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针对RLS自适应算法中固定遗忘因子在不同信道条件下的无法使每种信道的滤波效果达到最优的问题,提出运用遗传算法对遗忘因子进行寻优,通过MATLAB对信号在多径衰落条件下RLS滤波器的遗忘因子寻优仿真,解决了对于RLS滤波器在不同信噪比条件下的最优遗忘因子该如何确定的问题,并且通过最优遗忘因子和非最优遗忘因子的RLS滤波器滤波的仿真结果对比,得出最优遗忘因子的RLS滤波器的收敛速率显著优于非最优遗忘因子RLS滤波器的结论。
Aiming at the problem that the fixed forgetting factor in RLS adaptive algorithm can not optimize the filtering effect of each channel under different channel conditions, a genetic algorithm is proposed to optimize the forgetting factor. The signal is filtered by MATLAB under the condition of multipath fading RLS filter forgetting factor optimization simulation to solve the RLS filter in the different signal to noise ratio under the conditions of the optimal forgetting factor how to determine the problem, and through the optimal forgetting factor and non-optimal forgetting factor RLS filter The simulation results show that the convergence rate of the RLS filter with the best forgetting factor is significantly better than the non-optimal forgetting factor RLS filter.