Information Loss in Deterministic Signal Processing Systems (Hardcover, 1st ed. 2018)

This book introduces readers to essential tools for the measurement and analysis of information loss in signal processing systems. Employing a new information-theoretic systems theory, the book analyzes various systems in the signal processing engineer's toolbox: polynomials, quantizers, rectifiers, linear filters with and without quantization effects, principal components analysis, multirate systems, etc. The user benefit of signal processing is further highlighted with the concept of relevant information loss. Signal or data processing operates on the physical representation of information so that users can easily access and extract that information. However, a fundamental theorem in information theory-data processing inequality-states that deterministic processing always involves information loss. These measures form the basis of a new information-theoretic systems theory, which complements the currently prevailing approaches based on second-order statistics, such as the mean-squared error or error energy. This theory not only provides a deeper understanding but also extends the design space for the applied engineer with a wide range of methods rooted in information theory, adding to existing methods based on energy or quadratic representations.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Understanding Complex Systems
Release date:	July 2017
First published:	2018
Authors:	Bernhard C. Geiger • Gernot Kubin
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	145
Edition:	1st ed. 2018
ISBN-13:	978-3-319-59532-0
Categories:	Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Books > Science & Mathematics > Physics > Thermodynamics & statistical physics > Statistical physics Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General Promotions
LSN:	3-319-59532-6
Barcode:	9783319595320

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