Online Learning And Adaptive Filters
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Principles of Adaptive Filters and Self-learning Systems
Author | : Anthony Zaknich |
Publisher | : Springer Science & Business Media |
Total Pages | : 397 |
Release | : 2005-08-19 |
Genre | : Technology & Engineering |
ISBN | : 1846281210 |
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Teaches students about classical and nonclassical adaptive systems within one pair of covers Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful technology for solving complex nonlinear problems
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