量子人工鱼群优化的随机共振微弱信号检测

Weak Signal Detect Method Based on Quantum Artificial Fish Swarm Optimization Stochastic Resonance

针对传统随机共振方法微弱信号检测精度低、速度慢的问题,将量子人工鱼群算法应用到随机共振方法中,提出一种量子人工鱼群算法的随机共振微弱信号检测方法.方法以随机共振系统参数为研究对象,将随机共振问题转化为多参数同步寻优问题,实现微弱信号的增强.分别在Langevin与Duffing系统中仿真,表明所提方法高效可行.同一输入条件下,Duffing随机共振微弱信号检测性能优于Langevin系统.加入控制频率,将Duffing随机共振应用到多频大信号的检测,扩展了随机共振的应用范围.

Traditionally, the detection method has low accuracy and slow speed. Therefore, the quantum artificial fish swarm algorithm was applied to the stochastic resonance method, and a method to detect weak signals in stochastic resonance based on quantum artificial fish swarm algorithm was proposed. This method took stochastic resonance system parameters as the research target and converted the stochastic resonance into multi-parameter synchronous optimization, and thus to achieve the enhancement of weak signal. Respectively, the simulation was carried out in Langevin system and Duffing system. The results show that the proposed method is efficient and feasible, and under the same condition of input signal, Duffing stochastic resonance weak signal detection performance is better than that of Langevin system. After adding the control frequency, Duffing stochastic resonance was applied to the detection of multi-frequency large signal, so that the application scope of stochastic resonance was expanded.