Force-directed hybrid PSO–SNTO algorithm for acoustic source localization in sensor networks

As a smart combination of particle swarm optimization (PSO) and sequential number-theoretic optimization (SNTO), a new hybrid PSO–SNTO algorithm is proposed to handle the initialization dependence of basic PSO algorithm. We then apply the hybrid algorithm to the acoustic source localization problem...

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Bibliographic Details
Published in:	Signal processing Vol. 89; no. 8; pp. 1671 - 1677
Main Authors:	Yu, Zhijun, Wei, Jianming, Liu, Haitao
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 01.08.2009 Elsevier
Subjects:	Acoustic sources Algorithms Applied sciences Convergence Detection, estimation, filtering, equalization, prediction Exact sciences and technology Information, signal and communications theory Localization Networks Number-theoretic optimization Optimization Particle swarm optimization Position (location) Sensor networks Signal and communications theory Signal, noise Source localization Telecommunications and information theory Virtual force Number-theoretic optimization Virtual force Sensor networks Source localization Particle swarm optimization Performance evaluation Global optimum Acoustic signal detection Sound source Algorithm Biomimetics Algorithm performance Simulation Heuristic method Convergence rate Maximum likelihood Sensor array Target detection Signal detection Number theory
ISSN:	0165-1684, 1872-7557
Online Access:	Get full text
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