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IEEE signal processing MAGAZINE 2014年第3期31卷 16-17页

作者： Adali, Tuelay Jutten, Christian Yeredor, Arie Cichocki, Andrzej Moreau, Eric University of Maryland Baltimore MD 21250 United States Department of Electronics and Communication Engineering National Institute of Technology Durgapur West Bengal India Department of ECE NITMAS Dum Dum West Bengal India University of Toulon 83957 France

Presents the guest editorial for this issue of the publication.

关键词： Special issues and sections Source separation signal processing algorithms Matrix decomposition Heuristic algorithms Blind source separation

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An Efficient and Accurate RCS Reconstruction Technique Using Adaptive TLS-ESPRIT Algorithm

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2024年第1期23卷 49-53页

作者： Zhu, Fang-Yin Chai, Shui-Rong Zou, Yu-Feng He, Zhen-Xiang Guo, Li-Xin Xidian Univ Sch Phys Xian 710071 Peoples R China

In this letter, an adaptive total least squares-estimating signal parameter via rotational invariance techniques (TLS-ESPRIT) algorithm based on the analytical perspective is proposed to efficiently construct the scattering center model (SCM) and reconstruct the radar cross section (RCS) of a perfect electrical conductor (PEC) target. Compared with existing research, the proposed method does not require knowing the number of scattering centers, which means that it can be applied to the construction of SCMs for noncooperative targets. Compared with inverse synthetic aperture radar (ISAR) and statistical methods, this work strikes a balance between accuracy and efficiency through optimization of the core technology in the RCS reconstruction process. The effectiveness of the algorithm is verified by comparing the results derived by our method with those from the measurement.

关键词： Scattering Adaptation models signal processing algorithms Radar cross-sections Radar scattering Image reconstruction Statistical analysis Adaptive TLS-ESPRIT algorithm Hankel matrix one-dimensional (1-D) scattering center radar cross section (RCS) reconstruction

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The comparison of the constrained and unconstrained frequency-domain block-LMS adaptive algorithms

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IEEE TRANSACTIONS ON signal processing 1996年第7期44卷 1813-1816页

作者： Li, XH Jenkins, WK Coordinated Science Laboratory University of Illinois Urbana-Champaign Urbana-Champaign IL USA

Convergence properties of the constrained and the unconstrained frequency-domain block LMS algorithms are analyzed, Comparisons based on both a theoretical analysis and computer simulation are given, It is shown that the unconstrained algorithm has a slower convergence rate and smaller stable range of step size than that of the constrained algorithm.

关键词： Adaptive algorithm signal processing algorithms Frequency domain analysis Least squares approximation Algorithm design and analysis Convergence Computer simulation Filtering algorithms Adaptive filters Computational complexity

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Evaluation of storage requirements and applications in the memory management for multidimensional signal processing systems

Evaluation of storage requirements and applications in the m...

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IEEE International Conference on Electro-Information Technology

作者： Ilie I. Luican Hongwei Zhu Florin Balasa Department of Computer Science University of Illinois Chicago Chicago IL USA ARM Inc. Sunnyvale CA USA

The amount of the data storage in signal processing systems, whose behavior is described by loop-organized algorithmic specifications, has an important impact on the overall energy consumption, chip area, as well as system performance. This paper presents a non-scalar approach for computing exactly the minimum data storage for high-level procedural specifications, where the main data structures are multi-dimensional arrays. In contrast, all the previous works are only estimation methods. In addition, the paper discusses two applications of this technique in the memory management of signal processing systems: (1) the evaluation of the impact of loop transformations on the data storage, and (2) the assessment of different models of mapping multi-dimensional signals into the physical memory.

关键词： Memory management Multidimensional signal processing signal processing algorithms Energy consumption System performance Data structures signal processing Computational modeling Production Energy storage

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A novel approach to the convergence of neural networks for signal processing

A novel approach to the convergence of neural networks for s...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： Ruey-Wen Liu Yih-Fang Huang Xie-Ting Ling Department of Electrical Engineering University of Notre Dame Notre Dame IN USA Department of Electronic Engineering Fudan University Shanghai China

ISBN: (纸本)0780320700

Summary form only given. A novel deterministic approach to the convergence of (stochastic) learning algorithms is presented. The link is the new concept of time-average invariance which is a property of deterministic signals but resembles the realizations of stochastic signals that are ergodic and stationary. An unsupervised learning algorithm is considered. signals are viewed as deterministic functions, but satisfy a property called time-average invariance. As such, deterministic-based analysis can be applied to stochastic-like signals. Consequently, the complexity of the convergence analysis is significantly reduced.< >

关键词： Convergence Neural networks signal processing signal processing algorithms Stochastic processes Equations Unsupervised learning Counting circuits signal analysis

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Developing custom signal processing algorithm with labview FPGA and compact RIO to detect the Aortic Stenosis disease

Developing custom signal processing algorithm with labview F...

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Computers in Cardiology (CinC)

作者： B. Al-Naami J. Chebil B. Trabsheh H. Mgdob Hashemite University Zarqa Jordan University of Sussex Brighton UK

ISBN: (纸本)9781424425327

FPGAs provide an ideal template for run-time reconfigurable (RTR) designs. Only recently have RTR enabling design tools that bypass the traditional synthesis and bit stream generation process for FPGAs become available. Heart auscultation which is the interpretation of sounds produced by the heart is a fundamental tool in the diagnosis of heart disease. It is the most commonly used technique for screening and diagnosis in primary health care. This study aims at utilizing the discrete wavelet packet transforms in early detection of an Aortic Stenosis (AS) using heart sound data collected at Sussex University Hospital in England. From the data analysis, a criteria has been proposed for the detection of the AS disease from the heart sound data.

关键词： signal processing algorithms Field programmable gate arrays Heart Cardiac disease Cardiovascular diseases Discrete wavelet transforms Runtime signal synthesis Medical services Wavelet packets

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New programmable FFT implementations for radar signal processing

New programmable FFT implementations for radar signal proces...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： D.R. Bungard L. Lau T.L. Rorabaugh MITRE Corporation Bedford MA USA

The authors have designed two high-throughput, wide-dynamic-range, real-time FFT processors for use in advanced wide-bandwidth HF radar systems. These FFTs are capable of real-time operation at continuous throughput rates greater than 2 MHz with a programmable transform length of up to 16 K points. Either 32-b fixed-point or 32-b floating-point (IEEE format) computations can be performed. An interesting result is that both FFT design approaches provide approximately the same throughput rate, are approximately the same size (250 ICs), and require less than 100 W of power.< >

关键词： Radar signal processing signal processing algorithms Computer architecture Throughput signal design Pipelines Algorithm design and analysis Dynamic range Costs Digital signal processing chips

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Low-power reconfigurable signal processing via dynamic algorithm transformations (DAT)

Low-power reconfigurable signal processing via dynamic algor...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： M. Goel N.R. Shanbhag Coordinated Science Laboratory/ECE Department University of Illinois Urbana-Champaign Urbana-Champaign IL USA

Presented in this paper are dynamic algorithm transformations (DAT) for systematic design of reconfigurable computing engines. These techniques allow dynamic alteration of algorithm properties in response to input non-stationarities. The input is modeled as a set of states with an underlying probability distribution, /spl Pscr//sub S/. For each input state s, a signal monitoring algorithm (SMA) computes a power-optimal configuration for the signal processing algorithm (SPA) block. A fraction /spl alpha/ of the (SPA) block is hardwired and the remaining (1-/spl alpha/) is reconfigurable. Similarly, the (SMA) block computation is partitioned into a fraction /spl beta/ for the memory and the remaining (1-/spl beta/) for the data path. For the given input state distribution, the optimal values of /spl alpha/ (/spl alpha//sub opt/) and /spl beta/ (/spl beta//sub opt/) are determined. It is shown that for frequency selective filtering (FIR filters), the power savings of 35%-45% can be achieved by a DAT-based reconfigurable system as compared to the traditional design based on the worst-case scenario.

关键词： signal processing algorithms Heuristic algorithms Optimized production technology Finite impulse response filter Algorithm design and analysis Engines Power system modeling Probability distribution signal processing Monitoring

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PVL: An object oriented software library for parallel signal processing

PVL: An object oriented software library for parallel signal...

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Annual IEEE Symposium on Foundations of Computer Science

作者： E. Rutledge J. Kepner MIT Lincoln Laboratories USA

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. Real-time signal processing consumes the majority of the world's computing power. Increasingly, programmable parallel microprocessors are used to address a wide variety of signal processing applications (e.g. scientific, video, wireless, medical, communication, encoding, radar, sonar and imaging). In programmable systems the major challenge is no longer hardware but software. Specifically, the key technical hurdle lies in mapping (i.e., placement and routing) of an algorithm onto a parallel computer in a general manner that preserves software portability. We have developed the Parallel Vector Library (PVL) to allow signal processing algorithms to be written using high level Matlab like constructs that are independent of the underlying parallel mapping. Programs written using PVL can be ported to a wide range of parallel computers without sacrificing performance. Furthemore, the mapping concepts in PVL provide the infrastructure for enabling new capabilities such as fault tolerance, dynamic scheduling and self-optimization. This presentation discusses PVL with particular emphasis on quantitative comparisons with standard parallel signal programming practices.

关键词： Software libraries signal processing Video signal processing signal processing algorithms Concurrent computing Military computing Microprocessors Application software Wireless communication

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A non-linear phase-only algorithm for active sonar signal processing

A non-linear phase-only algorithm for active sonar signal pr...

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OCEANS

作者： F. Chan E. Rabe Division Newport Naval Undersea Warfare Center RI USA

In highly reverberant environments the standard signal processing chain for wideband active sonar may be improved by using a phase-only filter to perform replica correlation. Because of the significant distortion of t... 详细信息

关键词： signal processing algorithms Sonar detection Reverberation Matched filters Wideband Frequency Filtering Phase distortion Bandwidth signal processing

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