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Explains the fundamentals of adaptive filtering supported by numerous examples and computer simulations. This book introduces discrete-time signal processing, random variables and stochastic processes, the Wiener filter, properties of the error surface, the steepest descent method, and the least mean square (LMS) algorithm.

Suitable for engineering and science students, professionals, and those working on problems involving transforms, this title provides a large number of examples to explain the use of transforms in different areas, including circuit analysis, differential equations, signals and systems, and mechanical vibrations.

Explains the fundamentals of adaptive filtering supported by numerous examples and computer simulations. This book introduces discrete-time signal processing, random variables and stochastic processes, the Wiener filter, properties of the error surface, the steepest descent method, and the least mean square (LMS) algorithm.