Description
This comprehensive text provides an in-depth exploration of adaptive filtering theory and its diverse applications across engineering and signal processing fields. The book bridges the gap between theoretical foundations and practical implementations, making it an essential resource for students, researchers, and practitioners.
The content covers fundamental adaptive filtering algorithms including LMS, RLS, and Kalman filtering approaches, along with their computational aspects and convergence properties. Each chapter includes detailed mathematical derivations and illustrative examples that demonstrate how these techniques solve real-world problems in communications, audio processing, biomedical engineering, and control systems.
With contributions from expert authors and InTech’s rigorous peer-review process, this 2017 hardcover edition ensures accessibility to both beginners and advanced practitioners seeking to understand and implement state-of-the-art adaptive filtering solutions in their respective domains.
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