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A MATLAB differentiation matrix suite

Published:01 December 2000Publication History
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Abstract

A software suite consisting of 17 MATLAB functions for solving differential equations by the spectral collocation (i.e., pseudospectral) method is presented. It includes functions for computing derivatives of arbitrary order corresponding to Chebyshev, Hermite, Laguerre, Fourier, and sinc interpolants. Auxiliary functions are included for incorporating boundary conditions, performing interpolation using barycentric formulas, and computing roots of orthogonal polynomials. It is demonstrated how to use the package for solving eigenvalue, boundary value, and initial value problems arising in the fields of special functions, quantum mechanics, nonlinear waves, and hydrodynamic stability.

References

  1. ABRAMOWITZ,M.AND STEGUN, I. E. 1964. Handbook of Mathematical Functions. National Bureau of Standards, Washington, DC.Google ScholarGoogle Scholar
  2. ALHARGAN, F. A. 1996. A complete method for the computations of Mathieu characteristic numbers of integer orders. SIAM Rev. 38, 2, 239-255. Google ScholarGoogle Scholar
  3. BALTENSPERGER,R.AND BERRUT, J. P. 1999. The errors in calculating the pseudospectral differentiation matrices for Chebyshev-Gauss-Lobatto points. Comput. Math. Appl. 37,1, 41-48.Google ScholarGoogle Scholar
  4. BAYLISS, A., CLASS, A., AND MATKOWSKY, B. J. 1995. Roundoff error in computing derivatives using the Chebyshev differentiation matrix. J. Comput. Phys. 116, 2 (Feb.), 380-383. Google ScholarGoogle Scholar
  5. BERRUT, J. P. 1989. Barycentric formulae for cardinal (sinc-) interpolants. Numer. Math. 54, 703-718.Google ScholarGoogle Scholar
  6. BOYD, J. P. 1984. The asymptotic coefficients of Hermite function series. J. Comput. Phys. 54, 382-410.Google ScholarGoogle Scholar
  7. BOYD, J. P. 1989. Chebyshev and Fourier Spectral Methods. Springer-Verlag, Berlin, Germany.Google ScholarGoogle Scholar
  8. BREUER,K.S.AND EVERSON, R. M. 1992. On the errors incurred calculating derivatives using Chebyshev polynomials. J. Comput. Phys. 99, 1 (Mar.), 56-67. Google ScholarGoogle Scholar
  9. CANUTO, C., HUSSAINI,M.Y.,QUARTERONI, A., AND ZANG, T. A. 1988. Spectral Methods in Fluid Dynamics. Springer-Verlag, Berlin, Germany.Google ScholarGoogle Scholar
  10. COSTA,B.AND DON, W. S. 1999. Pseudopack 2000. See http://www.labma.ufrj.br/-bcosta/ PseudoPack2000/ Main.html.Google ScholarGoogle Scholar
  11. DON,W.S.AND SOLOMONOFF, A. 1995. Accuracy and speed in computing the Chebyshev collocation derivative. SIAM J. Sci. Comput. 16, 6 (Nov.), 1253-1268. Google ScholarGoogle Scholar
  12. DRAZIN,P.G.AND JOHNSON, R. S. 1989. Solitons: An Introduction. Cambridge University Press, New York, NY.Google ScholarGoogle Scholar
  13. DRAZIN,P.G.AND REID, W. H. 1981. Hydrodynamic Stability. Cambridge University Press, New York, NY.Google ScholarGoogle Scholar
  14. DUTT, A., GU, M., AND ROKHLIN, V. 1996. Fast algorithms for polynomial interpolation, integration, and differentiation. SIAM J. Numer. Anal. 33, 5, 1689-1711. Google ScholarGoogle Scholar
  15. EGGERT, N., JARRATT, M., AND LUND, J. 1987. Sinc function computation of the eigenvalues of Sturm-Liouville problems. J. Comput. Phys. 69, 1 (Mar. 1), 209-229. Google ScholarGoogle Scholar
  16. FLUGGE, S. 1971. Practical Quantum Mechanics I. Springer-Verlag, Berlin, Germany.Google ScholarGoogle Scholar
  17. FORNBERG, B. 1996. A Practical Guide to Pseudospectral Methods. Cambridge University Press, New York, NY.Google ScholarGoogle Scholar
  18. FUNARO, D. 1992. Polynomial Approximation of Differential Equations. Springer-Verlag, Berlin, Germany.Google ScholarGoogle Scholar
  19. FUNARO, D. 1993. Fortran routines for spectral methods. (available via anonymous FTP at ftp.ian.pv.cnr.it in pub/splibGoogle ScholarGoogle Scholar
  20. GOTTLIEB, D., HUSSAINI,M.Y.,AND ORSZAG, S. A. 1984. Theory and applications of spectral methods. In Spectral Methods for Partial Differential Equations, R. Voigt, D. Gottlieb, and M. Hussaini, Eds. 1-54.Google ScholarGoogle Scholar
  21. GREENGARD, L. 1991. Spectral integration and two-point boundary value problems. SIAM J. Numer. Anal. 28, 4 (Aug.), 1071-1080. Google ScholarGoogle Scholar
  22. GREENGARD,L.AND ROKHLIN, V. 1991. On the numerical solution of two-point boundary value problems. Comm. Pure Appl. Math. 44, 419-452.Google ScholarGoogle Scholar
  23. HENRICI, P. 1982. Essentials of Numerical Analysis with Pocket Calculator Demonstrations. John Wiley and Sons, Inc., New York, NY. Google ScholarGoogle Scholar
  24. HENRICI, P. 1986. Applied and Computational Complex Analysis: Discrete Fourier Analysis- Cauchy Integrals-Construction of Conformal Maps-Univalent Functions. Vol. 3. John Wiley and Sons, Inc., New York, NY. Google ScholarGoogle Scholar
  25. HUANG,W.AND SLOAN, D. M. 1992. The pseudospectral method for third-order differential equations. SIAM J. Numer. Anal. 29, 6 (Dec.), 1626-1647. Google ScholarGoogle Scholar
  26. HUANG,W.AND SLOAN, D. M. 1993. A new pseudospectral method with upwind features. IMA J. Num. Anal. 13, 413-430.Google ScholarGoogle Scholar
  27. HUANG,W.AND SLOAN, D. M. 1994. The pseudospectral method for solving differential eigenvalue problems. J. Comput. Phys. 111, 2 (Apr.), 399-409. Google ScholarGoogle Scholar
  28. ORSZAG, S. A. 1971. An accurate solution of the Orr-Sommerfeld equation. J. Fluid Mech. 50, 689-703.Google ScholarGoogle Scholar
  29. PRYCE, J. D. 1993. Numerical Solution of Sturm-Liouville Problems. Monographs on Numerical Analysis. Oxford University Press, Oxford, UK.Google ScholarGoogle Scholar
  30. REDDY,S.C.,SCHMID,P.J.,BAGGETT,J.S.,AND HENNINGSON, D. S. 1998. On stability of streamwise streaks and transition thresholds in plane channel flows. J. Fluid Mech. 365, 269-303.Google ScholarGoogle Scholar
  31. SCHONFELDER, J. L. 1978. Chebyshev expansions for the error and related functions. Math. Comput. 32, 1232-1240.Google ScholarGoogle Scholar
  32. SCHOOMBIE,S.W.AND BOTHA, J. F. 1981. Error estimates for the solution of the radial Schrodinger equation by the Rayleigh-Ritz finite element method. IMA J. Num. Anal. 1, 47-63.Google ScholarGoogle Scholar
  33. SHAMPINE,L.F.AND REICHELT, M. W. 1997. The MATLAB ODE suite. SIAM J. Sci. Comput. 18, 1, 1-22. Google ScholarGoogle Scholar
  34. SHARMA, A. 1972. Some poised and nonpoised problems of interpolation. SIAM Rev. 14, 129-151.Google ScholarGoogle Scholar
  35. STENGER, F. 1993. Numerical Methods Based on Sinc and Analytic Functions. Springer-Verlag, New York, NY.Google ScholarGoogle Scholar
  36. STRANG, G. 1986. A proposal for Toeplitz matrix calculations. Stud. Appl. Math. 74, 2 (Apr.), 171-176. Google ScholarGoogle Scholar
  37. TADMOR, E. 1986. The exponential accuracy of Fourier and Chebyshev differencing methods. SIAM J. Numer. Anal. 23, 1 (Feb.), 1-10. Google ScholarGoogle Scholar
  38. TANG, T. 1993. The Hermite spectral method for Gaussian-type functions. SIAM J. Sci. Comput. 14, 3 (May), 594-606. Google ScholarGoogle Scholar
  39. TANG,T.AND TRUMMER, M. R. 1996. Boundary layer resolving pseudospectral methods for singular perturbation problems. SIAM J. Sci. Comput. 17, 2, 430-438. Google ScholarGoogle Scholar
  40. THE MATHWORKS,INC. 1998. MATLAB 5.2.Google ScholarGoogle Scholar
  41. TREFETHEN, L. N. 2000. Spectral Methods in MATLAB. SIAM, Philadelphia, PA. Google ScholarGoogle Scholar
  42. WALEFFE, F. 1995. Hydrodynamic stability and turbulence: Beyond transients to a selfsustaining process. Stud. Appl. Math. 95, 319-343.Google ScholarGoogle Scholar
  43. WEIDEMAN, J. A. C. 1999. Spectral methods based on nonclassical orthogonal polynomials. In Approximations and Computation of Orthogonal Polynomials, W. Gautschi, G. Golub, and G. Opfer, Eds. Birkh~user, Basel, 239-251.Google ScholarGoogle Scholar
  44. WEIDEMAN,J.A.C.AND TREFETHEN, L. N. 1988. The eigenvalues of second-order spectral differentiation matrices. SIAM J. Numer. Anal. 25, 1279-1298.Google ScholarGoogle Scholar
  45. WELFERT, B. D. 1997. Generation of pseudospectral differentiation matrices I. SIAM J. Numer. Anal. 34, 4, 1640-1657. Google ScholarGoogle Scholar
  46. WIMP, J. 1984. Computation with Recurrence Relations. Pitman Publishing, Inc., Marshfield, MA.Google ScholarGoogle Scholar

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  1. A MATLAB differentiation matrix suite

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        George K. Adam

        The research work presented in this paper tackles the problem of solving differential equations using the spectral collocation method in a software system of 17 MATLAB functions created for this purpose. The algorithms described and the applications examined successfully show the importance of the differentiation matrix suite in the generation of spectral differentiation matrices based on Chebyshev, Fourier, and other interpolants. The algorithms and equations presented are quite significant, solving a variety of problems in scientific computation. The work documents the methods proposed using suitable mathematical terms and equations and sufficient numerical examples to prove its significance. However, further practical cases could have been given in order to justify its intended usage. In general, the length of the work, its presentation, and the references provided are quite sufficient and appropriate. Online Computing Reviews Service

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