Proportionate-Type Normalized Least Mean Square Algorithms (BOK)
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Proportionate-type normalized least mean square (PtNLMS) offer low computational complexity and fast convergence times, for sparse impulse responses in network and acoustic echo cancellation applications. Introducing this important subject, this book then develops and analyzes these algorithms. It shows how new PtNLMS algorithms are developed by choosing gains that optimize user-defined criteria, such as mean square error, at all times. It also explains how PtNLMS algorithms are extended from real-valued signals to complex-valued signals. The computational complexity of the presented algorithms is examined.