Principal Component Analysis: Principles and Applications

Author: Yang Fusheng
Publisher:
Publish Date: 2006-01-01
Features: Independent Component Analysis (ICA) is a class of multichannel signal decomposition methods that developed in the late 20th century and is a cutting-edge focus in the development of signal processing technology. This book provides a systematic introduction to its basic principles and engineering applications. The book is divided into 9 chapters, including topics such as prerequisite knowledge, optimization criteria, optimization algorithms, convolutional mixing cases, sparse component analysis, and applications in biomedical engineering. At the end, an overview of ICA online resources is provided to help readers stay updated on the latest developments and trends in ICA technology. The book is written based on the author's years of experience in teaching graduate-level courses and the research achievements of the research group, while also referencing a wide range of research reports from domestic and international journals. The narrative is tailored to the understanding and needs of engineering, striving to explain the issues from an engineering perspective using engineering terminology; it emphasizes the explanation of physical concepts, avoids excessive abstraction, and facilitates comprehension and self-study for engineering, as well as strengthening the connection with applications. This book is a highly introductory foundational text. It is suitable as a reference textbook for university teachers and graduate students, or for self-study or advanced training for science and technology workers engaged in signal processing.