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检索条件"主题词=Pursuit algorithms"

共 488 条记录，以下是381-390 订阅

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Worst configurations (instantons) for Compressed Sensing over reals: A channel coding approach

Worst configurations (instantons) for Compressed Sensing ove...

引用

IEEE International Symposium on Information Theory

作者： Shashi Kiran Chilappagari Michael Chertkov Bane Vasic Marvell Semiconductor Inc. Santa Clara CA USA Theoretical Division & CNLS LANL and New Mexico Consortium Los Alamos NM USA Department of ECE University of Arizona Tucson Tucson AZ USA

ISBN: (纸本)9781424478903

We consider the Linear Programming (LP) solution of the Compressed Sensing (CS) problem over reals, also known as the Basis pursuit (BasP) algorithm. The BasP allows interpretation as a channel-coding problem, and it guarantees error-free reconstruction with a properly chosen measurement matrix and sufficiently sparse error vectors. In this manuscript, we examine how the BasP performs on a given measurement matrix and develop an algorithm to discover the sparsest vectors for which the BasP fails. The resulting algorithm is a generalization of our previous results on finding the most probable error-patterns degrading performance of a finite size Low-Density Parity-Check (LDPC) code in the error-floor regime. The BasP fails when its output is different from the actual error-pattern. We design a CS-Instanton Search Algorithm (ISA) generating a sparse vector, called a CS-instanton, such that the BasP fails on the CS-instanton, while the BasP recovery is successful for any modification of the CS-instanton replacing a nonzero element by zero. We also prove that, given a sufficiently dense random input for the error-vector, the CS-ISA converges to an instanton in a small finite number of steps. The performance of the CS-ISA is illustrated on a randomly generated 120 × 512 matrix. For this example, the CS-ISA outputs the shortest instanton (error vector) pattern of length 11.

关键词： Compressed sensing Channel coding Sparse matrices Parity check codes Linear programming pursuit algorithms Vectors Performance evaluation Degradation Algorithm design and analysis

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Fast basis selection methods

Fast basis selection methods

引用

Asilomar Conference on Signals, Systems & Computers

作者： S.F. Cotter M.N. Murthi B.D. Rao Electrical and Computer Engineering Department University of California La Jolla CA USA

In this paper three methods of basis selection are considered: basic matching pursuit (BMP), order recursive matching pursuit (ORMP) and modified matching pursuit (MMP). These algorithms are briefly described and particular attention is paid, in the formulation of these algorithms, to the computation required. Fast versions of the algorithms are developed. The algorithms are evaluated in terms of their ability to produce a sparse solution and also in terms of their computational complexity and the storage necessary to implement them. Complexity-wise, BMP and MMP are shown to be comparable while ORMP is the most complex. In terms of their ability to select basis vectors, ORMP was the best followed by MMP and then BMP.

关键词： Matching pursuit algorithms Vectors pursuit algorithms Computational complexity Time frequency analysis Video coding Speech coding Filters Signal design Algorithm design and analysis

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Voiced/Unvoiced Detection of Speech Signals Using Empirical Mode Decomposition Model

Voiced/Unvoiced Detection of Speech Signals Using Empirical ...

引用

International Conference on Information and Communication Technologies (ICICT)

作者： Md. Khademul Islam Molla Keikichi Hirose Nobuaki Minematsu Md. Kamrul Hasan Department of Information and Communication Engineering University of Tokyo Bunkyo Tokyo Japan Department of Frontier Informatics University of Tokyo Bunkyo Tokyo Japan Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

This paper presents a new technique for voiced/unvoiced (V/UV) discrimination based on the extraction of pitch period. Empirical mode decomposition (EMD) is employed for multi-band representation of speech signal in time domain. The fundamental oscillation in a speech segment is determined in the autocorrelation function (ACF) of the EMD space. A damped cosine model is fitted using least squared method to extract the frequency of the fundamental oscillation. The mean fractional energy contributed by the oscillations with pitch period in different ACFs is used as the factor to classify a speech segment as V/UV. The experimental results show that the performance of the proposed method is noticeable as compared to other reported methods.

关键词： Signal detection Matching pursuit algorithms Speech processing Speech synthesis Speech analysis Communications technology Informatics Statistics pursuit algorithms Wavelet transforms

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Adversarial Multi-Armed Bandit Approach to Stochastic Optimization

Adversarial Multi-Armed Bandit Approach to Stochastic Optimi...

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IEEE Conference on Decision and Control

作者： Hyeong Soo Chang Michael C. Fu Steven I. Marcus Department of Computer Science and Engineering Sogang University Seoul South Korea Robert H. Smith School of Business University of Maryland College Park MD USA Department of Electrical and Computer Engineering University of Maryland College Park MD USA

ISBN: (纸本)1424401704;9781424401703

We first present a sampling-based algorithm for solving stochastic optimization problems based on the Exp3 algorithm by Auer et al for "adversarial multi-armed bandit problems." The value returned by the algorithm is an upper-bound estimate of the sample-average-maximum for a sample average approximation (SAA) problem induced by the sampling process of the algorithm, and the estimate converges to the optimal objective-function value as the number of samples goes to infinity. We then recursively extend the Exp3-based algorithm for solving a given finite-horizon Markov decision process (MDP) and analyze its finite-time performance in terms of the expected bias relative to the maximum value of the induced recursive SAA problem, showing that the upper bound of the expected bias approaches zero as the sampling size per stage goes to infinity, leading to the convergence to the optimal value of the original MDP problem in the limit

关键词： Stochastic processes Probability distribution USA Councils Approximation algorithms Sampling methods Educational institutions H infinity control Algorithm design and analysis pursuit algorithms Computer science

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Activity and Channel Estimation in Multi-User Wireless Sensor Networks

Activity and Channel Estimation in Multi-User Wireless Senso...

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WSA 2016;20th International ITG Workshop on Smart Antennas

作者： Benjamin Knoop Sebastian Schmale Dagmar Peters-Drolshagen Steffen Paul

Machine-type communications is quite often of very low data rate and of sporadic nature. In a multi-user wireless sensor network, this sporadic transmission activity can favourably be exploited to facilitate a joint activity and data detection on the physical layer as it has been shown in previous works. This abolishes the need for shared channel access signaling on higher network layers and increases bandwidth efficiency. However, each data source transmits over a user-specific channel which makes channel estimation mandatory for phase-coherent reception and channel equalisation. Since a totally blind estimation of channels, transmit activities and user data simultaneously is practically infeasible, we propose a joint activity and channel estimation scheme based on pilots and matching pursuit algorithms. We show that Zadoff-Chu sequences lead to a better user separation and estimation performance than random Gaussian codes. And since we do not make any assumptions about the user's data payload, our results are generally valid for any frame structure.

关键词： channel estimation activity FRAMED STRUCTURES Wireless sensor networks Low Data Rate network layer user data data detection Physical layer Pilots Matching pursuit algorithms pursuit algorithms

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BEV Image-based Lane Tracking Control System for Autonomous Lane Repainting Robot

BEV Image-based Lane Tracking Control System for Autonomous ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Junghyun Seo Hyeonjae Jeon Joonyoung Choi Kwangho Woo Yongseob Lim Yongsik Jin Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea Robot for People (RP) Daegu Republic of Korea Electronics and Telecommunications Research Institute (ETRI) Daegu Republic of Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we present a novel study on a BEV (bird’s eye view) image-based lane tracking control system for an autonomous lane repainting robot. Our research introduces a cutting-edge lane detection method based on BEV images, leveraging row-anchor techniques to enhance precision and provide detailed error information for lane tracking algorithms. By utilizing real-time sensor data and advanced deep learning processes, we have successfully implemented a high-performance lane repainting system that minimizes errors and ensures accuracy. Our proposed position-based visual pure pursuit algorithm (PV-PP) plays a crucial role in guiding the lane repainting process with precision and efficiency, ultimately improving the functionality and feasibility of the linear actuator responsible for paint spraying in the real indusrial fields. Through our contributions, including innovative lane detection methods, real-time sensor utilization, and robot control algorithm design, we aim to advance the field of autonomous lane repainting robots and enhance the safety and effectiveness of road maintenance operations.

关键词： Visualization Lane detection Roads Robot control Spraying Robot sensing systems Real-time systems Safety pursuit algorithms Paints

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Matching pursuits channel estimation for an underwater acoustic OFDM modem

Matching pursuits channel estimation for an underwater acous...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Taehyuk Kang Ronald A. Iltis Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

Sparse channel estimation algorithms are proposed for underwater acoustic Orthogonal Frequency Division Multiplexing (OFDM) communications in time-varying multipath channels. Following carrier frequency offset (CFO) correction, the proposed algorithms first extract the portion of the time domain signal corresponding to pilot symbols. The Matching pursuit (MP) algorithm is then applied to channel estimation. Performance of the proposed receiver is evaluated in simulations and in underwater field tests. Experiments in shallow water show that a BER on the order of 10 -3 is achievable at 330 m distance for uncoded data transmission. Experimental results with LDPC-coded transmission are also presented showing zero BER at 330 m.

关键词： Matching pursuit algorithms Channel estimation Underwater acoustics OFDM Modems Bit error rate Underwater communication Multipath channels pursuit algorithms Testing

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Examining the ϵ-optimality property of a tunable FSSA

Examining the ϵ-optimality property of a tunable FSSA

引用

IEEE International Conference on Cognitive Informatics

作者： A. H. Jamalian R. Iraji A. R. Sefidpour M. T. Manzuri-Shalmani Department of Computer Engineering Sharif University of Technology Tehran Iran Card Department Bank Eghtesad Novin Tehran Iran

ISBN: (纸本)1424413273;97

In this paper, a new fixed structure learning automaton (FSSA), with a tuning parameter for amount of its rewards, is presented and its behavior in stationary environments will be studied. This new automaton is called TFSLA (tunable fixed structured learning automata). The proposed automaton characterizes by star shaped transition diagram and each branch of the star contains N states associated with a particular action. TFSLA is tunable, so that the automaton can receive reward flexibly, even when it accepted penalty according to its previous action. Experiments show that TFSLA converges to the optimal action faster than some older FSSAs (e.g. Krinsky and Krylov) and the analytic examination proofs that the new automaton is ϵ-optimal.

关键词： Learning automata pursuit algorithms Power engineering computing Organisms Feedback Cybernetics Power engineering and energy Learning systems Stochastic processes Tin

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RAMP: an adaptive filter with links to matching pursuits and iterative linear equation solvers

RAMP: an adaptive filter with links to matching pursuits and...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： J.H. Husoy Department of Electrical and Computer Engineering Stavanger University College Stavanger Norway

Using the matching pursuit principle we present recursive adaptive matching pursuit (RAMP), a new fast converging adaptive filter having a complexity that is linear in the number of filter coefficients. We show that the algorithm provides for an explicit tradeoff between complexity and performance. The algorithm's relation to a Gauss-Seidel iterative scheme applied to the normal equations is uncovered. This is useful in establishing convergence results. Finally, before presenting an example simulation showing the performance of the algorithm, we point out that the presented algorithm can be viewed as a generalization of the recently introduced fast Euclidian direction search (FEDS) algorithm.

关键词： Adaptive filters Matching pursuit algorithms Equations Signal processing algorithms Iterative algorithms Gaussian processes Convergence Vectors pursuit algorithms Educational institutions

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Image Denoising with Shrinkage and Redundant Representations

Image Denoising with Shrinkage and Redundant Representations

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： M. Elad B. Matalon M. Zibulevsky Department of Computer Science Technion-Israel Institute of Technology Haifa Israel Department of Electrical Engineering Israel

Shrinkage is a well known and appealing denoising technique. The use of shrinkage is known to be optimal for Gaussian white noise, provided that the sparsity on the signal’s representation is enforced using a unitary transform. Still, shrinkage is also practiced successfully with nonunitary, and even redundant representations. In this paper we shed some light on this behavior. We show that simple shrinkage could be interpreted as the first iteration of an algorithm that solves the basis pursuit denoising (BPDN) problem. Thus, this work leads to a novel iterative shrinkage algorithm that can be considered as an effective pursuit method. We demonstrate this algorithm, both on synthetic data, and for the image denoising problem, where we learn the image prior parameters directly from the given image. The results in both cases are superior to several popular alternatives.

关键词： Image denoising Wavelet transforms Noise reduction Iterative algorithms Table lookup White noise pursuit algorithms Computer science Iterative methods Maximum a posteriori estimation

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