected Conjugate Gradient Method for Sparse Minimax Problems
DEFF Research Database (Denmark)
Madsen, Kaj; Jonasson, Kristjan
1993-01-01
A new method for nonlinear minimax problems is presented. The method is of the trust region type and based on sequential linear programming. It is a first order method that only uses first derivatives and does not approximate Hessians. The new method is well suited for large sparse problems...... as it only requires that software for sparse linear programming and a sparse symmetric positive definite equation solver are available. On each iteration a special linear/quadratic model of the function is minimized, but contrary to the usual practice in trust region methods the quadratic model is only...... with the method are presented. In fact, we find that the number of iterations required is comparable to that of state-of-the-art quasi-Newton codes....
A Multiobjective Sparse Feature Learning Model for Deep Neural Networks.
Gong, Maoguo; Liu, Jia; Li, Hao; Cai, Qing; Su, Linzhi
2015-12-01
Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this paper, we propose a multiobjective sparse feature learning model based on the autoencoder. The parameters of the model are learnt by optimizing two objectives, reconstruction error and the sparsity of hidden units simultaneously to find a reasonable compromise between them automatically. We design a multiobjective induced learning procedure for this model based on a multiobjective evolutionary algorithm. In the experiments, we demonstrate that the learning procedure is effective, and the proposed multiobjective model can learn useful sparse features.
Massively parallel sparse matrix function calculations with NTPoly
Dawson, William; Nakajima, Takahito
2018-04-01
We present NTPoly, a massively parallel library for computing the functions of sparse, symmetric matrices. The theory of matrix functions is a well developed framework with a wide range of applications including differential equations, graph theory, and electronic structure calculations. One particularly important application area is diagonalization free methods in quantum chemistry. When the input and output of the matrix function are sparse, methods based on polynomial expansions can be used to compute matrix functions in linear time. We present a library based on these methods that can compute a variety of matrix functions. Distributed memory parallelization is based on a communication avoiding sparse matrix multiplication algorithm. OpenMP task parallellization is utilized to implement hybrid parallelization. We describe NTPoly's interface and show how it can be integrated with programs written in many different programming languages. We demonstrate the merits of NTPoly by performing large scale calculations on the K computer.
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
Desmal, Abdulla; Bagci, Hakan
2014-01-01
Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
Desmal, Abdulla
2014-05-04
Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.
Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging
Desmal, Abdulla
2014-01-06
Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.
Identification of MIMO systems with sparse transfer function coefficients
Qiu, Wanzhi; Saleem, Syed Khusro; Skafidas, Efstratios
2012-12-01
We study the problem of estimating transfer functions of multivariable (multiple-input multiple-output--MIMO) systems with sparse coefficients. We note that subspace identification methods are powerful and convenient tools in dealing with MIMO systems since they neither require nonlinear optimization nor impose any canonical form on the systems. However, subspace-based methods are inefficient for systems with sparse transfer function coefficients since they work on state space models. We propose a two-step algorithm where the first step identifies the system order using the subspace principle in a state space format, while the second step estimates coefficients of the transfer functions via L1-norm convex optimization. The proposed algorithm retains good features of subspace methods with improved noise-robustness for sparse systems.