Independent Component Analysis

A comprehensive introduction to ICA for students and practitioners Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more. Independent Component Analysis is divided into four sections that cover: • General mathematical concepts utilized in the book • The basic ICA model and its solution • Various extensions of the basic ICA model • Real-world applications for ICA models Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative. "Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing and more. Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative."--BOOK JACKET. Hyvarinen and fellow researchers Juhu Karhunen and Erkki Oja (all Helsinki U. of Technology) introduce independent component analysis as a statistical and computational technique for revealing hidden factors that underlie sets of random variables, measurements, or signals. Readers are intended to be from such disciplines as statistics, signal processing, neural networks, information theory, and engineering, and to have a grounding in college calculus, matrix algebra, probability theory, and statistics. Exercise problems and computer assignments facilitate the book's use in a graduate course. "In this chapter, we review central concepts of probability theory, statistics, and random processes."