Signal Processing and Machine Learning with Applications

Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications. The Authors Offer A Comprehensive Guide To Machine Learning Applied To Signal Processing And Recognition Problems, And Then Discuss Real Applications In Domains Such As Speech Processing And Biomedical Signal Processing, With A Focus On Handling Noise. This Textbook Is Intended For Advanced Undergraduate And Graduate Students Of Computer Science And Engineering.