Information Loss in Deterministic Signal Processing Systems (Record no. 75205)

000 -LEADER
fixed length control field 03856nam a22006015i 4500
001 - CONTROL NUMBER
control field 978-3-319-59533-7
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801213448.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 170703s2018 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319595337
-- 978-3-319-59533-7
082 04 - CLASSIFICATION NUMBER
Call Number 515.39
100 1# - AUTHOR NAME
Author Geiger, Bernhard C.
245 10 - TITLE STATEMENT
Title Information Loss in Deterministic Signal Processing Systems
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2018.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIII, 145 p. 16 illus., 9 illus. in color.
490 1# - SERIES STATEMENT
Series statement Understanding Complex Systems,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Part I: Random Variables -- Piecewise Bijective Functions and Continuous Inputs -- General Input Distributions -- Dimensionality-Reducing Functions -- Relevant Information Loss -- II. Part II: Stationary Stochastic Processes -- Discrete-Valued Processes -- Piecewise Bijective Functions and Continuous Inputs -- Dimensionality-Reducing Functions -- Relevant Information Loss Rate -- Conclusion and Outlook.
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Kubin, Gernot.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-319-59533-7
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2018.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Dynamics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Nonlinear theories.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- System theory.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Applied Dynamical Systems.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing .
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Complex Systems.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1860-0840
912 ## -
-- ZDB-2-ENG
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-- ZDB-2-SXE

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