<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision: 1.6.2.2 $  $Date: 2004/02/06 00:25:33 $ -->
<demos>
   <name>Neural Network</name>
   <type>toolbox</type>
   <icon>$toolbox/matlab/icons/matlabicon.gif</icon>
   <description><![CDATA[
<p>The Neural Network Toolbox includes many kinds of powerful networks
for solving problems including:</p>

<ul>
   <li> function approximation, modeling,</li>
   <li> signal processing and prediction</li>
   <li> classification, and clustering.</li>
</ul>

<p>These tools are an essential part of many applications, including
engineering, finance, medicine, and artificial intelligence.</p>
]]></description>

   <demosection>
      <label>Neurons</label>
      <demoitem>
         <label>Simple neuron and transfer functions</label>
         <callback>nnd2n1</callback>
      </demoitem>
      <demoitem>
         <label>Neuron with vector input</label>
         <callback>nnd2n2</callback>
      </demoitem>
   </demosection>

   <demosection>
      <label>Perceptrons</label>
      <demoitem>
         <label>Decision Boundaries</label>
         <callback>nnd4db</callback>
      </demoitem>
      <demoitem>
         <label>Perceptron learning rule</label>
         <callback>nnd4pr</callback>
      </demoitem>
      <demoitem>
         <label>Classification with a 2-input perceptron</label>
         <file>html/demop1.html</file>
         <callback>playshow demop1</callback>
      </demoitem>
      <demoitem>
         <label>Outlier input vectors</label>
         <file>html/demop4.html</file>
         <callback>playshow demop4</callback>
      </demoitem>
      <demoitem>
         <label>Normalized perceptron rule</label>
         <file>html/demop5.html</file>
         <callback>playshow demop5</callback>
      </demoitem>
      <demoitem>
         <label>Linearly non-separable vectors</label>
         <file>html/demop6.html</file>
         <callback>playshow demop6</callback>
      </demoitem>
   </demosection>

   <demosection>
      <label>Linear Networks</label>
      <demoitem>
         <label>Pattern association showing error surface</label>
         <file>html/demolin1.html</file>
         <callback>playshow demolin1</callback>
      </demoitem>
      <demoitem>
         <label>Training a linear neuron</label>
         <file>html/demolin2.html</file>
         <callback>playshow demolin2</callback>
      </demoitem>
      <demoitem>
         <label>Linear classification system</label>
         <callback>nnd10lc</callback>
      </demoitem>
      <demoitem>
         <label>Adaptive noise cancellation</label>
         <file>html/demolin8.html</file>
         <callback>playshow demolin8</callback>
      </demoitem>
      <demoitem>
         <label>Adaptive noise cancellation in airplane</label>
         <callback>nnd10nc</callback>
      </demoitem>
      <demoitem>
         <label>Linear fit of nonlinear problem</label>
         <file>html/demolin4.html</file>
         <callback>playshow demolin4</callback>
      </demoitem>
      <demoitem>
         <label>Underdetermined problem</label>
         <file>html/demolin5.html</file>
         <callback>playshow demolin5</callback>
      </demoitem>
      <demoitem>
         <label>Linearly dependent problem</label>
         <file>html/demolin6.html</file>
         <callback>playshow demolin6</callback>
      </demoitem>
      <demoitem>
         <label>Too large a learning rate</label>
         <file>html/demolin7.html</file>
         <callback>playshow demolin7</callback>
      </demoitem>
   </demosection>

   <demosection>
      <label>Backpropagation</label>
      <demoitem>
         <label>Generalization</label>
         <callback>nnd11gn</callback>
      </demoitem>
      <demoitem>
         <label>Steepest descent backpropagation</label>
         <callback>nnd12sd1</callback>
      </demoitem>
      <demoitem>
         <label>Momentum backpropagation</label>
         <callback>nnd12mo</callback>
      </demoitem>
      <demoitem>
         <label>Variable learning rate backpropagation</label>
         <callback>nnd12vl</callback>
      </demoitem>
      <demoitem>
         <label>Conjugate gradient backpropagation</label>
         <callback>nnd12cg</callback>
      </demoitem>
      <demoitem>
         <label>Marquardt backpropagation</label>
         <callback>nnd12m</callback>
      </demoitem>
   </demosection>

   <demosection>
      <label>Radial Basis Networks</label>
      <demoitem>
         <label>Radial basis approximation</label>
         <file>html/demorb1.html</file>
         <callback>playshow demorb1</callback>
      </demoitem>
      <demoitem>
         <label>Radial basis underlapping neurons</label>
         <file>html/demorb3.html</file>
         <callback>playshow demorb3</callback>
      </demoitem>
      <demoitem>
         <label>Radial basis overlapping neurons</label>
         <file>html/demorb4.html</file>
         <callback>playshow demorb4</callback>
      </demoitem>
      <demoitem>
         <label>GRNN function approximation</label>
         <file>html/demogrn1.html</file>
         <callback>playshow demogrn1</callback>
      </demoitem>
      <demoitem>
         <label>PNN classification</label>
         <file>html/demopnn1.html</file>
         <callback>playshow demopnn1</callback>
      </demoitem>
   </demosection>

   <demosection>
      <label>Self-organizing Networks</label>
      <demoitem>
         <label>Competitive learning</label>
         <file>html/democ1.html</file>
         <callback>playshow democ1</callback>
      </demoitem>
      <demoitem>
         <label>One-dimensional self-organizing map</label>
         <file>html/demosm1.html</file>
         <callback>playshow demosm1</callback>
      </demoitem>
      <demoitem>
         <label>Two-dimensional self-organizing map</label>
         <file>html/demosm2.html</file>
         <callback>playshow demosm2</callback>
      </demoitem>
   </demosection>

   <demosection>
      <label>LVQ Networks</label>
      <demoitem>
         <label>Learning vector quantization</label>
         <file>html/demolvq1.html</file>
         <callback>playshow demolvq1</callback>
      </demoitem>
   </demosection>

   <demosection>
      <label>Hopfield Networks</label>
      <demoitem>
         <label>Hopfield two neuron design</label>
         <file>html/demohop1.html</file>
         <callback>playshow demohop1</callback>
      </demoitem>
      <demoitem>
         <label>Hopfield unstable equilibria</label>
         <file>html/demohop2.html</file>
         <callback>playshow demohop2</callback>
      </demoitem>
      <demoitem>
         <label>Hopfield three neuron design</label>
         <file>html/demohop3.html</file>
         <callback>playshow demohop3</callback>
      </demoitem>
      <demoitem>
         <label>Hopfield spurious stable points</label>
         <file>html/demohop4.html</file>
         <callback>playshow demohop4</callback>
      </demoitem>
   </demosection>

   <demosection>
      <label>Application Examples</label>
      <demoitem>
         <label>Linear design (command-line)</label>
         <callback>applin1</callback>
      </demoitem>
      <demoitem>
         <label>Adaptive linear prediction (command-line)</label>
         <callback>applin2</callback>
      </demoitem>
      <demoitem>
         <label>Elman amplitude detection (command-line)</label>
         <callback>appelm1</callback>
      </demoitem>
      <demoitem>
         <label>Character recognition (command-line)</label>
         <callback>appcr1</callback>
      </demoitem>
   </demosection>

   <demosection>
      <label>Control Systems</label>
      <demoitem>
         <label>Predictive control of a tank reactor (sim)</label>
         <callback>predcstr</callback>
         <dependency>Simulink</dependency>
      </demoitem>
      <demoitem>
         <label>NARMA-L2 control of a magnet levitation system (sim)</label>
         <callback>narmamaglev</callback>
         <dependency>Simulink</dependency>
      </demoitem>
      <demoitem>
         <label>Reference control of a robot arm (sim)</label>
         <callback>mrefrobotarm</callback>
         <dependency>Simulink</dependency>
      </demoitem>
   </demosection>

   <demosection>
      <label>Other Demos</label>
      <demoitem>
         <label>Other Neural Network Design textbook demos</label>
         <callback>nnd</callback>
      </demoitem>
   </demosection>

</demos>



