信号処理の機械学習 Machine Learning in Signal Processing : Applications, Challenges, and the Road Ahead

信号処理の機械学習<br>Machine Learning in Signal Processing : Applications, Challenges, and the Road Ahead

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信号処理の機械学習
Machine Learning in Signal Processing : Applications, Challenges, and the Road Ahead

Tanwar, Sudeep (EDT)/ Nayyar, Anand (EDT)/ Rameshwar, Rudra (EDT)

ウェブストア価格 ¥38,522（本体¥35,020）
Chapman & Hall/CRC（2021/12発売）
外貨定価 US$ 190.00
ポイント 350pt

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製本 Hardcover:ハードカバー版／ページ数 374 p.
言語 ENG
商品コード 9780367618902
DDC分類 006.31

Full Description

Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML).

ML, as the driving force of the wave of artificial intelligence (AI), provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML.

The focus is on understanding the contributions of signal processing and ML, and its aim to solve some of the biggest challenges in AI and ML.

FEATURES

Focuses on addressing the missing connection between signal processing and ML

Provides a one-stop guide reference for readers

Oriented toward material and flow with regards to general introduction and technical aspects

Comprehensively elaborates on the material with examples and diagrams

This book is a complete resource designed exclusively for advanced undergraduate students, post-graduate students, research scholars, faculties, and academicians of computer science and engineering, computer science and applications, and electronics and telecommunication engineering.

1. Introduction to Signal Processing and Machine Learning

Kavitha Somaraj

2. Learning Theory (Supervised/Unsupervised) for Signal Processing

Ruby Jain, Bhuvan Jain, and Manimala Puri

3. Supervised and Unsupervised Learning Theory for Signal Processing

Sowmya K. B.

4. Applications of Signal Processing

Anuj Kumar Singh and Ankit Garg

5. Dive in Deep Learning: Computer Vision, Natural Language Processing, and Signal Processing

V. Ajantha Devi and Mohd Naved

6. Brain-Computer Interfacing

Paras Nath Singh

7. Adaptive Filters and Neural Net

Sowmya K. B., Chandana G., and Anjana Mahaveer Daigond

8. Adaptive Decision Feedback Equalizer Based on Wavelet Neural Network

Saikat Majumder

9. Intelligent Video Surveillance Systems Using Deep Learning Methods

Anjanadevi Bondalapati and Manjaiah D. H.

10. Stationary Signal, Autocorrelation, and Linear and Discriminant Analysis

Bandana Mahapatra and Kumar Sanjay Bhorekar

11. Intelligent System for Fault Detection in Rotating Electromechanical Machines.

Pascal Dore, Saad Chakkor, and Ahmed El Oualkadi

12. Wavelet Transformation and Machine Learning Techniques for Digital Signal Analysis in IoT Systems

Rajalakshmi Krishnamurthi and Dhanalekshmi Gopinathan