Signal Processing and Machine Learning with Applications

Signal processing uses mathematics, statistics, probability, and stochastic processes to interpret real-world phenomena, model them, and extract useful information. This book presents various signals used for human-machine interaction and applies them for communication. It is organized in three parts and includes examples, questions, and historical notes. It is intended for advanced undergraduate and postgraduate students, researchers, and practitioners.

Format: Hardback
Length: 607 pages
Publication date: 28 July 2022
Publisher: Springer International Publishing AG

Signal processing is a powerful tool that encompasses a wide range of techniques for capturing, interpreting, describing, and manipulating physical phenomena. It utilizes a diverse array of signal processing languages, including mathematics, statistics, probability, and stochastic processes, to interpret real-world phenomena, model them, and extract valuable information. This comprehensive book explores various types of signals used by humans and their applications in human-machine interaction for communication purposes.

In the first part of the book, "Realms of Signal Processing," readers are introduced to the fundamental concepts and theories of signal processing. It covers topics such as signal representation, filtering, modulation, and transformation, as well as signal processing algorithms and their applications. The authors provide detailed explanations and examples to help readers understand the underlying principles and practical applications of signal processing.

The second part, "Machine Learning and Recognition," delves into the realm of machine learning and its applications in signal processing. It discusses various machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning, and their use in tasks such as image recognition, speech recognition, and pattern recognition. The book also covers topics such as feature extraction, model training, and evaluation, and provides practical examples and case studies to illustrate the effectiveness of these algorithms.

The third part, "Advanced Applications and Artificial Intelligence," explores the latest developments and applications of signal processing and machine learning in advanced fields such as healthcare, finance, and transportation. It discusses the use of signal processing techniques for medical imaging, financial analysis, and autonomous vehicle control, and highlights the challenges and opportunities associated with these applications.

Throughout the book, numerous examples, questions with solutions, and historical notes are provided to enhance the understanding of the topics. The book is intended for advanced undergraduate and postgraduate students, researchers, and practitioners who are engaged with signal processing, machine learning, and the applications. It serves as a valuable resource for anyone seeking to expand their knowledge and expertise in these fields.

In conclusion, Signal Processing and Machine Learning with Applications is a comprehensive and up-to-date book that provides a thorough introduction to signal processing and its applications in various fields. It offers a solid foundation for understanding the principles and techniques of signal processing, and provides practical insights into the latest developments and applications of machine learning. Whether you are a student, researcher, or practitioner, this book will be a valuable resource for your journey in signal processing and machine learning.

Weight: 1136g
Dimension: 235 x 155 (mm)
ISBN-13: 9783319453712
Edition number: 1st ed. 2022