Introducing Adaptive filters Based on Shadow Concept for Speech Processing

Abstract

This paper presents the new approach to introducing adaptive Filter with LMS Algorithm based on Shadow concept. Which is useful for the cancellation of the noise component overlap with Speech signal in the same frequency range, but fixed LMS algorithm produces minimum convergence rate and fixed steady state error. So we presents design, implementation and performance  of adaptive FIR filter, based on  Shadow concept, which produces minimum mean square error compare to fixed LMS, and we also obtains denoised Speech signal at output, and also we propose to calculate SNR values of  Adaptive Filter with LMS algorithm with and without Shadow concept.