Kong Xiangyu1,Han Chongzhao1,Ma Hongguang1,Wei Ruixuan2
(1.School of Electronics and Information Engineering,Xi'an Jiaotong University,Xi'an ¡¡710049,China;2.School of Engineering,Air Force Engineering University,Xi'an 710038,China)
Abstract:Aiming at the filter problem that exists when the input and output signal are both corrupted by noise,a robust total least square adaptive algorithm is proposed. Taking the minimum Rayleigh quotient as the loss function,the recursive formula of weight vector is derived, the stochastic discrete laws are applied to the analysis of the rule of the norm of the weight vector and the gradient is modified,and the robust anti-noise performance is improved.The algorithm is more simple and has excellent stability and high accuracy.The algorithm is applied to the Volterra filter; it still keeps nice convergent performance in the nonlinear systems even when the signal-noise-ratio is 10dB and learning rate is 0.01.The simulation results have also shown that,the robust anti-noise performance and the stable convergence precision of the proposed algorithm are remarkably better than other total least square adaptive algorithms when the signal-noise-ratio is lower or a larger learning factor is used.
Keywords:total least square;Volterra filter;Rayleigh quotient