A Variable Step-Size SIG Algorithm for Realizing the Optimal Adaptive FIR Filter

نویسندگان

  • Badong Chen
  • Yu Zhu
  • Jinchun Hu
  • Jose C. Principe
چکیده

Abstract: In this paper, we propose an optimal adaptive FIR filter, in which the step-size and error nonlinearity are simultaneously optimized to maximize the decrease of the mean square deviation (MSD) of the weight error vector at each iteration. The optimal step-size and error nonlinearity are derived, and a variable step-size stochastic information gradient (VS-SIG) algorithm is developed to approximately implement the optimal adaptation. Simulation results indicate that this new algorithm achieves faster convergence rate and lower misadjustment error in comparison with other adaptive algorithms.

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تاریخ انتشار 2011