一种基于经典遗传算法的自适应随机共振系统

针对实际工程中微弱信号的检测要求，根据双稳态随机共振系统原理和信号、噪声和非线性系统之间的关系，设计了一种基于经典遗传算法的自适应随机共振系统。该系统利用以输出信噪比为目标函数和对系统参数进行联合编码的遗传算法获取双稳态随机共振系统的最佳参数，再根据所得系统参数对接收信号进行最优随机共振处理。仿真结果表明，在低信噪比情况下，系统能始终保持最佳随机共振状态，快速地实现输出信噪比最大化和处理增益达到15~20dB，从而保证低信噪比条件下微弱信号的有效检测和处理。

Adaptive Stochastic Resonance System Based on Standard Genetic Algorithm

According to the demand of weak signal detection in actual engineering, an adaptive stochastic resonance system was designed utilizing standard genetic algorithm(SUA) based on the principle of bistable resonance systems and relationships among signal, noise and the nonlinear system. Through genetic algorithm using output signal-to-noise-ratio (SNR) as objective function and binary joint coding of system parameters, the optimal parameters of bistabile stochastic resonance were identified. Then,received signal was proceeded by making use of optimal stochastic resonance parameters. Simulation results show that the adaptive system designed can always maintain in an optimal state of stochastic resonance to achieve the maximum output SNR and processing gain to 15~20dB quickly. Therefore it ensures effective detection and processing of weak signal in low SNR.