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11: 18.27 q -Hahn Class
β–ΊThe q -hypergeometric OP’s comprise the q -Hahn class (or q -linear lattice class) OP’s and the Askey–Wilson class (or q -quadratic lattice class) OP’s (§18.28). … β–ΊThe q -Hahn class OP’s comprise systems of OP’s { p n ⁑ ( x ) } , n = 0 , 1 , , N , or n = 0 , 1 , 2 , , that are eigenfunctions of a second order q -difference operator. …In the q -Hahn class OP’s the role of the operator d / d x in the Jacobi, Laguerre, and Hermite cases is played by the q -derivative π’Ÿ q , as defined in (17.2.41). …
12: 3.6 Linear Difference Equations
§3.6 Linear Difference Equations
β–Ί
3.6.2 a n ⁒ Ξ” 2 ⁑ w n 1 + ( 2 ⁒ a n b n ) ⁒ Ξ” ⁑ w n 1 + ( a n b n + c n ) ⁒ w n 1 = d n ,
β–Ίwhere Ξ” ⁑ w n 1 = w n w n 1 , Ξ” 2 ⁑ w n 1 = Ξ” ⁑ w n Ξ” ⁑ w n 1 , and n β„€ . … β–Ί
§3.6(vii) Linear Difference Equations of Other Orders
13: Bibliography T
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  • L. N. Trefethen and D. Bau (1997) Numerical Linear Algebra. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA.
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  • S. Tsujimoto, L. Vinet, and A. Zhedanov (2012) Dunkl shift operators and Bannai-Ito polynomials. Adv. Math. 229 (4), pp. 2123–2158.
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  • S. A. Tumarkin (1959) Asymptotic solution of a linear nonhomogeneous second order differential equation with a transition point and its application to the computations of toroidal shells and propeller blades. J. Appl. Math. Mech. 23, pp. 1549–1565.
  • 14: 1.16 Distributions
    β–ΊThe linear space of all test functions with the above definition of convergence is called a test function space. … β–ΊA mapping Ξ› : π’Ÿ ⁑ ( I ) β„‚ is a linear functional if … β–ΊA tempered distribution is a continuous linear functional Ξ› on 𝒯 . … β–ΊA distribution in ℝ n is a continuous linear functional on π’Ÿ n . … β–ΊTempered distributions are continuous linear functionals on this space of test functions. …
    15: Bibliography H
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  • G. J. Heckman (1991) An elementary approach to the hypergeometric shift operators of Opdam. Invent. Math. 103 (2), pp. 341–350.
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  • J. H. Hubbard and B. B. Hubbard (2002) Vector Calculus, Linear Algebra, and Differential Forms: A Unified Approach. 2nd edition, Prentice Hall Inc., Upper Saddle River, NJ.
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  • C. Hunter (1981) Two Parametric Eigenvalue Problems of Differential Equations. In Spectral Theory of Differential Operators (Birmingham, AL, 1981), North-Holland Math. Stud., Vol. 55, pp. 233–241.
  • 16: Bibliography K
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  • A. A. Kapaev (2004) Quasi-linear Stokes phenomenon for the Painlevé first equation. J. Phys. A 37 (46), pp. 11149–11167.
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  • E. H. Kaufman and T. D. Lenker (1986) Linear convergence and the bisection algorithm. Amer. Math. Monthly 93 (1), pp. 48–51.
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  • T. H. Koornwinder (2006) Lowering and Raising Operators for Some Special Orthogonal Polynomials. In Jack, Hall-Littlewood and Macdonald Polynomials, Contemp. Math., Vol. 417, pp. 227–238.
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  • T. H. Koornwinder (2015) Fractional integral and generalized Stieltjes transforms for hypergeometric functions as transmutation operators. SIGMA Symmetry Integrability Geom. Methods Appl. 11, pp. Paper 074, 22.
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  • J. J. Kovacic (1986) An algorithm for solving second order linear homogeneous differential equations. J. Symbolic Comput. 2 (1), pp. 3–43.
  • 17: Philip J. Davis
    β–ΊAt that time John Todd was Chief of the Numerical Analysis Section of the Applied Mathematics Division and head of the Computation Laboratory that co-developed, with the NBS Electronic Computer Laboratory, the Standards Eastern Automatic Computer (SEAC), the first fully operational stored-program electronic digital computer in the United States. … β–ΊThis immediately led to discussions among some of the project members about what might be possible, and the discovery that some interactive graphics work had already been done for the NIST Matrix Market, a publicly available repository of test matrices for comparing the effectiveness of numerical linear algebra algorithms. …
    18: Bibliography G
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  • L. Gårding (1947) The solution of Cauchy’s problem for two totally hyperbolic linear differential equations by means of Riesz integrals. Ann. of Math. (2) 48 (4), pp. 785–826.
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  • W. Gautschi (1997b) The Computation of Special Functions by Linear Difference Equations. In Advances in Difference Equations (Veszprém, 1995), S. Elaydi, I. GyΕ‘ri, and G. Ladas (Eds.), pp. 213–243.
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  • A. Gil and J. Segura (2003) Computing the zeros and turning points of solutions of second order homogeneous linear ODEs. SIAM J. Numer. Anal. 41 (3), pp. 827–855.
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  • J. J. Gray (2000) Linear Differential Equations and Group Theory from Riemann to Poincaré. 2nd edition, Birkhäuser Boston Inc., Boston, MA.
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  • E. P. Gross and S. Ziering (1958) Kinetic theory of linear shear flow. Phys. Fluids 1 (3), pp. 215–224.
  • 19: Bibliography R
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  • M. Rahman (1981) A non-negative representation of the linearization coefficients of the product of Jacobi polynomials. Canad. J. Math. 33 (4), pp. 915–928.
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  • M. Reed and B. Simon (1978) Methods of Modern Mathematical Physics, Vol. 4, Analysis of Operators. Academic Press, New York.
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  • E. Ya. Remez (1957) General Computation Methods of Chebyshev Approximation. The Problems with Linear Real Parameters. Publishing House of the Academy of Science of the Ukrainian SSR, Kiev.
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  • S. Ritter (1998) On the computation of Lamé functions, of eigenvalues and eigenfunctions of some potential operators. Z. Angew. Math. Mech. 78 (1), pp. 66–72.
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  • G. Rota, D. Kahaner, and A. Odlyzko (1973) On the foundations of combinatorial theory. VIII. Finite operator calculus. J. Math. Anal. Appl. 42, pp. 684–760.
  • 20: 3.11 Approximation Techniques
    β–ΊAlso, in cases where f ⁒ ( x ) satisfies a linear ordinary differential equation with polynomial coefficients, the expansion (3.11.11) can be substituted in the differential equation to yield a recurrence relation satisfied by the c n . … β–ΊWith b 0 = 1 , the last q equations give b 1 , , b q as the solution of a system of linear equations. … β–Ί(3.11.29) is a system of n + 1 linear equations for the coefficients a 0 , a 1 , , a n . … β–ΊMore generally, let f ⁒ ( x ) be approximated by a linear combination … β–ΊIn consequence of this structure the number of operations can be reduced to n ⁒ m = n ⁒ log 2 ⁑ n operations. …