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Information loss in deterministic si...

Geiger, Bernhard C.

Information loss in deterministic signal processing systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Information loss in deterministic signal processing systemsby Bernhard C. Geiger, Gernot Kubin.
作者:	Geiger, Bernhard C.
其他作者:	Kubin, Gernot.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	xiii, 145 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Signal processingDigital techniques
電子資源:	http://dx.doi.org/10.1007/978-3-319-59533-7
ISBN:	9783319595337$q(electronic bk.)

Information loss in deterministic signal processing systems
Geiger, Bernhard C.

Information loss in deterministic signal processing systems[electronic resource] /by Bernhard C. Geiger, Gernot Kubin. - Cham :Springer International Publishing :2018. - xiii, 145 p. :ill. (some col.), digital ;24 cm. - Understanding complex systems,1860-0832. - Understanding complex systems..

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.

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.

ISBN: 9783319595337$q(electronic bk.)

Standard No.: 10.1007/978-3-319-59533-7doiSubjects--Topical Terms:

184837
Signal processing
--Digital techniques

LC Class. No.: TK5102.9

Dewey Class. No.: 621.3822

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