Numerical Differentiation Toolbox
Numerical Differentiation Toolbox
This toolbox supplies functions to evaluate derivatives, partial derivatives, gradients, directional derivatives, Jacobians, and Hessians using the forward difference, central difference, and complex-step approximations of a derivative.
Documentation
Toolbox Documentation
Technical Documentation
To open the home page of the toolbox documentation in MATLAB, type
doc_NDT
in the Command Window. To open the documentation of a specific function with name function_name
from the Command Window, type
doc_NDT function_name
To open the PDF file with the technical documentation (Numerical_Differentiation.pdf) from the Command Window, type
doc_NDT tech
Complex-Step Differentiation Functions
df = iderivative(f,x0)
pf = ipartial(f,x0,k)
g = igradient(f,x0)
Dv = idirectional(f,x0,v)
J = ijacobian(f,x0)
H = ihessian(f,x0)
"Complexified" Functions
y = iabs(x)
z = iatan2(y,x)
z = iatan2d(y,x)
z = idot(x,y)
m = imax(x1,x2)
m = imin(x1,x2)
r = imod(a,n)
y = inorm(x)
Central Difference Differentiation Functions
df = cderivative(f,x0)
pf = cpartial(f,x0,k)
g = cgradient(f,x0)
Dv = cdirectional(f,x0,v)
J = cjacobian(f,x0)
H = chessian(f,x0)
Forward Difference Differentiation Functions
df = fderivative(f,x0)
pf = fpartial(f,x0,k)
g = fgradient(f,x0)
Dv = fdirectional(f,x0,v)
J = fjacobian(f,x0)
H = fhessian(f,x0)
Citar como
Tamas Kis (2022). Numerical Differentiation Toolbox (https://github.com/tamaskis/Numerical_Differentiation_Toolbox-MATLAB/releases/tag/v6.4.0), GitHub. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformas
Windows macOS LinuxEtiquetas
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