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Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead
Machine Learning in Signal 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.
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.
374 pages, Kindle Edition
Published December 9, 2021
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