This paper presents a modified version of the twostep least-mean-square (LMS)-type adaptive algorithm motivated by the work of Gazor. We describe the nonstationary adaptation characteristics of this modified two-step LMS (MG-LMS) algorithm for the system identification problem. It ensures stable behavior during convergence as well as improved tracking performance in the smoothly time-varying environments.

TrackingofTimeVaryingChannelsUsingTwoStepLMSTypeAdaptiveAlgorithm.pdf

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