Wavelet Theory Principles and Applications

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Free Download Wavelet Theory: Principles and Applications
by David M Puchalski
English | 2021 | ISBN: 9781682518038 | 329 Pages | True PDF | 7.9 MB

The wavelet transform plays an extremely crucial role in image compression. For image compression applications, wavelet transform is a more suitable technique compared to the Fourier transform. Fourier transform is not practical for computing spectral information because it requires all previous and future information about the signal over the entire time domain and it cannot observe frequencies varying with time because the resulting function after Fourier transform is a function independent of time. Wavelets now serve as an alternative to classical Fourier methods, Fourier series and integrals. The reasons for this is that they are better localized, they are better adapted to discontinuities; they have a certain form of self-similarity, which makes the theory suited for the analysis of fractals and non-linear dynamical systems. The selfsimilarity properties of the scaling functions connect them to fractals and non-linear dynamical systems. This book is intended to focus on current research on wavelets theory and its applications in different areas such as biomedical analysis, fringe-pattern analysis, image applications, and network data transfer applications, and optical measurement techniques. Wavelet analysis is a powerful tool for characterizing the internal correlation of signal data and has powerful power in data compression and numerical approximation. Due to its "self-adaptive" and "mathematical microscope properties," it has become the focus of much attention in many disciplines. In the research of pattern recognition, wavelet analysis can be used to decompose the low frequency and high frequency of the frequency to represent the characteristics of the signal. It is widely used in many fields of signal analysis.
This book offers an introduction to wavelet theory and provides the essence of wavelet analysis, including differential and integral equations, harmonic analysis, signal and image processing, approximation theory and practical studies of Physics and Engineering. In this book some advances in wavelet theory and their applications in engineering, physics and technology are presented. This book will serve to students, practitioners and researchers in the academia and industry interested in challenging paradigms of wavelets and its application.


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