Speech Enhancement using Combinational Adaptive LMS Algorithms

The key to successful adaptive signal processing understands the fundamental properties of adaptive algorithms like LMS. Adaptive filter is used for the cancellation of the noise component (in the Speech and acoustic signal processing )which is overlap with undesired signal in the same frequency range, but fixed LMS algorithm produces minimum convergence rate and fixed steady state error. So the authors present design, implementation and performance of adaptive FIR filter, based on variations in LMS algorithm, which produces better convergence rate and minimum steady state error compare to fixed LMS, and they also obtains denoised signal at output, and also they propose to calculate SNR values of Adaptive Filter with LMS algorithms and comparison is made among the LMS algorithms.