Development Adaptive Solution for DSP/DC Related Applications: System Identification, Equalization, and DC-Offset Compensation Using LMS-Based Algorithms

This book explores the development and evaluation of adaptive filtering techniques for Digital Signal Processing (DSP) and Digital Communication (DC) applications. It focuses on three widely used adaptive algorithms: Standard LMS, Sign-LMS, and Sign-Sign LMS, implemented using MATLAB and Simulink for system identification and channel equalization tasks.The work investigates how these algorithms adaptively model unknown systems, compensate for signal distortions, and operate under practical conditions such as noise and DC offsets. Their convergence behavior, computational complexity, and steady-state performance are compared to identify the trade-offs between accuracy and implementation efficiency.Special attention is given to resource-constrained embedded systems, where computational cost, power consumption, and hardware simplicity are critical design factors. The findings provide practical guidelines for selecting suitable adaptive filtering algorithms in modern communication systems, signal processing applications, and real-time embedded DSP platforms.