GNU Octave

Some Matlab (Octave) tutorials

Some Matlab (Octave) resources

nonhomogeneous nonlinear ordinary differential equations

nonlinear systems of equations

random variables

These .m-functions can be used to compute probability distribution functions and to generate samples of random variables.
Distribution PDF, fX(x) CDF, FX(x) inverse CDF, FX-1(p) generate sample, x1 ... xN
uniform unifpdf.m unifcdf.m unifinv.m rand.m
triangular triangular_pdf.m triangular_cdf.m triangular_inv.m triangular_rnd.m
quadratic quadratic_pdf.m quadratic_cdf.m quadratic_inv.m quadratic_rnd.m
cubic cubic_pdf.m cubic_cdf.m cubic_inv.m cubic_rnd.m
quartic quartic_pdf.m quartic_cdf.m quartic_inv.m quartic_rnd.m
quintic quintic_pdf.m quintic_cdf.m quintic_inv.m quintic_rnd.m
normal normpdf.m normcdf.m norminv.m randn.m
log-normal logn_pdf.m logn_cdf.m logn_inv.m logn_rnd.m
Poisson Poisson_pmf.m Poisson_cdf.m Poisson_rnd.m
exponential exp_pdf.m exp_cdf.m exp_inv.m exp_rnd.m
Rayleigh Rayleigh_pdf.m Rayleigh_cdf.m Rayleigh_inv.m Rayleigh_rnd.m
gamma gamma_pdf.m gamma_cdf.m gamma_inv.m gamma_rnd.m
Laplace Laplace_pdf.m Laplace_cdf.m Laplace_inv.m Laplace_rnd.m
GEV GEV_pdf.m GEV_cdf.m GEV_inv.m GEV_rnd.m

nonlinear constrained optimization, in general

These .m-functions implement methods for minimizing a function of several parameters subject to a set of inequality constraints:
minimize f(x) such that g(x) ≤ 0,
where x is a vector of design variables, f(x) is a scalar-valued objective function, and g(x) is a vector of constraints.

nonlinear least squares via Levenberg-Marquardt

linear least squares with l1 regularization

signal processing

linear time-invariant systems analysis


© 2001-2019 Henri P. Gavin; updated: 9-27-2001, 12-15-2003, 1-7-2004, 1-6-2005, 1-22-2005, 2-1-2005, 2-14-2005, 1-11-2006, 2-14-2008, 2-28-2008, 3-24-2008, 1-8-2009, 8-7-2009, 1-5-2011, 1-8-2014, 1-7-2015, 1-13-2016, 2017-09-27