Description: 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
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Title: Randomness And Elements Of Decision Theory Applied To Signals By
Weight: 666
EAN: 9783030903138
ISBN-10: 9783030903138
Date of Publication: 2021-12
Place of Publication: 2021-12
Book Series: Springer
Genre: COMPUTERS / Mathematical & Statistical Software
Narrative Type: N/A
Features: N/A
Intended Audience: N/A
Ex Libris: No
Editor: N/A
Edition: N/A
Pagination: 262
Dimensions: 921x614
Subject Area: Data Analysis
Item Height: 235 mm
Item Width: 155 mm
Author: Mihaela Cislariu, Andreia Miclea, Raul Malutan, Monica Borda, Romulus Terebes, Ioana Ilea, Barburiceanu Stefania
Publication Name: Randomness and Elements of Decision Theory Applied to Signals
Format: Hardcover
Language: English
Publisher: Springer Nature Switzerland A&G
Subject: Engineering & Technology, Computer Science, Mathematics, Management
Publication Year: 2022
Type: Textbook
Number of Pages: 232 Pages
