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www.eeworm.com/read/469416/6976511
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/467534/7005220
java gaacanvas.java
import java.awt.*;
import java.applet.*;
class GaaCanvas extends Canvas
{
GaaProblem problem;
GaaPopulation pop;
GaaFunction function;
Graphics Gra;
Color color;
boolean first;
www.eeworm.com/read/467287/7009243
readme
1. The problem was caused by an overflow in the arithmetic coder
due to long strings of repeated characters. This has been
fixed.
2. The program now tests for repeated strings and by
www.eeworm.com/read/364251/7075507
todo
124907 HTML parse buffer problem when parsing larse in-memory docs
124110 DTD validation && wrong namespace
123564 xmllint --html --format
TODO for the XML parser and stuff:
==========
www.eeworm.com/read/440159/7100004
h surface.h
struct particleline *INIT_PARTICLES(int *N,int imax,int jmax,
REAL delx,REAL dely,
int ppc,char *problem,REAL **U,REAL **V);
vo
www.eeworm.com/read/461241/7231193
m calculate_domain_size.m
disp('calculating the number of cells in the problem space');
number_of_spheres = size(spheres,2);
number_of_bricks = size(bricks,2);
% find the minimum and maximum coordinates of a
% box en
www.eeworm.com/read/461235/7231515
m calculate_domain_size.m
disp('calculating the number of cells in the problem space');
number_of_spheres = size(spheres,2);
number_of_bricks = size(bricks,2);
% find the minimum and maximum coordinates of a
% box en
www.eeworm.com/read/457742/7318212
m bandb.m
function [optimal,itercount]=bandb(opts)
% main function for the l1l1 branch and bound algorithm
% this takes a structure with all the problem specs as input
% and returns a structure cont
www.eeworm.com/read/455917/7361837
m ldadesign.m
function LWt=LDADesign(n,m,sampleset,classnum,samplelabel,eignum)
% LDADESIGN will return LDA transformation matrix
% n denotes the problem's dimension
% m is the number of samples
% sampleset sto
www.eeworm.com/read/455917/7361843
m eldadesign.m
function LWt=ELDADesign(n,m,sampleset,classnum,samplelabel,eignum)
% ELDADESIGN will return ELDA(efficient LDA) transformation matrix
% n denotes the problem's dimension
% m is the number of sample