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Randomness and elements of decision ...

Borda, Monica.

Randomness and elements of decision theory applied to signals

Record Type:	Electronic resources : Monograph/item
Title/Author:	Randomness and elements of decision theory applied to signalsby Monica Borda ... [et al.].
other author:	Borda, Monica.
Published:	Cham :Springer International Publishing :2021.
Description:	xvii, 242 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Decision making.
Online resource:	https://doi.org/10.1007/978-3-030-90314-5
ISBN:	9783030903145$q(electronic bk.)

Randomness and elements of decision theory applied to signals
Randomness and elements of decision theory applied to signals[electronic resource] /by Monica Borda ... [et al.]. - Cham :Springer International Publishing :2021. - xvii, 242 p. :ill. (some col.), digital ;24 cm.

Introduction in Matlab -- Random variables -- Probability distributions -- Joint random variables -- Random processes -- Binary pseudo-noise sequence generator -- Markov processes -- Noise in telecommunication systems -- Decision systems in noisy transmission channels -- Audio signals denoising using Independent Component Analysis -- Texture classification based on statistical models -- Histogram equalization -- PCM and DPCM -- NN and kNN supervised classification algorithms -- Supervised deep learning classification algorithms -- Texture feature extraction and classification using the Local Binary Patterns operator.

This book offers an overview on the main modern important topics in random variables, random processes, and decision theory for solving real-world problems. After an introduction to concepts of statistics and signals, the book introduces many essential applications to signal processing like denoising, texture classification, histogram equalization, deep learning, or feature extraction. The book uses MATLAB algorithms to demonstrate the implementation of the theory to real systems. This makes the contents of the book relevant to students and professionals who need a quick introduction but practical introduction how to deal with random signals and processes.

ISBN: 9783030903145$q(electronic bk.)

Standard No.: 10.1007/978-3-030-90314-5doiSubjects--Topical Terms:

183849
Decision making.

LC Class. No.: QA279.4

Dewey Class. No.: 519.542

Randomness and elements of decision theory applied to signals
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245 0 0 $a Randomness and elements of decision theory applied to signals $h [electronic resource] / $c by Monica Borda ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xvii, 242 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Introduction in Matlab -- Random variables -- Probability distributions -- Joint random variables -- Random processes -- Binary pseudo-noise sequence generator -- Markov processes -- Noise in telecommunication systems -- Decision systems in noisy transmission channels -- Audio signals denoising using Independent Component Analysis -- Texture classification based on statistical models -- Histogram equalization -- PCM and DPCM -- NN and kNN supervised classification algorithms -- Supervised deep learning classification algorithms -- Texture feature extraction and classification using the Local Binary Patterns operator.
520 $a This book offers an overview on the main modern important topics in random variables, random processes, and decision theory for solving real-world problems. After an introduction to concepts of statistics and signals, the book introduces many essential applications to signal processing like denoising, texture classification, histogram equalization, deep learning, or feature extraction. The book uses MATLAB algorithms to demonstrate the implementation of the theory to real systems. This makes the contents of the book relevant to students and professionals who need a quick introduction but practical introduction how to deal with random signals and processes.
650 0 $a Decision making. $3 183849
650 0 $a Random variables. $3 199057
650 0 $a Signal processing $x Mathematics. $3 183873
650 1 4 $a Probability and Statistics in Computer Science. $3 274053
650 2 4 $a Operations Research/Decision Theory. $3 273963
650 2 4 $a Signal, Image and Speech Processing. $3 273768
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 348605
700 1 $a Borda, Monica. $3 522522
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856 4 0 $u https://doi.org/10.1007/978-3-030-90314-5
950 $a Physics and Astronomy (SpringerNature-11651)