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www.eeworm.com/read/140851/13059096
m demknn1.m
%DEMKNN1 Demonstrate nearest neighbour classifier.
%
% Description
% The problem consists of data in a two-dimensional space. The data is
% drawn from three spherical Gaussian distributions with
www.eeworm.com/read/140851/13059144
m~ demhmc1.m~
%DEMHMC1 Demonstrate Hybrid Monte Carlo sampling on mixture of two Gaussians.
%
% Description
% The problem consists of generating data from a mixture of two
% Gaussians in two dimensions using a
www.eeworm.com/read/140851/13059296
m demglm1.m
%DEMGLM1 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. Th
www.eeworm.com/read/140851/13059398
m demglm2.m
%DEMGLM2 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. Th
www.eeworm.com/read/140700/13065904
txt alg112.txt
> restart;
> # NONLINEAR SHOOTING ALGORITHM 11.2
> #
> # To approximate the solution of the nonlinear boundary-value problem
> #
> # Y'' = F(X,Y,Y'), A
www.eeworm.com/read/140700/13065940
txt alg055.txt
> restart;
> # ADAMS VARIABLE STEP-SIZE PREDICTOR-CORRECTOR ALGORITHM 5.5
> #
> # To approximate the solution of the initial value problem
> # y' = f( t, y ), a
www.eeworm.com/read/140700/13066210
txt alg112.txt
> restart;
> # NONLINEAR SHOOTING ALGORITHM 11.2
> #
> # To approximate the solution of the nonlinear boundary-value problem
> #
> # Y'' = F(X,Y,Y'), A
www.eeworm.com/read/140700/13066242
txt alg055.txt
> restart;
> # ADAMS VARIABLE STEP-SIZE PREDICTOR-CORRECTOR ALGORITHM 5.5
> #
> # To approximate the solution of the initial value problem
> # y' = f( t, y ), a
www.eeworm.com/read/140698/13066475
c alg051.c
/*
* EULER'S ALGORITHM 5.1
*
* TO APPROXIMATE THE SOLUTION OF THE INITIAL VALUE PROBLEM:
* Y' = F(T,Y), A
www.eeworm.com/read/140698/13066635
c alg055.c
/*
* ADAMS VARIABLE STEP-SIZE PREDICTOR-CORRECTOR ALGORITHM 5.5
*
* To approximate the solution of the initial value problem
*
* y' = f( t, y ), a