The Wavelet Transform [electronic resource] / by Ram Shankar Pathak.

By: Pathak, Ram Shankar [author.]Contributor(s): SpringerLink (Online service)Material type: TextTextSeries: Atlantis Studies in Mathematics for Engineering and Science ; 4Publisher: Paris : Atlantis Press, 2009Description: XIII, 178p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9789491216244Subject(s): Mathematics | Numerical analysis | Mathematics | Numerical AnalysisDDC classification: 518 LOC classification: QA297-299.4Online resources: Click here to access online
Contents:
An Overview -- TheWavelet Transform on Lp -- Composition ofWavelet Transforms -- TheWavelet Transform on Spaces of Type S -- The Wavelet Transform on Spaces of Type W -- The Wavelet Transform on a Generalized Sobolev Space -- A Class of Convolutions: Convolution for the Wavelet Transform -- The Wavelet Convolution Product -- Asymptotic Expansions of the Wavelet Transform when |b| is Large -- Asymptotic Expansions of the Wavelet Transform for Large and Small Values of a.
In: Springer eBooksSummary: The wavelet transform has emerged as one of the most promising function transforms with great potential in applications during the last four decades. The present monograph is an outcome of the recent researches by the author and his co-workers, most of which are not available in a book form. Nevertheless, it also contains the results of many other celebrated workers of the ?eld. The aim of the book is to enrich the theory of the wavelet transform and to provide new directions for further research in theory and applications of the wavelet transform. The book does not contain any sophisticated Mathematics. It is intended for graduate students of Mathematics, Physics and Engineering sciences, as well as interested researchers from other ?elds. The Fourier transform has wide applications in Pure and Applied Mathematics, Physics and Engineering sciences; but sometimes one has to make compromise with the results obtainedbytheFouriertransformwiththephysicalintuitions. ThereasonisthattheFourier transform does not re?ect the evolution over time of the (physical) spectrum and thus it contains no local information. The continuous wavelet transform (W f)(b,a), involving ? wavelet ?, translation parameterb and dilation parametera, overcomes these drawbacks of the Fourier transform by representing signals (time dependent functions) in the phase space (time/frequency) plane with a local frequency resolution. The Fourier transform is p n restricted to the domain L (R ) with 1 p 2, whereas the wavelet transform can be de?ned for 1 p.
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An Overview -- TheWavelet Transform on Lp -- Composition ofWavelet Transforms -- TheWavelet Transform on Spaces of Type S -- The Wavelet Transform on Spaces of Type W -- The Wavelet Transform on a Generalized Sobolev Space -- A Class of Convolutions: Convolution for the Wavelet Transform -- The Wavelet Convolution Product -- Asymptotic Expansions of the Wavelet Transform when |b| is Large -- Asymptotic Expansions of the Wavelet Transform for Large and Small Values of a.

The wavelet transform has emerged as one of the most promising function transforms with great potential in applications during the last four decades. The present monograph is an outcome of the recent researches by the author and his co-workers, most of which are not available in a book form. Nevertheless, it also contains the results of many other celebrated workers of the ?eld. The aim of the book is to enrich the theory of the wavelet transform and to provide new directions for further research in theory and applications of the wavelet transform. The book does not contain any sophisticated Mathematics. It is intended for graduate students of Mathematics, Physics and Engineering sciences, as well as interested researchers from other ?elds. The Fourier transform has wide applications in Pure and Applied Mathematics, Physics and Engineering sciences; but sometimes one has to make compromise with the results obtainedbytheFouriertransformwiththephysicalintuitions. ThereasonisthattheFourier transform does not re?ect the evolution over time of the (physical) spectrum and thus it contains no local information. The continuous wavelet transform (W f)(b,a), involving ? wavelet ?, translation parameterb and dilation parametera, overcomes these drawbacks of the Fourier transform by representing signals (time dependent functions) in the phase space (time/frequency) plane with a local frequency resolution. The Fourier transform is p n restricted to the domain L (R ) with 1 p 2, whereas the wavelet transform can be de?ned for 1 p.

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