Comparative Analysis of State-Space Least Mean Square Technique with Variable Step-Size Algorithms for Noise and Disturbance Resilience

Muhammad Tahir*; Abdul Sattar; Sara Mushtaque; Aqsa Zehra; Muhammad Farhan Siddiqui; Abdullah Jamshaid

Authors

Muhammad Tahir* Graduate School of Science and Engineering (Electronics), Karachi, Institute of Economics and Technology (KIET), Karachi, Pakistan
Abdul Sattar Department of Electronics, University of Larkano
Sara Mushtaque School of Mechanical and Manufacturing Engineering, National University of Science and Technology, Islamabad, Pakistan
Aqsa Zehra Graduate School of Science and Engineering (Electronics), Karachi, Institute of Economics and Technology (KIET), Karachi, Pakistan
Muhammad Farhan Siddiqui School of Interdisciplinary Engineering & Sciences (SINES), National University of Sciences & Technology (NUST), Islamabad,
Abdullah Jamshaid US Pakistan Center for Advance Studies in Energy (USPCAS-E), University of Engineering & Technology (UET), Peshawar

Abstract

The state-space least mean square technique with variable step-size algorithms. SSLMS assimilates time-varying behavior because of the disruptions from the surrounding environment. Consequently, in comparison to conventional LMS, SSLMS presents an enhanced performance compared entirely dependent on external noise, varying behavior of measured signals and transient disturbances. The step size plays a prominent role to minimize the error. Due to the absence of uncertainties, it is pretty typical to propose a feasible step-size parameter. To overcome the challenge, we applied three different variable step size algorithms resulting in modified step size and provides minimum mean square error compared to fixed step size SSLMS.

Keywords: State-Space Least Mean Square (SSLMS), Variable Step-Size Algorithms, Transient Disturbances, Mean Square Error Minimization, Time-Varying Behavior