Adaptive Filtering Under Minimum Mean p-Power Error Criterion

This book provides a detailed introduction to the minimum mean p-power error criterion, enhancing the understanding of adaptive filtering techniques.

The book Adaptive Filtering Under Minimum Mean p-Power Error Criterion offers a thorough exploration of the minimum mean p-power error (MMPE) criterion as an extension of the traditional minimum mean square error (MMSE). It highlights the advantages of using MMPE in adaptive filtering applications, demonstrating its superior performance in various fields such as communications, signal processing, and control engineering. The authors aim to provide a comprehensive introduction to MMPE and its related algorithms, ensuring that readers gain a solid understanding of this important topic.

Adaptive filtering remains a crucial area in engineering due to its ability to outperform fixed filters in environments characterized by time-varying and unknown statistics. While the MMSE criterion is widely recognized, it is primarily optimal for Gaussian-distributed signals. The book addresses the limitations of MMSE and illustrates how MMPE can serve as a more effective alternative. By presenting a systematic description of the MMPE criterion, the authors equip readers with the tools needed to apply these concepts in practical scenarios.

Designed for senior undergraduates, graduate students, and practitioners, Adaptive Filtering Under Minimum Mean p-Power Error Criterion emphasizes a foundational understanding of linear algebra and statistics. Throughout the text, numerous adaptive filtering algorithms, both linear and nonlinear, are introduced alongside extensive illustrative examples, making it an invaluable reference for anyone interested in the field of adaptive signal processing.