Abstract
The Fourier transformation \(\mathcal{F}\) of the function f on the real axis is defined as \(F(\omega ) = \mathcal{F}[f](\omega ) = \int _{-\infty }^\infty f(x)\, \mathrm {e}^{-\mathrm {i}\omega x } \, \mathrm {d}x \>. \) The sufficient conditions for the existence of F are that f is absolutely integrable, i.e. \(\int _{-\infty }^\infty |f(x)| \, \mathrm {d}x < \infty \), and that f is piecewise continuous or has a finite number of discontinuities.
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References
B.D. MacCluer, Elementary Functional Analysis (Springer Science+Business Media, New York, 2010)
C. Shannon, Communication in the presence of noise. Proc. IEEE 86, 447 (1998) (reprint); See also M. Unser, Sampling-50 years after Shannon, Proc. IEEE 88, 569 (2000) and H. Nyquist, Certain topics in telegraph transmission theory, Proc. IEEE 90, 280 (2002) (reprint)
C. Canuto, M.Y. Hussaini, A. Quarteroni, T.A. Zang, Spectral Methods. Fundamentals In Single Domains (Springer, Berlin, 2006)
D. Donnelly, B. Rust, The fast fourier transform for experimentalists, Part I: concepts. Comput. Sci. Eng. p. 80 (Mar/Apr, 2005)
F.J. Harris, On the use of windows for harmonic analysis with the discrete Fourier transform. Proc. IEEE 66, 51 (1978)
M. Frigo, S.G. Johnson, The design and implementation of FFTW3. Proc. IEEE 93, 216 (2005). documentation can be found at http://www.fftw.org
W.H. Press, B.P. Flannery, S.A. Teukolsky, W.T. Vetterling, Numerical Recipes: The Art of Scientific Computing, 3rd edn. (Cambridge University Press, Cambridge, 2007); See also the equivalent handbooks in Fortran, Pascal and C, as well as http://www.nr.com
P. Duhamel, M. Vetterli, Fast Fourier transforms: a tutorial review and a state of the art. Signal Process. 19, 259 (1990)
J.C. Schatzman, Accuracy of the discrete Fourier transform and the fast Fourier transform. SIAM J. Sci. Comput. 17, 1150 (1996)
H. Hassanieh, P. Indyk, D. Katabi, E. Price, Simple and practical algorithm for sparse Fourier transform, in Proceedings of the 23rd Annual ACM-SIAM Symposium on Discrete Algorithms, ed. by Y. Rabani (SIAM, Philadelphia, 2012), p. 1183
Available at http://groups.csail.mit.edu/netmit/sFFT/
H. Hassanieh, P. Indyk, D. Katabi, E. Price, Nearly optimal sparse Fourier transform, in Proceedings of the 44th Annual ACM Symposium on Theory of Computing (ACM, New York, 2012), p. 563
J. Schumacher, M. Püschel, High-performance sparse fast Fourier transforms, in Proceedings of the IEEE Workshop on Signal Processing Systems (IEEE, 2014), p. 1
Available at http://spiral.net/software/sfft.html
P. Degroote et al., Evidence for nonlinear resonant mode coupling in the \(\beta \) Cephei star HD 180642 (V1449 Aquilae) from CoRoT photometry. Astron. Astrophys. 506, 111 (2009)
J.T. VanderPlas, Understanding the Lomb-Scargle Periodogram, arXiv:1703.0982 [astro-ph.IM]
A. Dutt, V. Rokhlin, Fast Fourier transforms for nonequispaced data. SIAM J. Sci. Comput. 14, 1368 (1993)
A. Dutt, V. Rokhlin, Fast Fourier transforms for nonequispaced data, II. Appl. Comput. Harmon. Anal. 2, 85 (1995)
L. Greengard, J.-Y. Lee, Accelerating the nonuniform fast Fourier transform. SIAM Rev. 46, 443 (2004)
M. Lyon, J. Picard, The Fourier approximation of smooth but non-periodic functions from unevenly spaced data. Adv. Comput. Math. 40, 1073 (2014)
N. Seghouani, High-resolution spectral analysis of unevenly spaced data using a regularization approach. Mon. Not. R. Astron. Soc. 468, 3312 (2017)
W.H. Press, G.B. Rybicki, Fast algorithm for spectral analysis of unevenly sampled data. Astrophys. J. 338, 277 (1989)
J. Keiner, S. Kunis, D. Potts, Using NFFT3 – a software library for various nonequispaced Fourier transforms. ACM Trans. Math. Softw. 36, 1 (2009)
D. Potts, G. Steidl, Fast summation at nonequispaced knots by NFFTS. SIAM J. Sci. Comput. 24, 2013 (2003)
D. Potts, G. Steidl, M. Tasche, Fast Fourier transforms for nonequispaced data: a tutorial, in Modern Sampling Theory: Mathematics and Applications, ed. by J.J. Benedetto, P.J.S.G. Ferreira (Birkhäuser, Boston, 2001), p. 247
G. Steidl, A note on the fast Fourier transforms for nonequispaced grids. Adv. Comput. Math. 9, 337 (1998)
B. Leroy, Fast calculation of the Lomb-Scargle periodogram using nonequispaced fast Fourier transforms. Astron. Astrophys. 545, A50 (2012)
G. Szegö, Orthogonal Polynomials (AMS, Providence, 1939)
T.J. Rivlin, The Chebyshev Polynomials (Wiley, New York, 1974)
V. Rokhlin, A fast algorithm for discrete Laplace transformation. J. Complex. 4, 12 (1988) and J. Strain, A fast Laplace transform based on Laguerre functions. Math. Comput. 58, 275 (1992)
M. Abramowitz, I.A. Stegun, Handbook of Mathematical Functions, 10th edn. (Dover Publications, Mineola, 1972)
S. Zhang, J. Jin, Computation of Special Functions (Wiley-Interscience, New York, 1996)
W.E. Boyce, R.C. DiPrima, Elementary Differential Equations and Boundary Value Problems, 5th edn. (Wiley, New York, 1992)
J. Abate, P.P. Valkó, Multi-precision Laplace transform inversion. Int. J. Numer. Methods Eng. 60, 979 (2004)
A.M. Cohen, Numerical Methods For Laplace Transform Inversion (Springer Science+Business Media, New York, 2007)
B. Davies, B. Martin, Numerical inversion of the Laplace transform: a survey and comparison of methods. J. Comput. Phys. 33, 1 (1979); See also D.G. Duffy, On the numerical inversion of Laplace transforms: comparison of three new methods on characteristic problems from applications. ACM Trans. Math. Softw. 19, 333 (1993)
C.L. Epstein, J. Schotland, The bad truth about Laplace’s transform. SIAM Rev. 50, 504 (2008)
R. Piessens, Gaussian quadrature formulas for the numerical integration of Bromwich’s integral and the inversion of the Laplace transform. J. Eng. Math. 5, 1 (1971); See also L.N. Trefethen, J.A.C. Weideman, T. Schmelzer, Talbot quadratures and rational approximations. BIT Numer. Math. 46, 653 (2006)
J. Abate, W. Whitt, Queueing Syst. 10, 5 (1992); See also P. den Iseger, Prob. Eng. Inf. Sci. 20, 1 (2006) and A. Yonemoto, T. Hisikado, K. Okumura, IEEE Proc.-Circuits Devices Syst. 150, 399 (2003). Among the most efficient are also the algorithms based on the expansion of the function \(f\) in terms of Laguerre polynomials and the corresponding computation of \({\cal{L}}[f]\) and \({\cal{L}}^{-1}[F]\); See J. Abate, G. L. Choudhury, Inf. J Comput. 8, 413 (1996)
E. Titchmarsh, Introduction to the Theory of Fourier Integrals, 2nd edn. (Clarendon press, Oxford, 1948)
L. Grafakos, Classical And Modern Fourier Analysis (Prentice Hall, New Jersey, 2003)
M.L. Glasser, Some useful properties of the Hilbert transform. SIAM J. Math. Anal. 15, 1228 (1984)
R. Wong, Asymptotic expansion of the Hilbert transform. SIAM J. Math. Anal. 11, 92 (1980)
S.L. Hahn, Hilbert Transform in Signal Processing (Artech House, Boston, 1996)
W.J. Freeman, Origin, structure, and role of background EEG activity, Part 1. Analytic amplitude, Clin. Neurophys. 115, 2077 (2004); Part 2. Analytic phase, Clin. Neurophys. 115, 2089 (2004); Part 3. Neural frame classification, Clin. Neurophys. 116, 1118 (2005); Part 4. Neural frame simulation, Clin. Neurophys. 117, 572 (2006)
M. West, A. Krystal, EEG Recorded (Duke University)
C. Kittel, Introduction to Solid State Physics, 8th edn. (Wiley, New York, 2005)
M. Nandagopal, N. Arunajadai, On finite evaluation of finite Hilbert transform. Comput. Sci. Eng. 9, 90 (2007)
T. Hasegawa, T. Torii, Hilbert and Hadamard transforms by generalized Chebyshev expansion. J. Comput. Appl. Math. 51, 71 (1994)
W. Gautschi, J. Waldvogel, Computing the Hilbert transform of the generalized Laguerre and Hermite weight functions. BIT Numer. Math. 41, 490 (2001)
V.R. Kress, E. Martensen, Anwendung der Rechteckregel auf die reelle Hilberttransformation mit unendlichem Intervall. Z. Angew. Math. Mech. 50, 61 (1970)
F.W. King, G.J. Smethells, G.T. Helleloid, P.J. Pelzl, Numerical evaluation of Hilbert transforms for oscillatory functions: a convergence accelerator approach. Comput. Phys. Commun. 145, 256 (2002)
J.A.C. Weideman, Computing the Hilbert transform on the real line. Math. Comput. 64, 745 (1995). Attention: the authors use a non-standard definition \({{\rm sign}}(0)=1\); in Eq. (22) correct \(1/N\rightarrow 1/(2N)\)
X. Wang, Numerical implementation of the Hilbert transform, Ph.D. thesis, University of Saskatchewan, Saskatoon (2006)
H. Boche, M. Protzmann, A new algorithm for the reconstruction of the band-limited functions and their Hilbert transform. IEEE Trans. Instrum. Meas. 46, 442 (1997)
A.V. Oppenheim, R.W. Schafer, Discrete-Time Signal Processing, 2nd edn. (Prentice Hall, New Jersey, 1989)
R. Bracewell, The Fourier Transform and its Applications, 2nd edn. (McGraw-Hill Reading, New York, 1986)
F.W. King, Hilbert Transforms, Vol. 1 & 2 (Encyclopedia of Mathematics and its Applications, Vol. 124 & 125) (Cambridge University Press, Cambridge, 2009)
H.-G. Stark, Wavelets and Signal Processing. An Application-Based Introduction (Springer, Berlin, 2005)
P.S. Addison, The Illustrated Wavelet Transform Handbook, (Institute of Physics, Bristol, 2002)
G. Kaiser, A Friendly Guide to Wavelets (Birkhäuser, Boston, 1994). A physicist might find particular pleasure in physical (acoustic and electro-magnetic) wavelets: See G. Kaiser. J. Phys. A: Math. Gen. 36, R291 (2003)
J.F. Kirby, Which wavelet best reproduces the Fourier power spectrum? Comput. Geosci. 31, 846 (2005)
C. Torrence, G.P. Compo, A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 79, 61 (1998)
D. Jordan, R.W. Miksad, E.J. Powers, Implementation of the continuous wavelet transform for digital time series analysis. Rev. Sci. Instrum. 68, 1484 (1997)
G. Strang, T. Nguyen, Wavelets and Filter Banks, 2nd edn. (Wellesley-Cambridge Press, Cambridge, 1996)
D.B. Percival, A.T. Walden, Wavelet Methods For Time Series Analysis (Cambridge University Press, Cambridge, 2000)
J.S. Walker, A Primer on Wavelets and their Scientific Applications, 2nd edn. (Chapman & Hall/CRC, Boca Raton, 2008)
I. Daubechies, The wavelet transform time-frequency localization and signal analysis. IEEE Trans. Inf. Theory 36, 961 (1990)
I. Daubechies, Ten Lectures On Wavelets (SIAM, Philadelphia, 1992)
D.S. Taubman, M.W. Marcellin, Jpeg2000: Image Compression Fundamentals, Standards And Practice (Kluwer, Boston, 2002)
A. Cohen, I. Daubechies, J.-C. Feauveau, Biorthogonal bases of compactly supported wavelets. Commun. Pure Appl. Math. 45, 485 (1992)
A.R. Calderbank et al., Wavelet transforms that map integers to integers. Appl. Comput. Harmon. Anal. 5, 332 (1998)
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Širca, S., Horvat, M. (2018). Transformations of Functions and Signals. In: Computational Methods in Physics. Graduate Texts in Physics. Springer, Cham. https://doi.org/10.1007/978-3-319-78619-3_4
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