Signed Regressor Least Mean Fourth (SRLMF) Adaptive Algorithm

Name: Signed Regressor Least Mean Fourth (SRLMF) Adaptive Algorithm
Brand: VDM Verlag
SKU: 9783639262629
Price: 51.06 EUR
Availability: InStock

Автор: Mohammed Mujahid Ulla Faiz

Език:

Корици: С меки корици

Издател: VDM Verlag

Наличност: Налично при издателя, по поръчка

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In this book, a novel algorithm, called the signed regressor least mean fourth (SRLMF) adaptive algo...

Информация за книгата

Автор

Mohammed Mujahid Ulla Faiz

Език

Английски език

Корици

Книга - С меки корици

Издадена

2010

страници

EAN

9783639262629

ISBN

363926262X

Enbook ID

06833603

Издател

VDM Verlag

Теглоt

136

Размери

152 x 229 x 5

Пълно описание

In this book, a novel algorithm, called the signed regressor least mean fourth (SRLMF) adaptive algorithm, that reduces the computational cost and complexity while maintaining good performance is presented. Expressions are derived for the steady-state excess-mean-square error (EMSE) of the SRLMF algorithm in a stationary environment. Also, expressions are obtained for the tracking EMSE of the SRLMF algorithm in a non-stationary environment. An optimum value of the step-size is also derived. Moreover, the weighted variance relation has been extended in order to derive expressions for the mean-square error (MSE) and the mean-square deviation (MSD) of the proposed algorithm during the transient phase. Computer simulations are carried out to corroborate the theoretical findings. It is shown that there is a good match between the theoretical and simulated results. It is also shown that the SRLMF algorithm has no performance degradation when compared with the least mean fourth (LMF) algorithm. The results in this study emphasize the usefulness of this algorithm in applications requiring reduced implementation costs for which the LMF algorithm is too complex.

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Signed Regressor Least Mean Fourth (SRLMF) Adaptive Algorithm

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