Wavelets and Their Applications
Case Studies
Published on 30. September 1998
Book
Paperback/Softback
158 pages
978-0-89871-416-6 (ISBN)
Description
This collection of independent case studies demonstrates how wavelet techniques have been used to solve open problems and develop insight into the nature of the systems under study. Each case begins with a description of the problem and points to the specific properties of wavelets and techniques used for determining a solution.
The cases range from a very simple wavelet-based technique for reducing noise in laboratory data to complex work on two-dimensional geographical data display conducted at the Earthquake Research Institute in Japan. One case study shows how wavelet analysis is used in the development of a Japanese text-to-speech system for personal computers and another presents new wavelet techniques developed for and applied to the study of atmospheric wind, turbulent fluid, and seismic acceleration data.
Although calculus and some junior and senior mathematics courses for scientists and engineers will suffice, a solid background in undergraduate mathematics, particularly analysis and numerical analysis, and some familiarity with the basics of wavelets are helpful for reading this book.
The cases range from a very simple wavelet-based technique for reducing noise in laboratory data to complex work on two-dimensional geographical data display conducted at the Earthquake Research Institute in Japan. One case study shows how wavelet analysis is used in the development of a Japanese text-to-speech system for personal computers and another presents new wavelet techniques developed for and applied to the study of atmospheric wind, turbulent fluid, and seismic acceleration data.
Although calculus and some junior and senior mathematics courses for scientists and engineers will suffice, a solid background in undergraduate mathematics, particularly analysis and numerical analysis, and some familiarity with the basics of wavelets are helpful for reading this book.
More details
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Dimensions
Height: 255 mm
Width: 178 mm
Thickness: 10 mm
Weight
294 gr
ISBN-13
978-0-89871-416-6 (9780898714166)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
Preface
Chapter 1: Wavelet-Based Multiresolution Display of Coastline Data, Sumiko Hiyama and Mei Kobayashi
Introduction
Properties of Scaling Functions and Wavelets
Approximation of Curves Using Mallat's Algorithm
Conclusion
Chapter 2: A Wavelet-Based Technique for Reducing Noise in Laboratory Data, Susumu Sakakibara
Introduction
Wavelets and a Data Smoothing Method
Two Examples
Conclusion
Chapter 3: A Wavelet-Based Conjugate Gradient Method for Solving Poisson Equations, Nobuatsu Tanaka
Introduction
The Incomplete Discrete Wavelet Transform
Numerical Examples
Conclusion
Appendix 1: Conjugate Gradient Methods
Appendix 2: Preconditioned Conjugate Gradient Methods
Appendix 3: Successive Over-Relaxation Methods
Chapter 4: Wavelet Analysis for a Text-to-Speech (TTS) System, Mei Kobayashi, Masaharu Sakamoto, Takashi Saito, Yasuhide Hashimoto, Masafumi Nishimura, and Kazuhiro Suzuki
Introduction
Wavelets and Speech Signal Processing
TTS Conversion
Conclusion
Appendix 1: Selection of Synthesis Units
Appendix 2: Overlap-Add Methods
Chapter 5: Wavelet Analysis of Atmospheric Wind, Turbulent Fluid, and Seismic Acceleration Data, Michio Yamada and Fumio Sasaki
Introduction
Extraction of Events from Time-Series
Spatial Distribution of Fourier Components
Correction of Seismic Data
Index.
Chapter 1: Wavelet-Based Multiresolution Display of Coastline Data, Sumiko Hiyama and Mei Kobayashi
Introduction
Properties of Scaling Functions and Wavelets
Approximation of Curves Using Mallat's Algorithm
Conclusion
Chapter 2: A Wavelet-Based Technique for Reducing Noise in Laboratory Data, Susumu Sakakibara
Introduction
Wavelets and a Data Smoothing Method
Two Examples
Conclusion
Chapter 3: A Wavelet-Based Conjugate Gradient Method for Solving Poisson Equations, Nobuatsu Tanaka
Introduction
The Incomplete Discrete Wavelet Transform
Numerical Examples
Conclusion
Appendix 1: Conjugate Gradient Methods
Appendix 2: Preconditioned Conjugate Gradient Methods
Appendix 3: Successive Over-Relaxation Methods
Chapter 4: Wavelet Analysis for a Text-to-Speech (TTS) System, Mei Kobayashi, Masaharu Sakamoto, Takashi Saito, Yasuhide Hashimoto, Masafumi Nishimura, and Kazuhiro Suzuki
Introduction
Wavelets and Speech Signal Processing
TTS Conversion
Conclusion
Appendix 1: Selection of Synthesis Units
Appendix 2: Overlap-Add Methods
Chapter 5: Wavelet Analysis of Atmospheric Wind, Turbulent Fluid, and Seismic Acceleration Data, Michio Yamada and Fumio Sasaki
Introduction
Extraction of Events from Time-Series
Spatial Distribution of Fourier Components
Correction of Seismic Data
Index.