diego898

%% A imple Least Squares problem
% https://en.wikipedia.org/wiki/Least_squares

% We first consider the most basic convex optimization problem, least-squares 
% (also known as linear regression). In a least-squares problem, we seek 
% x \in R^n that minimizes norm(Ax?b)

% Setup parameters
n = 100;
A = randn(2*n,n);

diego898

thanks to @neurodyne and this link for updated instructions

This works with the following versions of termsrv.dll

x64 - termsrv.dll - 6.3.9600.17095

Find	Replace
39813C0600000F849E310500	B80001000089813806000090
090085C07F078BD8	090085C090908BD8

diego898

Windows Registry Editor Version 5.00

[HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\Keyboard Layout]
"Scancode Map"=hex:00,00,00,00,00,00,00,00,03,00,00,00,3a,00,46,00,01,00,3a,00,00,00,00,00

diego898

#!/bin/sh

# This is necessary to make perl work with cygwin.  Cygwin passes
# "cygwin style" paths to the program in the #! statement and ActiveState
# perl does not know what /cygwin/d/... means.  

# So, we put #!/usr/local/bin/perl in the perl script and this is called
# This routine translates the path name to something of type d:/

args=""

diego898

function color_average(image,diameter,type,thresh)
%% image is the name of the file 'image.format'
%% diameter is the cell size
%% type: either 'circle' or 'square'
%% thresh: from 0 to 1. Size of the gap between cells

[colormat,~,~] = imread(image);
[x,y,z] = size(colormat);

rows = floor(x/diameter);

diego898

function [approx, error] = taylor_approx(func, point, order, range_offset)
%taylor_approx   Construct, return and plot the taylor series approx.
%
%   taylor_approx(func, point, order, range_offset) will construct the
%   taylor series approx of the string in func to the specified order
%   evaluated at some range offset centered around point.
%
%   approx is the symbolic approximation
%
%   error is the error values in the range