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Adaptive Filtering Therories And Applications
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An adaptive ?lter is a computational device that iteratively models the relationship between the input and output signals of the ?lter. An adaptive ?lter self-adjusts the ?lter coe?cients according to an adaptive algorithm. Over the past three decades, digital signal processors have made great advances in increasing speed and complexity, and reducing power consumption. As a result, real-time adaptive ?ltering algorithms are quickly becoming practical and essential for the future of communications, both wired and wireless. An adaptive ?lter designs itself based on the characteristics of the input signal to the ?lter and a signal that represents the desired behaviour of the ?lter on its input. Because of the complexity of the optimization algorithms, almost all adaptive ?lters are digital ?lters. Adaptive ?lters are required for some applications because some parameters of the desired processing operation are not known in advance or are changing. The closed loop adaptive ?lter uses feedback in the form of an error signal to re?ne its transfer function. Adaptive ?ltering can be used to characterize unknown systems in time-variant environments. Commonly, the closed loop adaptive process involves the use of a cost function, which is a criterion for optimum performance of the ?lter, to feed an algorithm, which determines how to modify ?lter transfer function to minimize the cost on the next iteration. The most common cost function is the mean square of the error signal. This book, Adaptive Filtering - Theories and Applications, o?ers some theoretical approaches and practical applications in diverse areas that support increasing of adaptive systems. The book re?ect the latest advances in this ?eld; particularly an increased coverage given to the practical applications of the theory to illustrate the much broader range of adaptive ?lters applications developed in recent years.

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Author(s)Lefteris Tyler
Publish YearFebruary 2017
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