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检索条件"主题词=Pursuit Algorithms"

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Dimensionality Reduction with Adaptive Approximation

Dimensionality Reduction with Adaptive Approximation

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Effrosyni Kokiopoulou Pascal Frossard Signal Processing Institute-ITS Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland

In this paper, we propose the use of (adaptive) nonlinear approximation for dimensionality reduction. In particular, we propose a dimensionality reduction method for learning a parts based representation of signals using redundant dictionaries. A redundant dictionary is an overcomplete set of basis vectors that spans the signal space. The signals are jointly represented in a common subspace extracted from the redundant dictionary, using greedy pursuit algorithms for simultaneous sparse approximation. The design of the dictionary is flexible and enables the direct control on the shape and properties of the basis functions. Moreover, it allows to incorporate a priori and application-driven knowledge into the basis vectors, during the learning process. We apply our dimensionality reduction method to images and compare it with principal component analysis (PCA) and non-negative matrix factorization (NMF) and its variants, in the context of handwritten digit image recognition and face recognition. The experimental results suggest that the proposed dimensionality reduction algorithm is competitive to PCA and NMF and that it results into meaningful features with high discriminant value.

关键词： Dictionaries Principal component analysis Shape control Image recognition Sparse matrices Image coding Adaptive signal processing pursuit algorithms Face recognition Signal processing algorithms

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Uniqueness of Linear Combinations of Ridge Functions

Uniqueness of Linear Combinations of Ridge Functions

引用

International Conference on Natural Computation (ICNC)

作者： Jinling Long Wei Wu Dong Nan Junfang Wang Department of Applied Mathematics Dalian University of Technology Dalian China

Ridge functions are multivariate functions of the form g(a ldr x), where g is a univariate function, and a ldr x is the inner product of a isin R d \{0} and x isin R d . We are concerned with the uniqueness of representation of a given function as some sum of ridge functions. We prove that if f(x) = Sigma i=1 m g i (a i ldr x) = 0 for some a i = (a 1 i , hellip , a d i ) isin R d \{0}, and if g i isin L loc p (R) (or g i isin D' (R) and g i (a i ldr x) isin D' (R d )), then, each g i is a polynomial of degree at most m - 2. We also prove a theorem on the smoothness of linear combinations of ridge functions. These results improve the existing results.

关键词： Polynomials Lab-on-a-chip Mathematics Vectors Partial differential equations Tomography Neural networks Approximation methods Statistics pursuit algorithms

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The Engineering and Societal Impact of Embedded and Autonomous Systems: Beyond Sensor Webs

The Engineering and Societal Impact of Embedded and Autonomo...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Shankar Sastry Bioengineering and Mechanical Engineering University of California Berkeley USA

There has been a great deal of excitement in recent years concerning the evolution of sensor webs of smart dust. There has been a very substantive active world wide in this area and in particular at Berkeley there have now been over six generation of "motes" for these sensor webs, and numerous start ups have arisen to commercialize these developments. I will survey the state of these exciting technology developments and describe how the technology push is matched by the applications pull on numerous different kinds of deployments. I will highlight the efforts of my group and that of my colleagues in developing what we refer to as "embedded intelligence" in the environment. In particular, I will describe the range of learning, signal processing and data aggregation methods and algorithms needed to track multiple targets in sensor webs and to be able to pursue these targets in a pursuit evasion game. I believe that the next frontier is the development of network embedded systems combining the use of sensor networks combining heterogeneous webs with high and low bandwidth sensors (such as camera motes) and mobile sensor webs. In particular, I will discuss the use of some new techniques, we have introduced along with Rene Vidal of Johns Hopkins and Yi Ma of UIUC, in the context of computer vision, called Generalized Principal Component Analysis to analyze multi-camera data.

关键词： Sensor systems Intelligent sensors Signal processing algorithms Uninterruptible power systems Commercialization pursuit algorithms Target tracking Sensor phenomena and characterization Embedded system Bandwidth

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Fast implementation of a l∞- l/1 penalized sparse representations algorithm: applications in image denoising and coding

Fast implementation of a l∞- l/1 penalized sparse represent...

引用

Asilomar Conference on Signals, Systems & Computers

作者： Jean-Jacques Fuchs Christine Guillemot IRISA/INRIA-Université de Rennes 1 Rennes France

Sparse representation techniques have become an important tool in image processing in recent years, for coding, de-noising and in-painting purposes, for instance. They generally rely on an lscr 2 -lscr 1 penalized criterion and fast algorithms have been proposed to speed up the applications. We propose to replace the lscr 2 -part of the criterion, which has been chosen both for its easy implementation and its relation to the PSNR quality measure, by a lscr ∞ -part. We present a new fast way to minimize a lscr ∞ - lscr 1 penalized criterion and assess its potential benefits for image De-noising and coding.

关键词： Image coding Image reconstruction Signal processing algorithms Image denoising Matching pursuit algorithms Image processing PSNR Video coding Software algorithms pursuit algorithms

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Using Stereo Information for Instrument Identification in Polyphonic Mixtures

Using Stereo Information for Instrument Identification in Po...

引用

IEEE Workshop on Applications of Signal Processing to Audio and Acoustics

作者： David Sodoyer Pierre Leveau Laurent Daudet Institut Jean Le Rond D'Alembert LAM team University Pierre and Marie Curie Paris France TSI Department GET-Télécom Paris (ENST) Paris France

This paper discusses the localization of music instruments in the stereo space. The signal, composed of two channels, is decomposed into a linear combination of Stereo Instrument-Specific Harmonic atoms, that model the harmonic structure of instrument notes as a whole and whose individual angles give clues about the real angle of the sources. To get such decompositions, a Stereo Matching pursuit algorithm has been implemented, with a phase adaptation for each signal channel. This decomposition gives neat source localizations for instantaneous mixes, and the extension to realistic convolutive mixes seems possible with adequate post-processing.

关键词： Instruments Matching pursuit algorithms Multiple signal classification pursuit algorithms Music Signal processing algorithms Conferences Acoustic signal processing Acoustic applications Digital recording

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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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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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Compressed Sensing for Ultrawideband Impulse Radio

Compressed Sensing for Ultrawideband Impulse Radio

引用

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

作者： Jose L. Paredes Gonzalo R. Arce Zhongmin Wang Electrical Engineering Department Universidad de Los Andes Venezuela Department of Electrical and Computer Eng University of Delaware USA

In this paper, ultrawideband (UWB) channel estimation based on the novel theory of compressive sensing (CS) is developed. The proposed approach relies on the fact that transmitting an ultra-short UWB pulse through a multipath channel leads to a received UWB signal that can be approximated by a linear combination of a few atoms from a pre-defined dictionary, yielding thus a sparse representation of the received signal. The CS reconstruction capabilities are exploited to recover the composite pulse-multipath channel from a reduced set of random projections using the matching pursuit algorithm. This reconstructed signal is subsequently used as a referent template in a correlator based detector. Extensive simulations show that for different propagation scenarios and UWB communication environments, the CS detector outperforms traditional correlators using just 1/3 of the sampling rate leading thus to a reduced use of analog-to-digital resources in the channel estimation stage.

关键词： Compressed sensing Ultra wideband technology Channel estimation Matching pursuit algorithms Correlators Detectors Multipath channels Linear approximation Dictionaries pursuit algorithms

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Nonconvex Compressed Sensing and Error Correction

Nonconvex Compressed Sensing and Error Correction

引用

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

作者： Rick Chartrand Los Alamos National Laboratory USA

The theory of compressed sensing has shown that sparse signals can be reconstructed exactly from remarkably few measurements. In this paper we consider a nonconvex extension, where the lscr 1 1 norm of the basis pursuit algorithm is replaced with the lscr p norm, for p < 1. In the context of sparse error correction, we perform numerical experiments that show that for a fixed number of measurements, errors of larger support can be corrected in the nonconvex case. We also provide a theoretical justification for why this should be so.

关键词： Compressed sensing Error correction Image reconstruction pursuit algorithms Image coding Cryptography Laboratories Performance evaluation Signal reconstruction Error correction codes

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Clustered K-Center: Effective Replica Placement in Peer-to-Peer Systems

Clustered K-Center: Effective Replica Placement in Peer-to-P...

引用

IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference

作者： Jian Zhou Xin Zhang Laxmi Bhuyan Bin Liu University of California Riverside USA Carnegie Mellon University USA Tsinghua University China

Peer-to-Peer (P2P) systems provide decentralization, self-organization, scalability and failure-resilience, but suffer from high worst-case latencies. Researchers have proposed various replication algorithms to place multiple copies of objects across the network in pursuit of better performance for P2P computing; nevertheless, they neither presented clear analysis nor derived worst-case bound for their algorithms. In this paper, we model the replica placement problem arising in real-world P2P networks as a Clustered K-Center problem which we prove to be NP-complete. Then we propose an efficient approximation algorithm to this problem with a provable upper bound. Extensive experiments have been conducted to demonstrate the effectiveness and efficiency of our algorithm. The experimental results show that our approach can run several orders of magnitude faster than the optimal solution while being able to minimizing the query latency.

关键词： Peer to peer computing Clustering algorithms Delay pursuit algorithms Scalability Computer networks Performance analysis Algorithm design and analysis Approximation algorithms Upper bound

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