Adaptive Stochastic Resonance Method Based on Artificial-fish Swarm Optimization

KONG De-yang; PENG Hua; MA Jin-quan

doi:10.3969/j.issn.0372-2112.2017.08.009

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Adaptive Stochastic Resonance Method Based on Artificial-fish Swarm Optimization

更新时间：2025-07-16

- Adaptive Stochastic Resonance Method Based on Artificial-fish Swarm Optimization
- Acta Electronica Sinica Vol. 45, Issue 8, Pages: 1864-1872(2017)
- 作者机构：
  
  解放军信息工程大学信息系统工程学院,河南,郑州,450002
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61401511)
- DOI：10.3969/j.issn.0372-2112.2017.08.009
  CLC： TN911.7
- Published Online：25 August 2017，
  
  Published：2017
- 稿件说明：
移动端阅览
KONG De-yang, PENG Hua, MA Jin-quan. Adaptive Stochastic Resonance Method Based on Artificial-fish Swarm Optimization[J]. Acta Electronica Sinica, 2017, 45(8): 1864-1872.
DOI：

KONG De-yang, PENG Hua, MA Jin-quan. Adaptive Stochastic Resonance Method Based on Artificial-fish Swarm Optimization[J]. Acta Electronica Sinica, 2017, 45(8): 1864-1872. DOI： 10.3969/j.issn.0372-2112.2017.08.009.

摘要

随机共振为微弱通信信号的检测提供了新途径.本文提出一种基于人工鱼群算法的自适应随机共振新方法，重点研究基于随机共振的微弱周期信号检测技术，将人工鱼群算法和归一化处理结合增强随机共振，适当添加噪声并设定自适应步长策略及迭代停止条件.理论分析和仿真结果表明，对比传统群智能算法处理随机共振其在算法适应性及稳定性、最佳共振精确度、寻优收敛速度、精度方面有明显提升，并为信噪比增益带来3-5dB的提升，运算时间复杂度降低逾70%.

Abstract

Stochastic resonance provided new ways detecting weak communication signals.A new method based on artificial-fish swarm optimization is proposed whose emphasis is on weak periodic signal detection based on stochastic resonance.Artificial-fish swarm optimization is combined with normalization of stochastic resonance.Noise is utilized by adding it to the signal while new adaptive step strategy and iteration stopping strategy are also used.The results of theoretical analysis and simulation experiments show this proposed method have great promotions on adaptability

stability

precision of the optimal resonance and the convergence speed

as well as a great promotion of 3-5dB on SNR gain compared with traditional stochastic resonance based on swarm optimization.Meanwhile

the time complexity of calculation is decreased by 70%.

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