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On Spectral Approximations by Generalized Slepian Functions

Published online by Cambridge University Press:  28 May 2015

Jing Zhang
Affiliation:
Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, 637371, Singapore
Li-Lian Wang*
Affiliation:
Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, 637371, Singapore
*
Corresponding author.Email address:[email protected]
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Abstract

We introduce a family of orthogonal functions, termed as generalized Slepian functions (GSFs), closely related to the time-frequency concentration problem on a unit disk in D. Slepian [19]. These functions form a complete orthogonal system in with , and can be viewed as a generalization of the Jacobi polynomials with parameter (α, 0). We present various analytic and asymptotic properties of GSFs, and study spectral approximations by such functions.

Type
Research Article
Copyright
Copyright © Global Science Press Limited 2011

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References

[1]Abramowitz, M. and Stegun, I.. Handbook of Mathematical Functions. Dover, New York, 1964.Google Scholar
[2]Adams, R.A.. Sobolov Spaces. Acadmic Press, New York, 1975.Google Scholar
[3]Al-Gwaiz, M.A.. Sturm-Liouville Theory and its Applications. Springer, 2007.Google Scholar
[4]Beylkin, G. and Monzón, L.. On generalized Gaussian quadratures for exponentials and their applications. Appl. Comput. Harmon. Anal., 12(3):332373, 2002.CrossRefGoogle Scholar
[5]Beylkin, G. and Sandberg, K.. Wave propagation using bases for bandlimited functions. Wave Motion, 41(3):263291, 2005.CrossRefGoogle Scholar
[6]Bouwkamp, C.J.. On the theory of spheroidal wave functions of order zero. Nederl. Akad. Wetensch. Proc., 53:931944, 1965.Google Scholar
[7]Boyd, J.P.. Prolate spheroidal wavefunctions as an alternative to Chebyshev and Legen-dre polynomials for spectral element and pseudospectral algorithms. J. Comput. Phys., 199(2):688716, 2004.CrossRefGoogle Scholar
[8]Boyd, J.P.. Algorithm 840: computation of grid points, quadrature weights and derivatives for spectral element methods using prolate spheroidal wave functions—prolate elements. ACM Trans. Math. Software, 31(1):149165, 2005.CrossRefGoogle Scholar
[9]Canuto, C., Hussaini, M.Y., Quarteroni, A., and Zang, T.A.. Spectral Methods: Fundamentals in Single Domains. Springer, Berlin, 2006.CrossRefGoogle Scholar
[10]Chen, Q.Y., Gottlieb, D., and Hesthaven, J.S.. Spectral methods based on prolate spheroidal wave functions for hyperbolic PDEs. SIAM J. Numer. Anal., 43(5):19121933, 2005.CrossRefGoogle Scholar
[11]Coddington, E.A. and Levinson, N.. Theory of Ordinary Differential Equations. McGraw-Hill, New York, 1955.Google Scholar
[12]Dabrowska, D.. Recovering signals from inner products involving prolate spheroidals in the presence of jitter. Math. Comp., 74(249):279290, 2005.CrossRefGoogle Scholar
[13]Guo, B. and Wang, L.L. Jacobi approximations in non-uniformly Jacobi-weighted Sobolev spaces. J. Approx. Theory, 128(1):141, 2004.CrossRefGoogle Scholar
[14]Kovvali, N., Lin, W., and Carin, L.. Pseudospectral method based on prolate spheroidal wave functions for frequency-domain electromagnetic simulations. IEEE Trans. Antennas and Propagation, 53:39904000, 2005.CrossRefGoogle Scholar
[15]Kovvali, N., Lin, W., Zhao, Z., Couchman, L., and Carin, L.. Rapid prolate pseudospectral differentiation and interpolation with the fast multipole method. SIAM J. Sci. Comput., 28(2):485–497, 2006.Google Scholar
[16]Landau, H.J. and Pollak, H.O.. Prolate spheroidal wave functions, Fourier analysis and uncertainty. II. Bell System Tech. J., 40:6584, 1961.CrossRefGoogle Scholar
[17]Landau, H.J. and Pollak, H.O.. Prolate spheroidal wave functions, Fourier analysis and uncertainty. III. Bell System Tech. J., 41:12951336, 1962.CrossRefGoogle Scholar
[18]Rokhlin, V. and Xiao, H.. Approximate formulae for certain prolate spheroidal wave functions valid for large values of both order and band-limit. Appl. Comput. Harmon. Anal., 22(1):105–123, 2007.Google Scholar
[19]Slepian, D.. Prolate spheroidal wave functions, Fourier analysis and uncertainity. IV. Bell System Tech. J., 43:30093057, 1964.CrossRefGoogle Scholar
[20]Slepian, D. and Pollak, H.O.. Prolate spheroidal wave functions, Fourier analysis and uncertainty. I. Bell System Tech. J., 40:4363, 1961.CrossRefGoogle Scholar
[21]Szegö, G.. Orthogonal Polynomials. AMS Coll. Publ., 1975.Google Scholar
[22]Taylor, M.A. and Wingate, B.A.. A generalization of prolate spheroidal functions with more uniform resolution to the triangle. J. Engrg. Math., 56(3):221235, 2006.CrossRefGoogle Scholar
[23]Walter, G.G. and Shen, X.. Wavelets based on prolate spheroidal wave functions. Journal of Fourier Analysis and Applications, 10(1):126, 2004.CrossRefGoogle Scholar
[24]Wang, L.L.. Analysis of spectral approximations using prolate spheroidal wave functions. Math. Comp., 79(270):807827, 2010.CrossRefGoogle Scholar
[25]Wang, L.L. and Zhang, J.. A new generalization of the PSWFs with applications to spectral approximations on quasi-uniform grids. Appl. Comput. Harmon. Anal., 29(3):303329, 2010.CrossRefGoogle Scholar
[26]Watson, G. N.. A Treatise on the Theory of Bessel Functions. Cambridge Univ. Pr., 1966.Google Scholar
[27]Xiao, H., Rokhlin, V., and Yarvin, N.. Prolate spheroidal wavefunctions, quadrature and interpolation. Inverse Problems, 17(4):805838, 2001.CrossRefGoogle Scholar