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1: 3.8 Nonlinear Equations
Regula Falsi
Inverse linear interpolation (§3.3(v)) is used to obtain the first approximation: …
2: Mark J. Ablowitz
for appropriate data they can be linearized by the Inverse Scattering Transform (IST) and they possess solitons as special solutions. …
3: 31.16 Mathematical Applications
 thesis “Inversion problem for a second-order linear differential equation with four singular points”. …
4: 1.2 Elementary Algebra
The Inverse
If det( 𝐀 ) 0 , 𝐀 has a unique inverse, 𝐀 1 , such that …
n Linear Equations in n Unknowns
If det ( 𝐀 ) 0 the system of n linear equations in n unknowns, … and for the corresponding eigenvectors one has to solve the linear system …
5: Bibliography
  • M. J. Ablowitz and P. A. Clarkson (1991) Solitons, Nonlinear Evolution Equations and Inverse Scattering. London Mathematical Society Lecture Note Series, Vol. 149, Cambridge University Press, Cambridge.
  • M. J. Ablowitz and H. Segur (1977) Exact linearization of a Painlevé transcendent. Phys. Rev. Lett. 38 (20), pp. 1103–1106.
  • M. J. Ablowitz and H. Segur (1981) Solitons and the Inverse Scattering Transform. SIAM Studies in Applied Mathematics, Vol. 4, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA.
  • S. Axler (2015) Linear algebra done right. Third edition, Undergraduate Texts in Mathematics, Springer, Cham.
  • 6: 1.1 Special Notation
    x , y real variables.
    𝐀 1 inverse of the square matrix 𝐀
    linear operator defined on a manifold
    7: Bibliography O
  • A. B. Olde Daalhuis and F. W. J. Olver (1995a) Hyperasymptotic solutions of second-order linear differential equations. I. Methods Appl. Anal. 2 (2), pp. 173–197.
  • A. B. Olde Daalhuis and F. W. J. Olver (1995b) On the calculation of Stokes multipliers for linear differential equations of the second order. Methods Appl. Anal. 2 (3), pp. 348–367.
  • A. B. Olde Daalhuis and F. W. J. Olver (1998) On the asymptotic and numerical solution of linear ordinary differential equations. SIAM Rev. 40 (3), pp. 463–495.
  • A. B. Olde Daalhuis (1995) Hyperasymptotic solutions of second-order linear differential equations. II. Methods Appl. Anal. 2 (2), pp. 198–211.
  • A. B. Olde Daalhuis (1998a) Hyperasymptotic solutions of higher order linear differential equations with a singularity of rank one. Proc. Roy. Soc. London Ser. A 454, pp. 1–29.
  • 8: Errata
    This especially included updated information on matrix analysis, measure theory, spectral analysis, and a new section on linear second order differential operators and eigenfunction expansions. … The specific updates to Chapter 1 include the addition of an entirely new subsection §1.18 entitled “Linear Second Order Differential Operators and Eigenfunction Expansions” which is a survey of the formal spectral analysis of second order differential operators. The spectral theory of these operators, based on Sturm-Liouville and Liouville normal forms, distribution theory, is now discussed more completely, including linear algebra, matrices, matrices as linear operators, orthonormal expansions, Stieltjes integrals/measures, generating functions. …
  • Paragraph Inversion Formula (in §35.2)

    The wording was changed to make the integration variable more apparent.

  • Equations (4.45.8), (4.45.9)

    These equations have been rewritten to improve the numerical computation of arctan x .

  • 9: Bibliography B
  • A. W. Babister (1967) Transcendental Functions Satisfying Nonhomogeneous Linear Differential Equations. The Macmillan Co., New York.
  • P. M. Batchelder (1967) An Introduction to Linear Difference Equations. Dover Publications Inc., New York.
  • R. Blackmore and B. Shizgal (1985) Discrete ordinate solution of Fokker-Planck equations with non-linear coefficients. Phys. Rev. A 31 (3), pp. 1855–1868.
  • C. Brezinski (1999) Error estimates for the solution of linear systems. SIAM J. Sci. Comput. 21 (2), pp. 764–781.
  • J. C. Butcher (1987) The Numerical Analysis of Ordinary Differential Equations. Runge-Kutta and General Linear Methods. John Wiley & Sons Ltd., Chichester.
  • 10: 1.3 Determinants, Linear Operators, and Spectral Expansions
    §1.3 Determinants, Linear Operators, and Spectral Expansions
    §1.3(iv) Matrices as Linear Operators
    Linear Operators in Finite Dimensional Vector Spaces
    Square matices can be seen as linear operators because 𝐀 ( α 𝐚 + β 𝐛 ) = α 𝐀 𝐚 + β 𝐀 𝐛 for all α , β and 𝐚 , 𝐛 𝐄 n , the space of all n -dimensional vectors. … Let the columns of matrix 𝐒 be these eigenvectors 𝐚 1 , , 𝐚 n , then 𝐒 1 = 𝐒 H , and the similarity transformation (1.2.73) is now of the form 𝐒 H 𝐀 𝐒 = λ i δ i , j . …