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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Paperback. Condición: 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 multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9786630137163
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 112 pp. Englisch. Nº de ref. del artículo: 9786630137163
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9786630137163
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Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: 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. Nº de ref. del artículo: 9786630137163
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Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Development Adaptive Solution for DSP/DC Related Applications | System Identification, Adaptive Equalization, and DC-Offset Compensation Using LMS-Based Algorithms | Gengen Seidu Majeed | Taschenbuch | Englisch | 2026 | Scholars' Press | EAN 9786630137163 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 135975426
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9786630137163
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