A fast robust LMS algorithm utilizing the dynamics of a damped pendulum

A new fast LMS-based adaptive algorithm is proposed. It is derived by incorporating a damping force in the LMS update recursion in analogy with the force acting upon a damped planar pendulum. An expression for the evolution and the steady-state behaviour for the mean weight vector is developed. This expression provides a mathematical bound which constrains the parameter that controls the maximum contribution of the introduced damping force. Simulation results show an improved robust performance for the new algorithm as compared with the conventional LMS algorithm in smoothly tracking the optimal solution in correlated and nonstationary power environments, especially, in the presence of plant noise