Artificial Intelligence for Signal Processing and Wireless Communication
Description
This book focuses on artifi cial intelligence in the field of digital signal processing and wireless communication. The implementation of machine learning and deep learning in audio, image, and video processing is presented, while adaptive signal processing and biomedical signal processing are also explored through DL algorithms, as well as 5G and green communication. Finally, metaheuristic algorithms of related mathematical problems are explored.
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Persons
A. Sharma , A. Jain , Univ. of Petroleum, Bidholi, India; A. K. Arya , Kyung Hee Univ., S.Korea; M. Ram , Graphic Era Univ., India.
Content
- Intro
- Acknowledgments
- Preface
- Contents
- Editors' biographies
- Long short-term memory (LSTM) deep neural networks for sentiment classification
- Plant disease identification using IoT and deep learning algorithms
- A comprehensive study of plant pest and disease detection using different computer vision techniques
- Artificial intelligence applied to multiand broadband antenna design
- Direction of arrival estimation using Lévy flight-based moth flame optimization algorithm
- NLP techniques, tools, and algorithms for data science
- Prediction of coronary artery disease using logistic regression
- Design of antenna with biocomputing approach
- Energy-efficient methods for railway monitoring using WSN
- Analysis of acoustic emission for milling operation using artificial neural networks
- Index
