Randomness and elements of decision theory applied to signals / Monica Borda, Romulus Terebes, Raul Malutan, Ioana Ilea, Mihaela Cislariu, Andreia Miclea, Stefania Barburiceanu.

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 denoisin...

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Main Authors: Borda, Monica (Author), Terebes, Romulus (Author), Malutan, Raul (Author), Ilea, Ioana (Author), Cislariu, Mihaela (Author), Miclea, Andreia (Author), Barburiceanu, Stefania (Author)
Format: eBook
Language:English
Published: Cham : Springer, [2021]
Subjects:
Online Access:Click for online access

MARC

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245 1 0 |a Randomness and elements of decision theory applied to signals /  |c Monica Borda, Romulus Terebes, Raul Malutan, Ioana Ilea, Mihaela Cislariu, Andreia Miclea, Stefania Barburiceanu. 
264 1 |a Cham :  |b Springer,  |c [2021] 
264 4 |c ©2021 
300 |a 1 online resource (251 pages) :  |b illustrations (some color) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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504 |a Includes bibliographical references. 
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. 
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. 
588 0 |a Print version record. 
650 0 |a Decision making. 
650 0 |a Random variables. 
650 0 |a Signal processing  |x Mathematics. 
650 7 |a decision making.  |2 aat 
650 7 |a Decision making  |2 fast 
650 7 |a Random variables  |2 fast 
650 7 |a Signal processing  |x Mathematics  |2 fast 
700 1 |a Terebes, Romulus,  |e author. 
700 1 |a Malutan, Raul,  |e author. 
700 1 |a Ilea, Ioana,  |e author. 
700 1 |a Cislariu, Mihaela,  |e author. 
700 1 |a Miclea, Andreia,  |e author. 
700 1 |a Barburiceanu, Stefania,  |e author. 
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776 0 8 |i Print version:  |a Borda, Monica.  |t Randomness and Elements of Decision Theory Applied to Signals.  |d Cham : Springer International Publishing AG, ©2022  |z 9783030903138 
856 4 0 |u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-90314-5  |y Click for online access 
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