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Books on the topic 'Fast Fourier Transform(FFT)'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 September 2023

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1

Wei, Chʻen, and United States. National Aeronautics and Space Administration., eds. Report on the NASA FFT project: Feasibility study, software design, layout and simulation of a two-dimensional fast Fourier transform machine for use in optical array interferometry. [Washington, DC: National Aeronautics and Space Administration, 1990.

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2

Sorensen, Henrik V. Fast fourier transform database. Boston: PWS Publishing, 1995.

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3

Sorensen, Henrik V. Fast Fourier transform database. Boston, MA: PWS Pub., 1995.

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4

Pollock, D. S. G. A mixed-radix fast Fourier transform and a Base-2 fast Fourier transform. London: QueenMary and Westfield College, Department of Economics, 1989.

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5

Rao, K. R., D. N. Kim, and J. J. Hwang. Fast Fourier Transform - Algorithms and Applications. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-1-4020-6629-0.

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6

Rao, K. R. Fast Fourier Transform: Algorithms and Applications. Dordrecht: Springer Science+Business Media B.V., 2010.

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7

Brigham, E. Oran. The fast Fourier transform and its applications. Englewood Cliffs, NJ: Prentice-Hall International, 1988.

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8

The fast Fourier transform and its applications. Englewood Cliffs, N.J: Prentice Hall, 1988.

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9

Loan, Charles Van. Computational frameworks for the fast fourier transform. Philadelphia: SIAM, 1992.

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10

Takahashi, Daisuke. Fast Fourier Transform Algorithms for Parallel Computers. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9965-7.

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11

Research Institute for Advanced Computer Science (U.S.), ed. Fast fourier transform algorithm design and tradeoffs. [Moffett Field, Calif.?]: Research Institute for Advanced Computer Science, 1989.

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12

Constas, Athanasia. Fast fourier transform solvers for quadratic spline collation. Toronto: University of Toronto, Dept. of Computer Science, 1996.

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13

Morgan, Alan Robert. A digital fast Fourier transform spectrometer for radio astronomy. Manchester: University of Manchester, 1995.

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14

Zhao, Shunde. The computation of detailed geoids using the fast Fourier transform method. Colombus, Ohio: Dept.of Geodetic Science and Surveying, Ohio State University, 1989.

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15

An introduction to fast fourier transform methods for partial differential equations, with applications. Letchworth, Hertfordshire, England: Research Studies Press, 1986.

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16

McQuillan, Dermott M. Fast Fourier transform analysis of signal-averaged electrocardiograms for identification of patients proneto sustained ventricular tachycardia. [S.l: The author], 1985.

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17

Monsefi, Reza. An interactive digital simulation of a 'FSK' telemetry system, utilizing on-line real-time comb-filtering or fast fourier transform methods for reconstruction of binary data. Salford: University of Salford, 1987.

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18

United States. National Aeronautics and Space Administration., ed. Feasibility study, software design, layout and simulation of a two-dimensional fast Fourier transform machine for use in optical array interferometry: Final report on the NASA FTT project covering the period June 1, 1989 to September 1, 1994. [Washington, DC: National Aeronautics and Space Administration, 1994.

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19

United States. National Aeronautics and Space Administration., ed. Feasibility study, software design, layout and simulation of a two-dimensional fast Fourier transform machine for use in optical array interferometry: Final report on the NASA FTT project covering the period June 1, 1989 to September 1, 1994. [Washington, DC: National Aeronautics and Space Administration, 1994.

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20

Boles, Melanie. TB3141, Implementing the Fast Fourier Transform (FFT) on DsPIC DSCs. Microchip Technology Incorporated, 2015.

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21

Beyene, Joseph. Uses of the fast fourier transform (FFT) in exact statistical inference. 2001.

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22

George, Alan, and Eleanor Chu. Inside the FFT Black Box: Serial and Parallel Fast Fourier Transform Algorithms. Taylor & Francis Group, 1999.

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23

Inside the FFT Black Box: Serial and Parallel Fast Fourier Transform Algorithms (Computational Mathematics Series). CRC, 1999.

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24

Burl, Jeffrey. Fast Fourier Transform. Pearson Education, Limited, 2003.

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25

Takenaka, Norio. AN681 - Reading and Using Fast Fourier Transformation (FFT). Microchip Technology Incorporated, 2017.

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26

Brown, Dr Allen. Guide to the Fourier Transform and the Fast Fourier Transform. Independently published, 2019.

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27

Sorenson, Henrik T. Fast Fourier Transform Database Sftw. PWS Pub. Co., 1999.

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28

Nussbaumer, H. J. Fast Fourier Transform and Convolution Algorithms. Springer London, Limited, 2013.

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29

Fast Fourier Transform and Convolution Algorithms. Springer, 2011.

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30

Fast Fourier Transform and Convolution Algorithms. 2nd ed. Springer, 1990.

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31

Zhu, Feihong. Two dimensional recursive fast Fourier transform. 1987.

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32

Nussbaumer, Henri J. Fast Fourier Transform and Convolution Algorithms. Springer London, Limited, 2012.

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33

Kim, Do Nyeon, Jae Jeong Hwang, and K. R. R. Rao. Fast Fourier Transform - Algorithms and Applications. Springer, 2012.

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34

Takahashi, Daisuke. Fast Fourier Transform Algorithms for Parallel Computers. Springer Singapore Pte. Limited, 2020.

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35

National Aeronautics and Space Administration (NASA) Staff. Fast Fourier Transform Algorithm Design and Tradeoffs. Independently Published, 2018.

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36

Takahashi, Daisuke. Fast Fourier Transform Algorithms for Parallel Computers. Springer, 2019.

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37

Fast NMR Data Acquisition: Beyond the Fourier Transform. Royal Society of Chemistry, The, 2017.

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38

McGill, Kenneth C. Fast fourier transformed acoustic resonances with sonic transform. 1990.

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39

Bisseling, Rob H. Parallel Scientific Computation. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198788348.001.0001.

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This book explains how to use the bulk synchronous parallel (BSP) model to design and implement parallel algorithms in the areas of scientific computing and big data. Furthermore, it presents a hybrid BSP approach towards new hardware developments such as hierarchical architectures with both shared and distributed memory. The book provides a full treatment of core problems in scientific computing and big data, starting from a high-level problem description, via a sequential solution algorithm to a parallel solution algorithm and an actual parallel program written in the communication library BSPlib. Numerical experiments are presented for parallel programs on modern parallel computers ranging from desktop computers to massively parallel supercomputers. The introductory chapter of the book gives a complete overview of BSPlib, so that the reader already at an early stage is able to write his/her own parallel programs. Furthermore, it treats BSP benchmarking and parallel sorting by regular sampling. The next three chapters treat basic numerical linear algebra problems such as linear system solving by LU decomposition, sparse matrix-vector multiplication (SpMV), and the fast Fourier transform (FFT). The final chapter explores parallel algorithms for big data problems such as graph matching. The book is accompanied by a software package BSPedupack, freely available online from the author’s homepage, which contains all programs of the book and a set of test programs.

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40

The Regularized Fast Hartley Transform Optimal Formulation Of Realdata Fast Fourier Transform For Siliconbased Implementation In Resourceconstrained Environments. Springer, 2010.

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41

Loan, Charles Van. Computational Frameworks for the Fast Fourier Transform (Frontiers in Applied Mathematics). Society for Industrial Mathematics, 1987.

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42

Jones, Keith. Regularized Fast Hartley Transform: Optimal Formulation of Real-Data Fast Fourier Transform for Silicon-Based Implementation in Resource-Constrained Environments. Springer, 2010.

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43

An Introduction to Fast Fourier Transform Methods for Partial Differential Equations, with Applications. Research Studies Press, 1986.

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44

An Improved Asynchronous Implementation of a Fast Fourier Transform Architecture for Space Applications. Storming Media, 1999.

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45

Allen, Michael P., and Dominic J. Tildesley. Long-range forces. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0006.

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A wide variety of special techniques for handling long-range forces are explained in this chapter. This includes the traditional Ewald sum, and the particle-mesh methods that use a discrete Fourier transform. A number of techniques based on spherical truncation such as the Wolf method, the isotropic periodic sum and the reaction field are also considered. Techniques for larger systems such as the fast-multipole method, the multilevel summation approach, and the direct solution of Maxwell’s equations, are explained. The advantages and disadvantages of the different approaches are reviewed, and a number of methods for tackling long-range forces in inhomogeneous systems, particularly in a slab geometry, are presented.

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46

Allen, Michael P., and Dominic J. Tildesley. How to analyse the results. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0008.

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In this chapter, practical guidance is given on the calculation of thermodynamic, structural, and dynamical quantities from simulation trajectories. Program examples are provided to illustrate the calculation of the radial distribution function and a time correlation function using the direct and fast Fourier transform methods. There is a detailed discussion of the calculation of statistical errors through the statistical inefficiency. The estimation of the error in equilibrium averages, fluctuations and in time correlation functions is discussed. The correction of thermodynamic averages to neighbouring state points is described along with the extension and extrapolation of the radial distribution function. The calculation of transport coefficients by the integration of the time correlation function and through the Einstein relation is discussed.

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47

Boudreau, Joseph F., and Eric S. Swanson. Continuum dynamics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0019.

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The theory and application of a variety of methods to solve partial differential equations are introduced in this chapter. These methods rely on representing continuous quantities with discrete approximations. The resulting finite difference equations are solved using algorithms that stress different traits, such as stability or accuracy. The Crank-Nicolson method is described and extended to multidimensional partial differential equations via the technique of operator splitting. An application to the time-dependent Schrödinger equation, via scattering from a barrier, follows. Methods for solving boundary value problems are explored next. One of these is the ubiquitous fast Fourier transform which permits the accurate solution of problems with simple boundary conditions. Lastly, the finite element method that is central to modern engineering is developed. Methods for generating finite element meshes and estimating errors are also discussed.

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48

Petersen, Wesley, and Peter Arbenz. Introduction to Parallel Computing. Oxford University Press, 2004. http://dx.doi.org/10.1093/oso/9780198515760.001.0001.

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In the last few years, courses on parallel computation have been developed and offered in many institutions in the UK, Europe and US as a recognition of the growing significance of this topic in mathematics and computer science. There is a clear need for texts that meet the needs of students and lecturers and this book, based on the author's lecture at ETH Zurich is an ideal practical student guide to scientific computing on parallel computers working up from a hardware instruction level, to shared memory machines and finally to distributed memory machines. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science and engineering, subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations, including examples in C and in some cases Fortran. This book is also ideal for practitioners and programmers.

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