Signal Processing and Machine Learning Theory

Signal Processing and Machine Learning Theory, authored by world-leading experts, reviews the principles, methods, and techniques of essential and advanced signal processing theory, driving many current and emerging research topics and technologies.

Format: Paperback / softback
Length: 1234 pages
Publication date: 01 May 2023
Publisher: Elsevier Science & Technology

Signal Processing and Machine Learning Theory, penned by esteemed experts from around the globe, delves into the comprehensive principles, methodologies, and advanced techniques of essential and cutting-edge signal processing theory. These profound theories and indispensable tools serve as the powerful engines propelling numerous current and emerging research domains and technologies, including machine learning, autonomous vehicles, the Internet of Things, future wireless communications, medical imaging, and many more.

The book offers a comprehensive and systematic exploration of signal processing fundamentals, covering topics such as linear systems, digital signal processing, Fourier analysis, and time-frequency analysis. It also delves into advanced topics such as adaptive filters, neural networks, and machine learning algorithms, providing readers with a deep understanding of the theoretical foundations and practical applications of these cutting-edge techniques.

With its extensive coverage and rigorous analysis, Signal Processing and Machine Learning Theory serves as a valuable resource for researchers, engineers, and students in the fields of telecommunications, computer science, electrical engineering, and mathematics. It equips them with the necessary knowledge and skills to tackle complex signal processing challenges and contribute to the development of innovative technologies that shape our modern world.

By presenting a unified and coherent framework for signal processing and machine learning, this book fosters a deeper understanding of the underlying principles and enables readers to apply these techniques to real-world problems. It serves as a valuable reference for both novice and experienced practitioners, providing them with a comprehensive guide to the state-of-the-art in signal processing and machine learning.

In conclusion, Signal Processing and Machine Learning Theory is a groundbreaking work that revolutionizes our understanding of signal processing and machine learning. It is a must-read for anyone interested in advancing their knowledge in these fields and contributing to the development of cutting-edge technologies that will shape the future.

Weight: 1840g
Dimension: 235 x 191 (mm)
ISBN-13: 9780323917728