Ebook: QRD-RLS adaptive filtering

QRD-RLS Adaptive Filtering covers some of the most recent developments as well as the basic concepts for a complete understanding of the QRD-RLS-based adaptive filtering algorithms. It presents this research with a clear historical perspective which highlights the underpinning theory and common motivating factors that have shaped the subject.

The material is divided into twelve chapters, going from fundamentals to more advanced aspects. Different algorithms are derived and presented, including basic, fast, lattice, multichannel and constrained versions. Important issues, such as numerical stability, performance in finite precision environments and VLSI oriented implementations are also addressed. All algorithms are derived using Givens rotations, although one chapter deals with implementations using Householder reflections.

QRD-RLS Adaptive Filtering is a useful reference for engineers and academics in the field of adaptive filtering.

This book provides tools and knowledge in a simple way such that the reader is able to implement a particular QRD-RLS algorithm tailored for the application at hand. The material presents not only classical and recent research results but also the expertise of a number of authors that have contributed to the development of this fast converging class of adaptive filter algorithms. The intended audience encompasses graduate students, researchers, and practitioners working in the field of adaptive filtering or in need of using a robust and fast converging algorithm.