Wavelet Applications in Chemical Engineering

Overview

Wavelet analysis is an emerging field of applied mathematics that has provided new tools and algorithms for solving such problems as are encountered in fault diagnosis, modelling, identification, and control and optimization of chemical systems, where raw sensor data have to be processed into meaningful information. The theory has acquired the status of a unifying theory underlying many of the methods used in physics and signal processing.
Wavelet Applications in Chemical ...

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Hardcover (1994)
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Overview

Wavelet analysis is an emerging field of applied mathematics that has provided new tools and algorithms for solving such problems as are encountered in fault diagnosis, modelling, identification, and control and optimization of chemical systems, where raw sensor data have to be processed into meaningful information. The theory has acquired the status of a unifying theory underlying many of the methods used in physics and signal processing.
Wavelet Applications in Chemical Engineering gives an insight into the many possible applications of time-frequency decomposition to the discipline of chemical engineering. It also includes tutorial chapters introducing wavelets and providing computational examples which will be especially helpful to readers new to the field.
For researchers and students investigating new tools to solve problems in process operation and control, process modeling and simulation, process optimization and sensor data interpretation, Wavelet Applications in Chemical Engineering is both a practical resource and a valuable reference.

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Product Details

Table of Contents

Preface. I: Introduction to Wavelet Transformation and Time Frequency Analysis; X. Dai, B. Joseph, R.L. Motard. II: Computational Aspects of Wavelets and Wavelet Transforms; S. Palavajjhala, R.L. Motard, B. Joseph. III: Trend Analysis Using the Frazier—Jawerth Transform; A. Joshi, A. Kumar, R.L. Motard. IV: Process Signal Features Analysis; X. Dai, B. Joseph, R.L. Motard. V: Learning at Multiple Resolutions: Wavelets as Basis Functions in Artificial Neural Networks and Inductive Decision Trees; B.R. Bakshi, A. Koulouris, G. Stephanopoulos. VI: Application of Wavelets in Process Control; Y. Chikkula, J.H. Lee. VII: Use of Wavelets for Numerical Solution of Differential Equations; M. Nikolaou, Y. You. VIII: A Parallel Two-Dimensional Wavelet Packet Transform and Some Applications in Computing and Compression Analysis; E. Goirand, M.V. Wickerhauser, M. Farge.

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