Titlebook: Adaptive Signal Processing; Theory and Applicati S. Thomas Alexander Book 1986 Springer-Verlag New York Inc. 1986 Signal.bridge.communicati

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The Mean Square Error (MSE) Performance Criteria,cking the autofluorescence through filters or it is based on nanomaterials with long lifetimes, filtering autofluorescence through a time delay. The second group of approaches avoids the occurrence of autofluorescence either through the absence of excitation radiation (bioluminescence, chemiluminesc

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The Least Mean Squares (LMS) Algorithm,age and frequency allocation schemes. We propose three aggressive NTC voltage tuning and allocation strategies, showing that performance can be efficiently sustained or even optimized at the NTC regime. Finally, we show that NTC highly depends on the underlying workload characteristics, delivering a

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Gradient Adaptive Lattice Methods,en nanometric particles has opened new ways to nanometric optical science and technology, and many applications to nanometric fabrication and manipulation have been proposed and implemented. Building on this historical background, this book describes recent progress in near-field optical science and technolog978-1-4613-7192-2978-1-4615-4835-5

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Chapter 8 Recursive Least Squares Signal Processing, NIR spectroscopy. Selected examples from recent literature are included to demonstrate how these methods can be applied to solve practical problems in spectroscopy. The aim of this chapter is to provide a comprehensive presentation of the topic aimed at a spectroscopic audience, while remaining acc

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The Least Squares Lattice Algorithm,M, +) satisfying r(m + a) — rm ( A for all r ( R, m ( M, a ( A. Submodules of .R are left ideals of R. If A is a left ideal of R and AR = {ar | a ( A,r ( R} ⊂ A, then A is an ideal of R. For any subset B of an R-module M the set {r ( R | rB = (0)} is called the left annihilator of B, denoted by l(B)

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