SUMMARYA new LMS based variable step size adaptive algorithm is presented. The step size is incremented or decremented by a small positive value, whenever the instantaneous error is positive or negative, respectively. The algorithm is simple, robust and e cient. It is characterized by fast convergence and low steady state mean squared error. The performance of the algorithm is analysed for a stationary zeromean white-Gaussian input. MC simulations are provided to demonstrate its improved performance over the conventional LMS (Proc. IEEE 1976; 64:1151-1162) and some other variable step size adaptive algorithms (IEEE Trans. Signal Process. 1992; 40:1633-1642 IEEE Trans. Signal Process. 1997; 45:631-639) within a range of statistical environments. For a non-stationary input, the proposed algorithm behaves similar to these algorithms. A modiÿed version of the algorithm is presented to perform in the presence of abrupt changes.
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