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Numerical fourier analysis

Plonka, Gerlind.

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Numerical fourier analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Numerical fourier analysis/ by Gerlind Plonka ... [et al.].
其他作者:	Plonka, Gerlind.
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	xviii, 664 p. :illustrations (some col.), digital ;24 cm.
內容註:	Chapter. 1. Fourier series -- Chapter. 2. Fourier transform -- Chapter. 3. Discrete Fourier transforms -- Chapter. 4. Multidimensional Fourier methods -- Chapter. 5. Fast Fourier transforms -- Chapter. 6. Chebyshev methods and fast DCT algorithms -- Chapter. 7. Fast Fourier transforms for nonequispaced data -- Chapter. 8. High dimensional FFT -- Chapter. 9. Numerical applications of DFT -- Chapter. 10. Prony method for reconstruction of structured functions -- Appendix A -- Index -- References.
Contained By:	Springer Nature eBook
標題:	Fourier analysis. -
電子資源:	https://doi.org/10.1007/978-3-031-35005-4
ISBN:	9783031350054

Numerical fourier analysis
Numerical fourier analysis[electronic resource] /by Gerlind Plonka ... [et al.]. - Second edition. - Cham :Springer International Publishing :2023. - xviii, 664 p. :illustrations (some col.), digital ;24 cm. - Applied and numerical harmonic analysis,2296-5017. - Applied and numerical harmonic analysis..

Chapter. 1. Fourier series -- Chapter. 2. Fourier transform -- Chapter. 3. Discrete Fourier transforms -- Chapter. 4. Multidimensional Fourier methods -- Chapter. 5. Fast Fourier transforms -- Chapter. 6. Chebyshev methods and fast DCT algorithms -- Chapter. 7. Fast Fourier transforms for nonequispaced data -- Chapter. 8. High dimensional FFT -- Chapter. 9. Numerical applications of DFT -- Chapter. 10. Prony method for reconstruction of structured functions -- Appendix A -- Index -- References.

New technological innovations and advances in research in areas such as spectroscopy, computer tomography, signal processing, and data analysis require a deep understanding of function approximation using Fourier methods. To address this growing need, this monograph combines mathematical theory and numerical algorithms to offer a unified and self-contained presentation of Fourier analysis. The first four chapters of the text serve as an introduction to classical Fourier analysis in the univariate and multivariate cases, including the discrete Fourier transforms, providing the necessary background for all further chapters. Next, chapters explore the construction and analysis of corresponding fast algorithms in the one- and multidimensional cases. The well-known fast Fourier transforms (FFTs) are discussed, as well as recent results on the construction of the nonequispaced FFTs, high-dimensional FFTs on special lattices, and sparse FFTs. An additional chapter is devoted to discrete trigonometric transforms and Chebyshev expansions. The final two chapters consider various applications of numerical Fourier methods for improved function approximation, including Prony methods for the recovery of structured functions. This new edition has been revised and updated throughout, featuring new material on a new Fourier approach to the ANOVA decomposition of high-dimensional trigonometric polynomials; new research results on the approximation errors of the nonequispaced fast Fourier transform based on special window functions; and the recently developed ESPIRA algorithm for recovery of exponential sums, among others. Numerical Fourier Analysis will be of interest to graduate students and researchers in applied mathematics, physics, computer science, engineering, and other areas where Fourier methods play an important role in applications.

ISBN: 9783031350054

Standard No.: 10.1007/978-3-031-35005-4doiSubjects--Topical Terms:

532730
Fourier analysis.

LC Class. No.: QA403.5

Dewey Class. No.: 515.2433

Numerical fourier analysis
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520 $a New technological innovations and advances in research in areas such as spectroscopy, computer tomography, signal processing, and data analysis require a deep understanding of function approximation using Fourier methods. To address this growing need, this monograph combines mathematical theory and numerical algorithms to offer a unified and self-contained presentation of Fourier analysis. The first four chapters of the text serve as an introduction to classical Fourier analysis in the univariate and multivariate cases, including the discrete Fourier transforms, providing the necessary background for all further chapters. Next, chapters explore the construction and analysis of corresponding fast algorithms in the one- and multidimensional cases. The well-known fast Fourier transforms (FFTs) are discussed, as well as recent results on the construction of the nonequispaced FFTs, high-dimensional FFTs on special lattices, and sparse FFTs. An additional chapter is devoted to discrete trigonometric transforms and Chebyshev expansions. The final two chapters consider various applications of numerical Fourier methods for improved function approximation, including Prony methods for the recovery of structured functions. This new edition has been revised and updated throughout, featuring new material on a new Fourier approach to the ANOVA decomposition of high-dimensional trigonometric polynomials; new research results on the approximation errors of the nonequispaced fast Fourier transform based on special window functions; and the recently developed ESPIRA algorithm for recovery of exponential sums, among others. Numerical Fourier Analysis will be of interest to graduate students and researchers in applied mathematics, physics, computer science, engineering, and other areas where Fourier methods play an important role in applications.
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