Wavelets in Chemistry: Data Handling in Science and Technology, cartea 22
Editat de Beata Walczaken Limba Engleză Hardback – 9 mai 2000
The first part, concentrating on theoretical aspects, is written in a tutorial-like manner, with simple numerical examples. For the reader's convenience, all basic terms are explained in detail and all unique properties of wavelets are pinpointed and compared with the other types of basis function. The second part presents applications of wavelets from many branches of chemistry which will stimulate chemists to further exploration of this exciting subject.
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Specificații
ISBN-13: 9780444501110
ISBN-10: 0444501118
Pagini: 572
Dimensiuni: 184 x 257 x 41 mm
Greutate: 1.34 kg
Editura: ELSEVIER SCIENCE
Seria Data Handling in Science and Technology
ISBN-10: 0444501118
Pagini: 572
Dimensiuni: 184 x 257 x 41 mm
Greutate: 1.34 kg
Editura: ELSEVIER SCIENCE
Seria Data Handling in Science and Technology
Cuprins
Part headings and chapter headings: Preface. Theory. Finding frequencies in signals; the Fourier transform (B. van den Bogaert). When frequencies change in time; towards the wavelet transform (B. van den Bogaert). Fundamentals of wavelet transforms (Y. Mallet et al.). The discrete wavelet transform in practice (O. de Vel et al.). Multiscale methods for denoising and compression (M.N. Nounou, B.R. Bakshi). Wavelet packet transforms and best basis algorithms (Y. Mallet et al.). Joint basis and joint best-basis for data sets (B. Walczak, D.L. Massart). The adaptive wavelet algorithm for designing task specific wavelets (Y. Mallet et al.). Applications. Application of wavelet transform in processing chromatographic data (Foo-tim Chau, A. Kai-man Leung). Application of wavelet transform in electrochemical studies (Foo-tim Chau, A. Kai-man Leung). Applications of wavelet transform in spectroscopic studies (Foo-tim Chau, A. Kai-man Leung). Application of wavelet analysis to physical chemistry (H. Teitelbaum). Wavelet bases for IR library compression, searching and reconstruction (B. Walczak, J.P. Radomski). Application of the discrete wavelet transformation for online detection of transitions in time series (M. Marth). Calibration in wavelet domain (B. Walczak, D.L. Massart). Wavelets in parsimonious functional data analysis models (B.K. Alsberg). Multiscale statistical process control and model-based denoising (B.R. Bakshi). Application of adaptive wavelets in classification and regression (Y. Mallet et al.). Wavelet-based image compression (O. de Vel et al.). Wavelet analysis and processing of 2-D and 3-D analytical images (S.G. Nikolov et al.). Index.