基于混合智能算法的随机共振微弱信号检测

Stochastic Resonance Weak Signal Detection Based on Hybrid Intelligent Algorithm

针对在随机共振系统参数调节过程中使用单一智能算法导致的搜索结果不够精确的问题,使用了一种基于粒子群算法和人工鱼群算法的混合智能算法实现自适应微弱信号的检测。将两种算法结合起来,回避了粒子群算法调参的过程中极易导致局部最优的这一问题,同时弥补了人工鱼群算法后期搜索不精确的不足。上述方法将随机共振输出信噪比作为混合智能算法的目标函数,仿真结果表明,所提出的方法与多种单一算法以及单一优化算法相比,能够更好地提高微弱信号的检测精度和检测性能。为微弱信号检测提供了一条新的途径。

Aiming at the inaccuracy of the search results caused by the single intelligent algorithm in the parameter adjustment process of stochastic resonance system, a hybrid intelligent algorithm based on particle swarm optimization and artificial fish swarm algorithm is used to realize adaptive weak signal detection. Combining the two algorithms avoids the problem that the particle swarm optimization algorithm is easy to cause local optimization in the process of parameter adjustment, and makes up for the inaccuracy of the artificial fish swarm algorithm in the late search. The stochastic resonance output signal-to-noise ratio was used as the objective function of the hybrid intelligent algorithm. The simulation results show that thedetection accuracy and detection performance of weak signals are improvedvia the proposed method and better than many single algorithms and single optimization algorithms, whichprovides a new way for weak signal detection.