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<html><head> <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1"> <title>gencircledata.m</title><link rel="stylesheet" type="text/css" href="../../m-syntax.css"></head><body><code><span class=defun_kw>function</span> <span class=defun_out>[X,gnd_X] </span>= <span class=defun_name>gencircledata</span>(<span class=defun_in>Center,R,num_data,dev</span>)
<br><span class=h1>% GENCIRCLEDATA Generates data on circle corrupted by Gaussian noise.
</span><br><span class=help>%
</span><br><span class=help>% <span class=help_field>Synopsis:</span></span><br><span class=help>% [X,gnd_X] = gencircledata(Center,R,num_data,dev)
</span><br><span class=help>%
</span><br><span class=help>% <span class=help_field>Description:</span></span><br><span class=help>% The underlying curve is 2D circle given by Center and radius R.
</span><br><span class=help>% This function randomly samples points on the circle and it adds
</span><br><span class=help>% Gaussian noise with given standard deviation dev.
</span><br><span class=help>%
</span><br><span class=help>% <span class=help_field>Input:</span></span><br><span class=help>% Center [2x1] Circle center.
</span><br><span class=help>% R [1x1] Circle radius.
</span><br><span class=help>% num_data [1x1] Number of samples.
</span><br><span class=help>% dev [1x1] Standard deviation of added Gaussian noise (default 1).
</span><br><span class=help>%
</span><br><span class=help>% <span class=help_field>Output:</span></span><br><span class=help>% X [2xnum_data] Generated samples.
</span><br><span class=help>% gnd_X [2xnum_data] Ground truth - samples without noise.
</span><br><span class=help>%
</span><br><span class=help>% <span class=help_field>Example:</span></span><br><span class=help>% [X,gnd_X] = gencircledata([1;1],5,500,1);
</span><br><span class=help>% figure;
</span><br><span class=help>% ppatterns(X); ppatterns(gnd_X,'r+');
</span><br><span class=help>%
</span><br><hr><br><span class=help1>% <span class=help1_field>About:</span> Statistical Pattern Recognition Toolbox
</span><br><span class=help1>% (C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac
</span><br><span class=help1>% <a href="http://www.cvut.cz">Czech Technical University Prague</a>
</span><br><span class=help1>% <a href="http://www.feld.cvut.cz">Faculty of Electrical Engineering</a>
</span><br><span class=help1>% <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a>
</span><br><br><span class=help1>% <span class=help1_field>Modifications:</span>
</span><br><span class=help1>% 4-may-2004, VF
</span><br><br><hr><span class=keyword>if</span> <span class=stack>nargin</span> < 4, dev = 1; <span class=keyword>end</span>
<br>
<br>phi = 2*pi*rand(1,num_data);
<br>gnd_X = repmat(Center,1,num_data)+R*[cos(phi);sin(phi)];
<br>gnd_y = ones(1,num_data);
<br>
<br><span class=comment>% add noise
</span><br>X = gnd_X + randn(2,num_data)*dev;
<br>
<br><span class=jump>return</span>;
<br><span class=comment>% EOF
</span><br></code>⌨️ 快捷键说明
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