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Publisher's Note: Products purchased from Third Party sellers are
not guaranteed by the publisher for quality, authenticity, or
access to any online entitlements included with the product. A
no-nonsense guide to the fundamentals and applications of
statistical signal processing Ideal for upper-undergraduate and
graduate courses, this engineering textbook offers key signal
analysis principles and uses and explains the necessary underlying
mathematics. Coverage includes representation and approximation
theory in vector spaces, the orthogonality principle, the least
squares problem, minimum mean square estimation, and the
Wiener-Hopf equation. Signal Analysis: A Concise Guide clearly
explains linear systems and signals and the concepts behind them.
The book covers matrix factorizations, optimal linear filter
theory, classical and modern spectral estimation, adaptive filters,
and processing of spatial arrays. You will also explore linear
optima filters, eigrn decomposition methods, the singular value
decomposition, adaptive linear filters, noise cancellation, and
spectral estimation. * Includes exercises for computer
implementation using MATLAB * Presents the core material in a
succinct format * Written by a team of renowned academics with
multiple teaching awards
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