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	<title>Stone Studio &#187; Matlab Archives </title>
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		<title>Example of the Matlab Precision Issue</title>
		<link>http://wei-jiang.com/programming/matlab/example-of-the-matlab-precision-issue</link>
		<comments>http://wei-jiang.com/programming/matlab/example-of-the-matlab-precision-issue#comments</comments>
		<pubDate>Fri, 12 Mar 2010 00:06:08 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/?p=1764</guid>
		<description><![CDATA[I noticed that there are many people comparing Matlab with Maple, Mathematica etc. to find out what&#8217;s the best Maths package for them. But many of them didn&#8217;t realize the limitations of Matlab. I put up an article about the Birthday Problem in probability, If you try to solve it analytically like: 11 - factorial&#40;365&#41;/factorial&#40;336&#41;/365^30 [...]]]></description>
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		<slash:comments>1</slash:comments>
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		<item>
		<title>EigTool: Matlab Package for Computing Pseudospectra of Dense and Sparse Matrices</title>
		<link>http://wei-jiang.com/programming/matlab/eigtool-matlab-package-for-computing-pseudospectra-of-dense-and-sparse-matrices</link>
		<comments>http://wei-jiang.com/programming/matlab/eigtool-matlab-package-for-computing-pseudospectra-of-dense-and-sparse-matrices#comments</comments>
		<pubDate>Sat, 20 Feb 2010 23:55:18 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>
		<category><![CDATA[toolbox]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/programming/matlab/eigtool-matlab-package-for-computing-pseudospectra-of-dense-and-sparse-matrices</guid>
		<description><![CDATA[EigTool is a free MATLAB package for computing pseudospectra of dense and sparse matrices. It also provides a graphical interface to MATLAB&#8217;s built-in eigs routine (ARPACK) for large-scale eigenvalue computations. EigTool was developed from 1999 &#8211; 2002 by Thomas G. Wright at the Oxford University Computing Laboratory, under the direction of Nick Trefethen. The software [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<item>
		<title>ChebFun: Matlab Toolbox Numerical computation</title>
		<link>http://wei-jiang.com/programming/matlab/chebfun-matlab-toolbox-numerical-computation</link>
		<comments>http://wei-jiang.com/programming/matlab/chebfun-matlab-toolbox-numerical-computation#comments</comments>
		<pubDate>Sat, 20 Feb 2010 23:53:04 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>
		<category><![CDATA[toolbox]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/programming/matlab/chebfun-matlab-toolbox-numerical-computation</guid>
		<description><![CDATA[The aim of the chebfun system is to &#8220;feel symbolic but run at the speed of numerics&#8221;. More precisely our vision is to achieve for functions what floating-point arithmetic achieves for numbers: rapid computation in which each successive operation is carried out exactly apart from a rounding error that is very small in relative terms [...]]]></description>
		<wfw:commentRss>http://wei-jiang.com/programming/matlab/chebfun-matlab-toolbox-numerical-computation/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Three Matlab Software Tools for Speech Analysis</title>
		<link>http://wei-jiang.com/programming/matlab/a-matlab-software-tool-for-speech-analysis-colea</link>
		<comments>http://wei-jiang.com/programming/matlab/a-matlab-software-tool-for-speech-analysis-colea#comments</comments>
		<pubDate>Mon, 08 Feb 2010 00:01:49 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>
		<category><![CDATA[Speech Processing]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/programming/matlab/a-matlab-software-tool-for-speech-analysis-colea</guid>
		<description><![CDATA[COLEA: A software tool for speech analysis PESQ and other objective measures for evaluating quality of speech processed by noise suppression algorithms [composite.zip] &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Relevant references: Quality Assessment:&#160;&#160; Hu, Y. and Loizou, P. (2008). “Evaluation of objective quality measures for speech enhancement,” IEEE Transactions on Speech and Audio Processing, 16(1), 229-238. Intelligibility Assessment:&#160; Ma, J., [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<item>
		<title>Howto Animate Graphs in Matlab</title>
		<link>http://wei-jiang.com/programming/matlab/howto-animate-graphs-in-matlab</link>
		<comments>http://wei-jiang.com/programming/matlab/howto-animate-graphs-in-matlab#comments</comments>
		<pubDate>Mon, 01 Feb 2010 14:42:33 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>
		<category><![CDATA[gif]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/programming/matlab/howto-animate-graphs-in-matlab</guid>
		<description><![CDATA[A Simple Example 1234567891011121314clear all; close all; clc; f0 = 10; N = 1024; t = linspace&#40;0,10,N&#41;; NFFT = 2^nextpow2&#40;N&#41;; fs = 1/&#40;t&#40;2&#41;-t&#40;1&#41;&#41;; aa = 0.001:0.002:0.5; L = length&#40;aa&#41;; for kk = 1:L &#160; &#160; a = aa&#40;kk&#41;; &#160; &#160; ff = f0 - a*t; &#160; &#160; y = cos&#40;2*pi*ff.*t&#41;; &#160; &#160; periodogram&#40;y,&#91;&#93;,NFFT,fs&#41;; vline&#40;f0&#41;; ylim&#40;&#91;-50,2&#93;&#41; [...]]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Howto Estimate Noise Variance in Matlab</title>
		<link>http://wei-jiang.com/programming/matlab/howto-estimate-noise-and-variance-in-matlab</link>
		<comments>http://wei-jiang.com/programming/matlab/howto-estimate-noise-and-variance-in-matlab#comments</comments>
		<pubDate>Thu, 28 Jan 2010 02:42:30 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/programming/matlab/howto-estimate-noise-and-variance-in-matlab</guid>
		<description><![CDATA[Assuming that the deterministic function y has additive Gaussian noise, evar(y) returns an estimated variance of this noise. A thin-plate smoothing spline model is used to smooth y. It is assumed that the model whose generalized cross-validation score is minimum can provide the variance of the additive noise. A few tests showed that evar works [...]]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Robust Signal Smoothing Method in Matlab (smoothN)</title>
		<link>http://wei-jiang.com/programming/matlab/robust-signal-smoothing-method-in-matlab-smoothn</link>
		<comments>http://wei-jiang.com/programming/matlab/robust-signal-smoothing-method-in-matlab-smoothn#comments</comments>
		<pubDate>Thu, 28 Jan 2010 02:24:44 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/programming/matlab/robust-signal-smoothing-method-in-matlab-smoothn</guid>
		<description><![CDATA[Damien Garcia has produced a 1-D to N-D robust smoothing matlab file to allow fast and robust smoothing of one-dimensional and multidimensional data w/wo missing values. A simple example for signal: y = cos(x/10)+(x/50).^2 + randn(size(x))/10; y([70 75 80]) = [5.5 5 6]; is shown below: In a continuous time domain, this might be like [...]]]></description>
		<wfw:commentRss>http://wei-jiang.com/programming/matlab/robust-signal-smoothing-method-in-matlab-smoothn/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>cloudPlot &#8211; Matlab function to plot the distribution of 2-dimensional data.</title>
		<link>http://wei-jiang.com/programming/matlab/cloudplot-matlab-function-to-plot-the-distribution-of-2-dimensional-data</link>
		<comments>http://wei-jiang.com/programming/matlab/cloudplot-matlab-function-to-plot-the-distribution-of-2-dimensional-data#comments</comments>
		<pubDate>Thu, 28 Jan 2010 01:54:01 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>
		<category><![CDATA[toolbox]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/programming/matlab/cloudplot-matlab-function-to-plot-the-distribution-of-2-dimensional-data</guid>
		<description><![CDATA[cloudPlot will help visualize the distribution of a 2-dimensional dataset. It is especially helpful when looking at extremely large datasets where a redular plot(x,y,&#8217;.') will just fill the plot with a solid color because the measurement points overlap each other. cloudPlot uses the built-in matlab routines to set the axis limits and grid points appropriate [...]]]></description>
		<wfw:commentRss>http://wei-jiang.com/programming/matlab/cloudplot-matlab-function-to-plot-the-distribution-of-2-dimensional-data/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Automated Robust MicroArray Data Analysis in MATLAB (Toolbox)</title>
		<link>http://wei-jiang.com/programming/matlab/automated-robust-microarray-data-analysis-in-matlab-toolbox</link>
		<comments>http://wei-jiang.com/programming/matlab/automated-robust-microarray-data-analysis-in-matlab-toolbox#comments</comments>
		<pubDate>Wed, 27 Jan 2010 18:05:35 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>
		<category><![CDATA[dataset]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[toolbox]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/programming/matlab/automated-robust-microarray-data-analysis-in-matlab-toolbox</guid>
		<description><![CDATA[Microarray technology allows gene expression profiling at a global level by measuring mRNA abundance. ARMADA (Automated Robust MicroArray Data Analysis) is a MATLAB implemented program with a graphical user interface (GUI) which performs all steps of typical microarray data analysis; starting from importing raw data from several image analysis software outputs as well as text [...]]]></description>
		<wfw:commentRss>http://wei-jiang.com/programming/matlab/automated-robust-microarray-data-analysis-in-matlab-toolbox/feed</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>Begin Numerical Computing in Python NOT Matlab</title>
		<link>http://wei-jiang.com/programming/matlab/begin-numerical-computing-in-python-not-matlab</link>
		<comments>http://wei-jiang.com/programming/matlab/begin-numerical-computing-in-python-not-matlab#comments</comments>
		<pubDate>Sun, 10 Jan 2010 01:39:19 +0000</pubDate>
		<dc:creator>Wei Jiang</dc:creator>
				<category><![CDATA[Matlab]]></category>
		<category><![CDATA[Python]]></category>

		<guid isPermaLink="false">http://wei-jiang.com/programming/matlab/begin-numerical-computing-in-python-not-matlab</guid>
		<description><![CDATA[Matlab is a commercial program used extensively in the scientific and business communities.&#160; There are many reasons why it is very popular, including its interactive structure, clean syntax, and ability to interface with fast compiled languages, like C.&#160; It also has many routines for signal and image processing, optimization, and visualization.&#160; Python is a modern [...]]]></description>
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		<slash:comments>0</slash:comments>
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