Name: Sparse Adaptive Filtering Techniques for Channel Estimation (en Inglés)
SKU: 62655182
Price: 52.45 USD
Availability: InStock
Author: Muhammad Lawan Aliyu; Mohammad Shukri Salman
ISBN: 9783659468759

portada Sparse Adaptive Filtering Techniques for Channel Estimation (en Inglés)

Sparse Adaptive Filtering Techniques for Channel Estimation (en Inglés)

Formato

Libro Físico

Editorial

Lap Lambert Academic Publishing

Autor

Muhammad Lawan Aliyu; Mohammad Shukri Salman

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

ISBN13

9783659468759

Sparse Adaptive Filtering Techniques for Channel Estimation (en Inglés)

Muhammad Lawan Aliyu; Mohammad Shukri Salman (Autor) · Lap Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Sparse Adaptive Filtering Techniques for Channel Estimation (en Inglés)"

Recently, sparse signal approximation has become an increasingly important research area in signal processing. It attracts a lot of interest due to its wide range of practical applications. In this work, a novel adaptive filtering algorithm with relative low computational complexity that is capable of exploiting the sparsity of systems is proposed. The basic idea here is, we adopt a p-norm constraint in the cost function of the variable step-size least mean square (VSSLMS) algorithm. This constrain imposes a zero attraction at each filter coefficient based on their respective relative value. Also, the convergence analysis of the proposed algorithm is presented and the stability condition is derived. The performance of the proposed algorithm has been compared to those of the Zero Attraction Least Mean Square(ZA-LMS), windowing ZA-LMS(wZA-LMS), Non-uniform Norm Constraint LMS(NNCLMS) in a system identification setting for different additive Gaussian noise(AGN), additive correlated noise(ACN)and additive impulsive noise(AIN) environments. The proposed algorithm has always shown superior performance to the others with less or comparable number of computations