Series In Machine Perception And Artificial Intelligence
3 primary works • 4 total works
Book 0
Wavelet Theory Approach To Pattern Recognition (3rd Edition)
by Yuan Yan Tang
Published 20 September 2024
This 3rd edition tackles the basic principle of deep learning as well as the application of combination of wavelet theory with deep learning to pattern recognition. Five new chapters related to the combination of wavelet theory and deep learning are added with many novel research results.The useful reference text will benefit academics, researchers, computer scientists, electronic engineers and graduate students in the field of pattern recognition, image analysis, machine learning and electrical and electronic engineering.
Book 36
Wavelet Theory And Its Application To Pattern Recognition
by Jiming Liu, Hong Ma, Yuan Yan Tang, and Lihua Yang
Published 13 March 2000
This is not a purely mathematical book. It presents the basic principle of wavelet theory to electrical and electronic engineers, computer scientists, and students, as well as the ideas of how wavelets can be applied to pattern recognition. It also contains many novel research results from the authors' research team.
Book 74
Wavelet Theory Approach To Pattern Recognition (2nd Edition)
by Yuan Yan Tang
Published 13 July 2009
The 2nd edition is an update of the book Wavelet Theory and its Application to Pattern Recognition published in 2000. Three new chapters, which are research results conducted during 2001-2008, are added. The book consists of three parts — the first presents a brief survey of the status of pattern recognition with wavelet theory; the second contains the basic theory of wavelet analysis; the third includes applications of wavelet theory to pattern recognition. The new book provides a bibliography of 170 references including the current state-of-the-art theory and applications of wavelet analysis to pattern recognition.
Book 79
Document Analysis And Recognition With Wavelet And Fractal Theories
by Yuan Yan Tang
Published 1 January 2012
Many phenomena around the research in document analysis and understanding are much better described through the powerful multiscale signal representations than by traditional ways.From this perspective, the recent emergence of powerful multiscale signal representations in general and fractal/wavelet basis representations in particular, has been particularly timely. Indeed, out of these theories arise highly natural and extremely useful representations for a variety of important phenomena in document analysis and understanding.This book presents both the development of these new approaches as well as their application to a number of fundamental problems of interest to scientists and engineers in document analysis and understanding.