FOO-TIM CHAU, PhD, is a Professor in the Department of Applied Biology and Chemical Technology at Hong Kong Polytechnic University.
YI-ZENG LIANG, PhD, is a Professor in the College of Chemistry and Chemical Engineering at Central South University, China.
JUNBIN GAO, PhD, is a Professor in the Department of Mathematics at Huazhong University of Science and Technology. He is currently visiting the University of Southhampton.
XUE-GUANG SHAO, PhD, is a Professor at the University of Science and Technology in China.

Wavelet Transformations and Their Applications in Chemistry pioneers a new approach to classifying existing chemometric techniques for data analysis in one and two dimensions, using a practical applications approach to illustrating chemical examples and problems. Written in a simple, balanced, applications-based style, the book is geared to both theorists and non-mathematicians.
This text emphasizes practical applications in chemistry. It employs straightforward language and examples to show the power of wavelet transforms without overwhelming mathematics, reviews other methods, and compares wavelets with other techniques that provide similar capabilities. It uses examples illustrated in MATLAB codes to assist chemists in developing applications, and includes access to a supplementary Web site providing code and data sets for work examples. Wavelet Transformations and Their Applications in Chemistry will prove essential to professionals and students working in analytical chemistry and process chemistry, as well as physical chemistry, spectroscopy, and statistics.

PREFACE.
CHAPTER 1: INTRODUCTION.
1.1. Modern Analytical Chemistry.
1.2. Chemometrics.
1.3. Chemometrics-Based Signal Processing Techniques.
1.4. Resources Available on Chemometrics and Wavelet Transform.
CHAPTER 2: ONE-DIMENSIONAL SIGNAL PROCESSING TECHNIQUES IN CHEMISTRY.
2.1. Digital Smoothing and Filtering Methods.
2.2. Transformation Methods of Analytical Signals.
2.3. Numerical Differentiation.
2.4. Data Compression.
CHAPTER 3: TWO-DIMENSIONAL SIGNAL PROCESSING TECHNIQUES IN CHEMISTRY.
3.1. General Features of Two-Dimensional Data.
3.2. Some Basic Concepts for Two-Dimensional Data from Hyphenated Instrumentation.
3.3. Double-Centering Technique for Background Correction.
3.4. Congruence Analysis and Least-Squares Fitting.
3.5. Differentiation Methods for Two-Dimensional Data.
3.6 Resolution Methods for Two-Dimensional Data.
CHAPTER 4: FUNDAMENTALS OF WAVELET TRANSFORM.
4.1. Introduction to Wavelet Transform and Wavelet Packet Transform.
4.2. Wavelet Function Examples.
4.3. Fast Wavelet Algorithm and Packet Algorithm.
4.4. Biorthogonal Wavelet Transform.
4.5. Two-Dimensional Wavelet Transform.
CHAPTER 5: APPLICATION OF WAVELET TRANSFORM IN CHEMISTRY.
5.1. Data Compression.
5.2. Data Denoising and Smoothing.
5.3. Baseline/Background Removal.
5.4. Resolution Enhancement.
5.5. Combined Techniques.
5.6. An Overview of the Applications in Chemistry.
APPENDIX VECTOR AND MATRIX OPERATIONS AND ELEMENTARY MATLAB.
A.1. Elementary Knowledge in Linear Algebra.
A.2. Elementary Knowledge of MATLAB.
INDEX.