电子学报2017，Vol.45Issue(8)：1864-1872,9.DOI:10.3969/j.issn.0372-2112.2017.08.009
基于人工鱼群算法的自适应随机共振方法研究
Adaptive Stochastic Resonance Method Based on Artificial-Fish Swarm Optimization
摘要
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%.关键词
随机共振/人工鱼群算法/归一化处理/自适应步长Key words
stochastic resonance/artificial-fish swarm optimization/normalization method/adaptive step分类
信息技术与安全科学引用本文复制引用
孔德阳,彭华,马金全..基于人工鱼群算法的自适应随机共振方法研究[J].电子学报,2017,45(8):1864-1872,9.基金项目
国家自然科学基金(No.61401511) （No.61401511）
