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检索条件"主题词=Signal Processing Algorithms"

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Research on Heterogeneous Parallel algorithms for Radar signal processing in OpenCL Platform

Research on Heterogeneous Parallel Algorithms for Radar Sign...

引用

International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Yingfei Wang Xiaoqin Xue Wei Wang Department of Computer Science Xi’an Polytechnic University Xi’an China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China

An efficient radar signal processing parallel algorithm for Open Computing Language (OpenCL) is presented in this paper, which reveals a rational allocation schema of tasks between the central processing unit (CPU) and the graphics processing unit (GPU). The powerful parallel processing ability of GPU is used to replace the traditional serial processing method by the way of pipeline acceleration and algorithm parallel acceleration, and the real-time performance of the proposed algorithm is improved by the design idea of intra-module parallelism and inter-module flow processing. The algorithm is applied to CPU-GPU heterogeneous computing platform and has a good portability. The effectiveness and real-time performance of the algorithm are verified through simulation data.

关键词： signal processing algorithms Graphics processing units Radar signal processing Real-time systems Heterogeneous networks Central processing Unit Resource management

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Research of Digital algorithms Implementing Integrated Mellin Transform for signal processing in Automated Control Systems

Research of Digital Algorithms Implementing Integrated Melli...

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International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)

作者： A. Makarov S. Postovalov A. Ermakov Department of information and communication technologies Pyatigorsk state University G. Pyatigorsk Departments of control systems and information technologies North Caucasus Federal University G. Pyatigorsk

The use of integral transformations for signal processing purposes has long been known-these are the integral Fourier, Hilbert, Laplace, Bessel transformations. In the late 20th and early 21st centuries, the Mellin integral transformation was used to solve signal processing problems under uncertainty of the signal scale and the shape of the noise correlation function. But in the practical application of the Mellin transformation, difficulties arose in its hardware and software implementation. The purpose of this article is to develop suitable for digital implementation of Mellin transform algorithms based on existing hardware and software of computer technology.

关键词： signal processing algorithms signal processing Industrial engineering Transforms Hardware Software Uncertainty

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Analysis and design of parallel algorithms and implementations of matrix multiplications for image and signal processing

Analysis and design of parallel algorithms and implementatio...

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IEEE Pacific Rim Conference on Communications, Computers and signal processing

作者： M. Yasrebi J.C. Browne IBM Corporation Austin TX USA Computer Science Department University of Technology Austin TX USA

Parallel matrix multiplication algorithms (based on the common data distribution formats) used in pattern recognition, image processing, and signal processing applications are discussed. A novel algorithm is introduced and is shown to be the fastest one for a determined class of applications. The algorithms are analyzed for performance as a function of array dimension, data distribution formats, and the architecture of the computer upon which the algorithms are executed. Performance bounds and speedups (linear in the number of processors) are established. The results of the analysis are given both as characterizations of executions on selected classes of architectures and also in the form of theorems which establish the relative performance of the algorithms across classes of data distributions and architectures.< >

关键词： Algorithm design and analysis Parallel algorithms signal processing algorithms Application software Performance analysis Computer architecture Pattern recognition Image processing Array signal processing Distributed computing

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Stabilized algorithms for ill-posed problems in signal processing

Stabilized algorithms for ill-posed problems in signal proce...

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International Conferences on Info-tech and Info-net (ICII)

作者： Zhang Buyun Xu Dinghua Liu Tangwei Department of Electronic Engineering Nanjing University of Science and Technology of PLA Nanjing China East China Geological Institute Fuzhou Jiangxi China

In this paper we discuss two kinds of ill-posed problems in signal processing, that is, in detail, reconstructing compactly supported signals in the Fourier transform and solving the convolution equation with analytic kernel. Having analyzed the essential reason of ill-posedness for these problems, we present some stabilized algorithms, which cure the ill-posedness, to recover the approximate solution. Finally numerical experiments show the efficiency and fast convergence of these algorithms.

关键词： signal processing algorithms Equations Fourier transforms Image reconstruction Algorithm design and analysis signal processing Convolution Mathematical model signal analysis Kernel

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Research on the Application of Machine Learning Big Data Mining algorithms in Digital signal processing

Research on the Application of Machine Learning Big Data Min...

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Image processing, Electronics and Computers (IPEC), Asia-Pacific Conference on

作者： Simin Niu Taiyuan University of Technology Taiyuan China

ISBN: (纸本)9781728190198

Traditional digital signal processing technology based on DSP and FPGA is more suitable for real-time signal processing, and is limited by data scale and frequency resolution, making it unsuitable for offline data processing, analysis and mining under large-scale data Application. At present, the industrial big data analysis platform can use Spark as a calculation engine for real-time signal processing and offline signal processing acceleration, but the analysis platform lacks mathematical calculation solutions such as digital signal processing suitable for distributed parallel calculation engines. This article is based on time the parity decomposition is selected, and the fast Fourier transform is realized by MATLAB software. Based on an example of the application of the compiled FFT source program, this article analyses the frequency spectrum of discrete-time and continuous-time signals of limited length.

关键词： Machine learning algorithms signal processing algorithms Digital signal processing Machine learning Libraries Real-time systems Sparks

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Stability and convergence of a class of nonlinear algorithms in digital signal processing

Stability and convergence of a class of nonlinear algorithms...

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International Conference on signals and Systems (ICSigSys)

作者： T.J. Moir Department of Electrical and Electronic Engineering Auckland University of Technology Auckland New Zealand

ISBN: (纸本)9781509067497

Square-root algorithms have use in certain areas of digital signal processing. However, they are characterized as being non-linear in nature and hence their analysis is not straight-forward. This paper examines two such algorithms and shows that the convergence is guaranteed provided the closed-loop discrete-time system is stable, but that the upper limit on stability is determined by the values of the square-root coefficients themselves. The analysis is quite classical but also requires a link between Toeplitz matrices and polynomials to progress further.

关键词： Convolution Convergence Stability analysis Mathematical model Eigenvalues and eigenfunctions Algorithm design and analysis signal processing algorithms

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High performance algorithms for digital signal processing AGC

High performance algorithms for digital signal processing AG...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： G.N. Tavares M.S. Piedade INESC and CEAUTL (INIC) Lisboa Portugal INESC & Univ. Tecnica Lisboa Portugal

New types of discrete-time automatic gain control (AGC) circuits are proposed. The AGCs are based on iterative processes, and both feedforward and feedback structures are considered for two different signal energy detectors: mean absolute deviation (MAD) and root mean square (RMS). The different algorithms were implemented on a digital signal processor, and experimental results are presented.< >

关键词： signal processing algorithms Digital signal processing Iterative algorithms Gain control Circuits Feedback signal processing signal detection Detectors Root mean square

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Linearly constrained adaptive algorithms for line-frequency signal processing

Linearly constrained adaptive algorithms for line-frequency ...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： O. Vainio Department of Information Technology Tampere University of Technology Tampere Finland

Linearly constrained LMS adaptive filter algorithms are considered for digital processing of 50/60 Hz line-frequency signals. The constraints are set such that the primary sinusoidal waveform is guaranteed to pass the filter unaltered, and the adaptation is used to dynamically optimize the noise attenuation properties. In order to reduce the computational complexity of the constrained algorithm, selective coefficient updating is used, and the update formulas are derived accordingly. The approach is efficient in suppressing noise and harmonics in applications such as reactive power estimation and zero-crossing detection.

关键词： Adaptive algorithm signal processing algorithms Adaptive signal processing Least squares approximation Adaptive filters signal processing Constraint optimization Attenuation Computational complexity Power system harmonics

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Modified LMS algorithms for high speed underwater acoustic signal processing

Modified LMS algorithms for high speed underwater acoustic s...

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OCEANS

作者： En-Fang Sang Hen-Geul Yeh Harbin Shipbuilding Engineering Institute Harbin China Electrical Engineering Department California State University Long Beach CA USA Electrical Engineering Department California State University Long Beach Long Beach CA USA

ISBN: (纸本)0780313852

Several modified Least Mean Square (LMS) algorithms are studied in order to improve the rate of convergence of the regular LMS algorithm. The performance of these modified LMS algorithms is evaluated by simulations. It shows that the error feedback LMS algorithm converges much faster then all other modified LMS algorithms including regular LMS algorithm.< >

关键词： signal processing algorithms Least squares approximation Underwater acoustics Acoustic signal processing Convergence signal to noise ratio Acoustic noise signal processing Iterative algorithms Adaptive signal processing

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Addressing the requirements for fast sidelobe stabilisation algorithms and their application in sonar signal processing

Addressing the requirements for fast sidelobe stabilisation ...

引用

OCEANS

作者： J. Gill P. McNair C. Hodges Qinetiq Limited Weymouth Dorset UK

Adaptive beamforming (ABF) methods typically yield beam patterns that contain regions of high sidelobe gain. This can become a major problem when the platform is mobile with respect to noise sources. Real world ABF systems demand some sort of sidelobe control or stabilisation - one such approach is via penalty function methods. Computational speed is an important issue and their exists a requirement for computationally efficient methods of calculating penalty functions. One such method is described in this paper.

关键词： signal processing algorithms Sonar applications Adaptive signal processing Array signal processing Power generation Radar signal processing Covariance matrix Adaptive arrays Control systems Radar imaging

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