Randomness and elements of decision theory applied to signals / Monica Borda, Romulus Terebes, Raul Malutan, Ioana Ilea, Mihaela Cislariu, Andreia Miclea, Stefania Barburiceanu.
Borda, Monica, author.; Terebes, Romulus, author.; Malutan, Raul, author.; Ilea, Ioana, author.; Cislariu, Mihaela, author.; Miclea, Andreia, author.; Barburiceanu, Stefania, author.
2021
QA279.4 .B67 2021
Available Online

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Title Randomness and elements of decision theory applied to signals / Monica Borda, Romulus Terebes, Raul Malutan, Ioana Ilea, Mihaela Cislariu, Andreia Miclea, Stefania Barburiceanu.
Author Borda, Monica, author.
ISBN 9783030903145 (electronic bk.)
3030903141 (electronic bk.)
9783030903138
3030903133
DOI https://doi.org/10.1007/978-3-030-90314-5
Published Cham : Springer, [2021]
Copyright ©2021
Language English
Description 1 online resource (251 pages) : illustrations (some color)
Other Standard Identifiers 10.1007/978-3-030-90314-5 doi
Call Number QA279.4 .B67 2021
Dewey Decimal Classification 519.5/42
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Description based on print version record.
Added Author Terebes, Romulus, author.
Malutan, Raul, author.
Ilea, Ioana, author.
Cislariu, Mihaela, author.
Miclea, Andreia, author.
Barburiceanu, Stefania, author.
Available in Other Form Randomness and Elements of Decision Theory Applied to Signals.
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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.

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