1.

Record Nr.

UNISALENTO991000694029707536

Autore

Anastassiou, George A.

Titolo

Approximation, probability, and related fields / edited by George Anastassiou and Svetlozar T. Rachev

Pubbl/distr/stampa

New York ; London : Plenum Press, c1994

ISBN

030644724X

Descrizione fisica

xiii, 454 p. ; 26 cm.

Classificazione

AMS 41-06

AMS 60-06

QA221.A643

Altri autori (Persone)

Rachev, Svetlozar Todorov

Disciplina

511.4

Soggetti

Approximation theory - Congresses

Probability theory - Congresses

Stochastic processes - Congresses

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes bibliographical references and index.

"Proceedings of a Conference on Approximation, Probability, and Related Fields, held May 20-22, 1993, in Santa Barbara, California" - T.p. verso



2.

Record Nr.

UNICAMPANIAVAN0114979

Autore

Davis, John H.

Titolo

Methods of applied mathematics with a software overview / Jon H. Davis

Pubbl/distr/stampa

[Basel], : Birkhäuser, : Springer, 2016

Titolo uniforme

Methods of applied mathematics with a MATLAB overview

Edizione

[2. ed]

Descrizione fisica

XVII, 781 p. : ill. ; 24 cm

Soggetti

35-XX - Partial differential equations [MSC 2020]

42Axx - Harmonic analysis in one variable [MSC 2020]

30-XX - Functions of a complex variable [MSC 2020]

65Mxx - Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems [MSC 2020]

34-XX - Ordinary differential equations [MSC 2020]

44-XX - Integral transforms, operational calculus [MSC 2020]

33-XX - Special functions [MSC 2020]

00A69 - General applied mathematics [MSC 2020]

35Qxx - Partial differential equations of mathematical physics and other areas of application [MSC 2020]

46Cxx - Inner product spaces and their generalizations, Hilbert spaces [MSC 2020]

42Cxx - Nontrigonometric harmonic analysis [MSC 2020]

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia



3.

Record Nr.

UNINA9910299904603321

Autore

Geiger Bernhard C

Titolo

Information Loss in Deterministic Signal Processing Systems / / by Bernhard C. Geiger, Gernot Kubin

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018

ISBN

3-319-59533-4

Edizione

[1st ed. 2018.]

Descrizione fisica

1 online resource (XIII, 145 p. 16 illus., 9 illus. in color.)

Collana

Understanding Complex Systems, , 1860-0832

Disciplina

621.3822

Soggetti

Computational complexity

Signal processing

Image processing

Speech processing systems

Statistical physics

Dynamics

Complexity

Signal, Image and Speech Processing

Complex Systems

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

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.

Sommario/riassunto

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.