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Variable Step-Size Least Mean Fourth Adaptive Algorithm: Basics, Concepts and Analysis - Couverture souple

Muhammad Asad, Syed

 
9783639249392: Variable Step-Size Least Mean Fourth Adaptive Algorithm: Basics, Concepts and Analysis
Couverture souple
ISBN 10 : 3639249399 ISBN 13 : 9783639249392
Editeur : VDM Verlag Dr. Müller, 2010

Synopsis

Adaptive ?ltering algorithms have been proposed to improve the performance in terms of their steady-state error and convergence rate. They have also been developed to counter the e?ects of measurement noise characterised as white Gaussian. The Least Mean Square (LMS) algorithm has been by far the most important in terms of its simplicity and range of applications. Thus it has been a centre point of extensive research. In particular, the time-varying step-size models of LMS have contributed immensely in the performance enhancement of LMS algorithm. By comparison the Least Mean Fourth (LMF) algorithm that gives better convergence rate in non-Gaussian noise environment has not been researched in its full spectrum. The aim of this work is to exploit the research in LMS algorithm particularly in the model of time-varying step-size parameter and extend it to the LMF. We have developed a variable step-size LMF algorithm with the aim to achieve better performance than the traditional LMF and retain its inherent dominance over the LMF in non-Gaussian noise environments.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Adaptive ?ltering algorithms have been proposed to improve the performance in terms of their steady-state error and convergence rate. They have also been developed to counter the e?ects of measurement noise characterised as white Gaussian. The Least Mean Square (LMS) algorithm has been by far the most important in terms of its simplicity and range of applications. Thus it has been a centre point of extensive research. In particular, the time-varying step-size models of LMS have contributed immensely in the performance enhancement of LMS algorithm. By comparison the Least Mean Fourth (LMF) algorithm that gives better convergence rate in non-Gaussian noise environment has not been researched in its full spectrum. The aim of this work is to exploit the research in LMS algorithm particularly in the model of time-varying step-size parameter and extend it to the LMF. We have developed a variable step-size LMF algorithm with the aim to achieve better performance than the traditional LMF and retain its inherent dominance over the LMF in non-Gaussian noise environments.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
VDM Verlag Dr. Müller
Date d'édition
2010
Langue
anglais
ISBN 10 
3639249399
ISBN 13 
9783639249392
Reliure
Broché
Nombre de pages
112
Coordonnées du fabricant
non disponible
Personne responsable
non disponible