Page 515 - Applied Numerical Methods Using MATLAB

504 INDEX FOR MATLAB ROUTINES
clear S1.1-2 remove items from workspace, freeing up system
memory
clf S1.1-4 clear current figure window
compare DFT FFT S3.9-1 compare DFT with FFT
− −
cond() S2.2-2 condition number
constr() AH constrained minimization (in MATLAB 5.x)
contour() S1.1-5 2-D contour plot of a scalar-valued function of 2-D
variable
conv() S1.1-6 convolution of two sequences
or multiplication of two polynomials
cspline() S3.5 cubic spline interpolation
CtFT1() P1.26 Inverse Continuous-time Fourier Transform
curve fit() P3.9 weighted least-squares curve fitting
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c2d steq() S6.5-2 continuous-time state equation to discrete-time one
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dblquad() S1.1-7 2-D (double) integral
diag() S5.3 construct a diagonal matrix or get diagonals of a matrix
difapx() S5.4, AG2-3 difference approximation for numerical derivatives
diff() S5.10, P5.14 differences between neighboring elements in an array
disp() S1.1-3 display text or array onto the (monitor) screen
do cheby S3.3 approximate by Chebyshev polynomial
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do condition S2.2-2 condition numbers for ill-conditioned matrices
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do csplines S3.5 interpolate by cubic splines
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do FFT S3.9-1 do FFT (Fast Fourier Transform)
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do gauss S2.2-1 do Gauss elimination
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do hermit S3.6 do Hermite polynomial interpolation
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do interp2 S3.7 do 2-dimensional interpolation
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do lagranp S3.1 do Lagrange polynomial interpolation
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do lagnewch S3.3 try Lagrange/Newton/Chebyshev polynomial
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do lu dcmp S2.4-1 do LU decomposition (factorization)
− −
do MBK P6.4 simulate a mass-damper-spring system
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do newtonp S3.2 do Newton polynomial interpolation
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do newtonp1 S3.2 do Newton polynomial interpolation
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do pade() S3.4 do Pade (rational polynomial) approximation
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do polyfits() S3.8-2 do polynomial curve fitting
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do RDFT P3.20 do recursive DFT
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do quiver P6.0 use quiver() to plot the gradient vectors
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do rlse S2.1-4 do recursive least-squares estimation
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do wlse S3.8-2 do weighted least-squares curve fitting
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double() AG1 convert to double-precision
draw MBK P6.4 simulate a mass-damper-spring system
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dsolve() S6.6-2, symbolic differential equation solver
P6.3, AG5
eig() S8.1 eigenvalues and eigenvectors of a matrix
eig Jacobi() S8.4 find the eigenvalues/eigenvectors of a symmetric matrix
−
eig power() S8.3 find the largest eigenvalue & the corresponding
−
eigenvector
eig QR() P8.7 find eigenvalues using QR factorization
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eig QR Hs() P8.7 find eigenvalues using QR factorization via Hessenberg
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else S1.1-9 for conditional execution of statements
elseif S1.1-9 for conditional execution of statements
end S1.1-9 terminate for/while,/witch/try/if statements or last index
err of sol de() P6.9 evaluate the error of solution of differential eq.
− − −
eval() S1.1-5 (T1.3) evaluate a string containing a MATLAB expression