Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-10T15:18:05.921Z Has data issue: false hasContentIssue false

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:lilian@ntu.edu.sg
Get access

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

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