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ADAPTIVE FILTRING

Platform : DSP

IEEE Projects Years : 1997

This paper appears in: Signal Processing Letters, IEEE Issue Date: Feb 1997 AIM: TO VERIFY THE AUTOMATED VERSION OF FILTERING OVER A SPEECH SIGNAL ABSTRACT We propose a new member of the family of mixed-norm stochastic gradient adaptive filter algorithms for system identification applications based upon a convex function of the error norms that underlie the least mean square (LMS) and least absolute difference (LAD) algorithms. A scalar parameter controls the mixture and relates, approximately, to the probability that the instantaneous desired response of the adaptive filter does not contain significant impulsive noise. The parameter is calculated with the complementary error function and a robust estimate of the standard deviation of the desired response. The performance of the proposed algorithm is demonstrated in a system identification simulation with impulsive and Gaussian measurement noise LEARNING OBJECTIVE : To understand about creating speech file from microphone and processing it with on real time filtring. INPUT: Input speech file created from real time microphone. OUTPUT: Simulated speech signal modified from the input speech file in terms of time and Amplitude. APPLICATIONS: Speech Signal Processing SOFTWARE USED: MATLAB2007A

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