Stochastic Resonance Based on PSO with Applications in Multiple Line-Spectrums Detection

Zhi-kai Fu (), Jian-chun Xing, Shuang-qing Wang and Qi-liang Yang
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Zhi-kai Fu: PLA University of Science and Technology
Jian-chun Xing: PLA University of Science and Technology
Shuang-qing Wang: PLA University of Science and Technology
Qi-liang Yang: PLA University of Science and Technology

A chapter in Proceedings of 20th International Conference on Industrial Engineering and Engineering Management, 2013, pp 419-427 from Springer

Abstract: Abstract Based on the deficiency of the traditional stochastic resonance method in multi-parameters optimization and the difficulty of adaptive stochastic resonance with genetic algorithm in multiple line-spectrums detection, a new method of adaptive swept stochastic resonance based on particle swarm optimization (PSO) is proposed. The signal-noise-ratio (SNR) of outputs of bistable system is determined as the fitness function of PSO and the line-spectrum can be detected by the synchronous optimization of multi-parameters. Simultaneously, the adaptive swept stochastic resonance, combined with twice sampling algorithm and PSO algorithm, achieves the detection of multiple line-spectrums. The simulation results show that the proposed method can detect multiple line- spectrums signal effectively, and has advantages of simplicity and fast convergence speed.

Keywords: Line-spectrum detection; Particle swarm optimization; Stochastic resonance; Twice sampling (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-40063-6_42

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DOI: 10.1007/978-3-642-40063-6_42

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