期刊
SIGNAL PROCESSING
卷 132, 期 -, 页码 40-50出版社
ELSEVIER
DOI: 10.1016/j.sigpro.2016.09.004
关键词
Non-stationary signal analysis; Swarm decomposition; Swarm intelligence; Swarm filtering
A novel approach in non-stationary signal decomposition, namely swarm decomposition (SWD), that fosters rules of biological swarms to address non-stationary signal analysis, is presented here. Cornerstone of SWD is the swarm filtering (SwF), a processing approach envisioned by a swarm-prey hunting. Under proper parameterization, the output of iterative applications of SwF results in an individual component of the input signal. To control the method, the relationships between hunting parameters and particular responses of SwF are extracted using a genetic algorithm. SWD consists of successive applications of iterative SwF under different hunting parameters, so as the existing components to be extracted. The SWD is evaluated through its application to non-stationary multi-component (both synthetic and real-life) signal decomposition. The results obtained by SWD are compared with the respective ones obtained by empirical mode decomposition, wavelet-based multiresolution analysis and an iterative approach based on eigenvalue decomposition of the Hankel matrix, achieving higher accuracy in correctly isolating the components of the analyzed signals in the most cases. The promising results pave the way for a new approach in signal decomposition with a wide range of application potentialities. (C) 2016 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据