Author : Ashish Agrawal 1
Date of Publication :7th December 2015
Abstract: The appropriate choice of the convergence factor in the Least Mean Square (LMS) and recursive least-squares (RLS) algorithm with the forgetting factor in the are key to assuring good performance for the adaptive filter. These choices are environment dependent and optimal ked values for these factors are difficult to determine especially in non stationary environments (High Noise). In this paper, 3 adaptive filtering algorithms with variable convergence factor are analyzed. We compare Least Mean Square algorithm (LMS), Recursive Means Square algorithm (RMS) and our proposed algorithm. The relations of these algorithms with the conventional LMS algorithm are first addressed. Their performance in stationary and non stationary environments is studied and then compare with one exiting and one proposed algorithm. Our Proposed algorithm reduces the noise effect and MSE on signal and gives better desired output as compare to existing algorithms. The paper concludes with experimental results analysis presented. Keywords: Static hand gesture, Fourier Descriptors, Support Vector Machine, Classification Accuracy.
Reference :
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