Wavelet Methods for Time Series Analysis, Second Edition

Author: Xu Changsheng
Publisher:
Publish Date: 2004-01-01
Features: This book introduces the basic knowledge of wavelet theory and its applications using popular mathematical language. It discusses the shortcomings of Fourier transform and windowed Fourier transform in the context of time-frequency analysis, provides a detailed analysis of the basic principles of wavelet transform, elaborates on the fundamental ideas of multi-resolution approximation and wavelet decomposition, and thoroughly discusses the implementation process of discrete wavelet transform and its fast algorithms. It introduces several common wavelets and their construction methods, and presents various application examples while analyzing the fundamental principles of wavelet methods in practical applications. The book is rich in content, easy to understand, and beneficial for practical use and self-study. It can serve as a textbook for senior undergraduate and graduate students in science and engineering disciplines in higher education institutions, as well as a reference book for technical personnel engaged in signal processing research.