MATLAB Mathematics - SERC - Index of

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5 Differential Equations Changing DDE Integration Properties The default integration properties in the DDE solver dde23 are selected to handle common problems. In some cases, you can improve solver performance by overriding these defaults. You do this by supplying dde23 with an options structure that specifies one or more property values. For example, to change the relative error tolerance of dde23 from the default value of 1e-3 to 1e-4, 1 Create an options structure using the function ddeset by entering options = ddeset('RelTol', 1e-4); 2 Pass the options structure to dde23 as follows: sol = dde23(ddefun,lags,history,tspan,options) For a complete description of the available options, see the reference page for ddeset. 5-60
Boundary Value Problems for ODEs Boundary Value Problems for ODEs This section describes how to use MATLAB to solve boundary value problems (BVPs) of ordinary differential equations (ODEs). It provides: • A summary of the BVP functions and examples • An introduction to BVPs • A description of the BVP solver and its syntax • A discussion about changing default integration properties • General instructions for solving a BVP • Examples that use continuation to solve a difficult problem • Instructions for solving singular BVPs • Instructions for solving multipoint BVPs 5-61
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MATLAB® The Language of Technical
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Revision History June 2004 First pr
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2 Polynomials and Interpolation Pol
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Introduction to Initial Value ODE P
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vi Contents
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1 Matrices and Linear Algebra Funct
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1 Matrices and Linear Algebra Matri
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1 Matrices and Linear Algebra Addin
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1 Matrices and Linear Algebra If x
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1 Matrices and Linear Algebra y = v
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1 Matrices and Linear Algebra Vecto
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1 Matrices and Linear Algebra If A
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1 Matrices and Linear Algebra Inver
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1 Matrices and Linear Algebra X = p
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1 Matrices and Linear Algebra Matri
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1 Matrices and Linear Algebra compu
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1 Matrices and Linear Algebra Eigen
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1 Matrices and Linear Algebra produ
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1 Matrices and Linear Algebra Singu
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1 Matrices and Linear Algebra 1-44
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2 Polynomials and Interpolation Pol
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2 Polynomials and Interpolation pol
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2 Polynomials and Interpolation Cal
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2 Polynomials and Interpolation whe
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2 Polynomials and Interpolation Int
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2 Polynomials and Interpolation int
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2 Polynomials and Interpolation 2 G
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2 Polynomials and Interpolation for
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2 Polynomials and Interpolation Con
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2 Polynomials and Interpolation Lat
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2 Polynomials and Interpolation −
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2 Polynomials and Interpolation −
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2 Polynomials and Interpolation 7 3
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2 Polynomials and Interpolation T =
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2 Polynomials and Interpolation Bec
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2 Polynomials and Interpolation 2-3
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2 Polynomials and Interpolation 2-3
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3 Fast Fourier Transform (FFT) Intr
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3 Fast Fourier Transform (FFT) 200
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3 Fast Fourier Transform (FFT) 2 x
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3 Fast Fourier Transform (FFT) 500
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3 Fast Fourier Transform (FFT) Func
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4 Function Functions Function Summa
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4 Function Functions You can also c
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4 Function Functions 25 20 15 10 5
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4 Function Functions Minimizing Fun
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4 Function Functions To try fminsea
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4 Function Functions Plotting the R
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4 Function Functions The number of
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4 Function Functions and displays t
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4 Function Functions end function s
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4 Function Functions States of the
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4 Function Functions 100 80 60 40 2
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4 Function Functions You can verify
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4 Function Functions Troubleshootin
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4 Function Functions A three-dimens
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4 Function Functions Parameterizing
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4 Function Functions “Anonymous F
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5 Differential Equations Initial Va
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5 Differential Equations odephas3 o
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5 Differential Equations This secti
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5 Differential Equations The basic
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6 Sparse Matrices Function Summary
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6 Sparse Matrices This matrix requi
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6 Sparse Matrices S = (3,1) 1 (2,2)
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6 Sparse Matrices Now F = full(S) d
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6 Sparse Matrices Importing Sparse
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6 Sparse Matrices west0479 west0479
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6 Sparse Matrices The find Function
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6 Sparse Matrices of the rows and c
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6 Sparse Matrices The vertices of o
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6 Sparse Matrices 0 10 20 30 40 50
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6 Sparse Matrices 0 500 1000 1500 2
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6 Sparse Matrices simply sparse(m,n
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6 Sparse Matrices Similarly, S(:,p)
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6 Sparse Matrices The following MAT
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6 Sparse Matrices 0 Original 0 Reve
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6 Sparse Matrices QR Factorization
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6 Sparse Matrices shows that A has
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6 Sparse Matrices Functions for Ite
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6 Sparse Matrices set up the five-p
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6 Sparse Matrices Manipulating Spar
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6 Sparse Matrices Selected Bibliogr
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Index comparing sparse and full mat
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Index H hb1dae demo 5-35 hb1ode dem
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Index nonstiff ODE examples rigid b
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Index LU factorization 6-30 minimum
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Index twobvp demo 5-63 two-dimensio
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