A New VSLMS Algorithm for Performance Analysis of Self Adaptive Equalizers

The fundamental feature of the LMS Least Mean Squares algorithm is the step size, and it involvesa cautious adjustment. Large step size may lead to loss of stability which are required for fast adaptation. Small step size leads to low convergence which are needed for insignificant excess mean square error. Consequently, several changes of the LMS algorithm in which the step size modifications are made throughout the adaptation method which depend on certain specific features, were and are still under development. A new variable step size LMS algorithm is examined to solve the problem of LMS algorithm. The algorithm will be based on the sigmoid function which develops the non linear functional relation among error and step. The algorithm solves the problem of setting parameters in the function by introducing the error feedback strategy to adjust the parameters adaptively. Compared with other algorithms, simulation results show that the algorithm performs perfect at convergence rate and steady state error with a better applicability. B. R. Kavitha | P. T. Jamuna Devi "A New VSLMS Algorithm for Performance Analysis of Self Adaptive Equalizers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38229.pdf Paper URL : https://www.ijtsrd.com/computer-science/computer-network/38229/a-new-vslms-algorithm-for-performance-analysis-of-self-adaptive-equalizers/b-r-kavitha