Randomness and Elements of Decision Theory Applied to Signals /
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...
| Main Authors: | , , , , , , |
|---|---|
| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2021.
|
| Edition: | 1st ed. 2021. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| 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. |
|---|---|
| Physical Description: | 1 online resource (XVII, 242 pages 254 illustrations, 168 illustrations in color.) |
| ISBN: | 9783030903145 |
| DOI: | 10.1007/978-3-030-90314-5 |