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.
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Majeed Seidu Gengen is a Communication Engineer with interests spanning Digital Signal Processing, Digital Communications, Python development, network security, and cybersecurity. He holds a Master of Science in Engineering from Carinthia University of Applied Sciences, Austria and is passionate about adaptive DSP systems.
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Paperback. Zustand: new. Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786630137163
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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. 112 pp. Englisch. Bestandsnummer des Verkäufers 9786630137163
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