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Discrete Prolate Spheroidal Wave Functions: Further Spectral Analysis and Some Related Applications

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For fixed \(W\in \big (0,\frac{1}{2}\big )\) and positive integer \(N\ge 1\), the discrete prolate spheroidal wave functions (DPSWFs), denoted by \(U_{k,W}^N\), \(0\le k\le N-1\) form the set of eigenfunctions of the positive and finite rank integral operator \({\widetilde{Q}}_{N,W}\), defined on \(L^2(-1/2,1/2)\), with kernel \(K_N(x,y)=\frac{\sin (N\pi (x-y))}{\sin (\pi (x-y))}\, {\mathbf {1}}_{[-W,W]}(y)\). It is well known that the DPSWFs have a wide range of signal processing applications. These applications rely heavily on the properties of the DPSWFs as well as the behaviour of their eigenvalues \({{\widetilde{\lambda }}}_{k,N}(W)\). In his pioneer work (Slepian in Bell Syst. Tech. J. 57: 1371–1430,1978) D. Slepian has given the properties of the DPSWFs, their asymptotic approximations as well as the asymptotic behaviour and asymptotic decay rate of these eigenvalues. In this work, we give further properties as well as new non-asymptotic decay rates of the spectrum of the operator \({\widetilde{Q}}_{N,W}\). In particular, we show that each eigenvalue \({{\widetilde{\lambda }}}_{k,N}(W)\) is up to a small constant bounded above by the corresponding eigenvalue, associated with the classical prolate spheroidal wave functions (PSWFs). Then, based on the well established results concerning the behaviour of the eigenvalues associated with the PSWFs, we extend these results to the eigenvalues \({{\widetilde{\lambda }}}_{k,N}(W)\). Also, we show that the DPSWFs can be used for the approximation of classical band-limited functions, as well as those functions belonging to periodic Sobolev spaces. Finally, we provide the reader with some numerical examples that illustrate the different results of this work.

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References

  1. Slepian, D.: Prolate spheroidal wave functions, Fourier analysis and uncertainty-V: The discrete Case. Bell Syst. Tech. J. 57, 1371–1430 (1978)

    Article  Google Scholar 

  2. Davenport, M.A., Wakin, M.B.: Compressive sensing of analog signals using discrete prolate spheroidal sequences. Appl. Comput. Harmon. Anal. 33, 438–472 (2012)

    Article  MathSciNet  Google Scholar 

  3. Yin, F., Debes, C., Zoubir, A.M.: Parametric waveform design using discrete prolate spheroidal sequences for enhanced detection of extended targets. IEEE Trans. Signal Process. 60(9), 4525–4536 (2012)

    Article  MathSciNet  Google Scholar 

  4. Adcock, B., Huybrechs, D.: On the numerical stability of Fourier extensions. Found. Comput. Math. 14(4), 635–687 (2014)

    Article  MathSciNet  Google Scholar 

  5. Landau, H.J., Pollak, H.O.: Prolate spheroidal wave functions, Fourier analysis and uncertainty-III. The dimension of space of essentially time-and band-limited signals. Bell Syst. Tech. J. 41, 1295–1336 (1962)

    Article  MathSciNet  Google Scholar 

  6. Slepian, D., Pollak, H.O.: Prolate spheroidal wave functions, Fourier analysis and uncertainty I. Bell Syst. Tech. J. 40, 43–64 (1961)

    Article  MathSciNet  Google Scholar 

  7. Bonami, A., Karoui, A.: Spectral decay of time and frequency limiting operator. Appl. Comput. Harmon. Anal. 42, 1–20 (2017)

    Article  MathSciNet  Google Scholar 

  8. Bonami, A., Jaming, P., Karoui, A.: Non-asymptotic behaviour of the sinc-kernel operator and related applications (2018). arXiv:1804.01257

  9. Hogan, J.A., Lakey, J.D.: Duration and Bandwidth Limiting: Prolate Functions, Sampling, and Applications Applied and Numerical Harmonic Analysis Series. Birkhäuser, London (2013)

    Google Scholar 

  10. Slepian, D.: Some asymptotic expansions for prolate spheroidal wave functions. Stud. Appl. Math. 44(4), 99–140 (1965)

    MathSciNet  MATH  Google Scholar 

  11. Zhu, Z., Wakin, M.B.: Approximating sampled sinusoids and multiband signals using multiband modulated DPSS dictionaries. J. Fourier Anal. Appl. 23, 1263–1310 (2017)

    Article  MathSciNet  Google Scholar 

  12. Olver, F.W., Lozier, D.W., Boisvert, R.F., Clark, C.W.: NIST Handbook of Mathematical Functions. Cambridge University Press, New York (2010)

    MATH  Google Scholar 

  13. Batir, N.: Inequalities for the gamma function. Arch. Math. 91, 554–563 (2008)

    Article  MathSciNet  Google Scholar 

  14. Bonami, A., Karoui, A.: Random discretization of the finite Fourier transform and related kernel random matrices (2019). availbale at arxiv:1703.10459

  15. Karnik, S., Zhu, Z., Wakin, M., Romberg, J., Davenport, M.: The fast Slepian transform. Appl. Comput. Harmon. Anal. 46, 624–652 (2019)

    Article  MathSciNet  Google Scholar 

  16. Nazarov, F.L.: Complete version of Turàn’s lemma for trigonometric polynomials on the unit circumference. In: Havin, V.P., Nikolski, N.K. (eds.) Complex Analysis, Operators, and Related Topics. Operator Theory: Advances and Applications, vol. 113, pp. 239–246. Birkhäseur Verlag Basel, Switzerland (2000)

  17. Zwald Laurent, L., Blanchard, G.: On the convergence of eigenspaces in kernel principal component analysis. In: Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference (Neural Information Processing). MIT Press (2006)

  18. Wang, L.L.: Analysis of spectral approximations using prolate spheroidal wave functions. Math. Comp. 79, 807–827 (2010)

    Article  MathSciNet  Google Scholar 

  19. Jaming, P., Karoui, A., Spektor, S.: The approximation of almost time- and band-limited functions by their expansion in some orthogonal polynomials bases. J. Approx. Theory 212, 41–65 (2016)

    Article  MathSciNet  Google Scholar 

  20. Karoui, A., Moumni, T.: New efficient methods of computing the prolate spheroidal wave functions and their corresponding eigenvalues. Appl. Comput. Harmon. Anal. 24(3), 269–289 (2008)

    Article  MathSciNet  Google Scholar 

  21. Bonami, A., Karoui, A.: Approximation in Sobolev spaces by prolate spheroidal wave functions. Appl. Comput. Harmon. Anal. 42, 361–377 (2017)

    Article  MathSciNet  Google Scholar 

  22. Wang, L.L., Zhang, J.: A new generalization of the PSWFs with applications to spectral approximations on quasi-uniform grids. Appl. Comput. Harmon. Anal. 29, 303–329 (2010)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

The authors thank very much the anonymous referees for the valuable comments and suggestions that helped them to improve the revised version of this work.

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Correspondence to Abderrazek Karoui.

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This work is supported by the Tunisian DGRST research Grant UR 13ES47 and PHC-Utique research Project 20G1503.

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Boulsane, M., Bourguiba, N. & Karoui, A. Discrete Prolate Spheroidal Wave Functions: Further Spectral Analysis and Some Related Applications. J Sci Comput 82, 54 (2020). https://doi.org/10.1007/s10915-020-01157-5

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  • DOI: https://doi.org/10.1007/s10915-020-01157-5

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