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	<title>Recursion (disambiguation) - Revision history</title>
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	<updated>2026-04-20T11:06:54Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
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		<title>71.212.15.27: /* See also */</title>
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		<updated>2014-01-04T18:22:28Z</updated>

		<summary type="html">&lt;p&gt;&lt;span class=&quot;autocomment&quot;&gt;See also&lt;/span&gt;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&amp;#039;&amp;#039;&amp;#039;Grossberg network&amp;#039;&amp;#039;&amp;#039; is a [[neural network]] introduced by [[Stephen Grossberg]]. It is a [[self organizing]], competitive network based on continuous time.&amp;lt;ref name=&amp;quot;Hagan&amp;quot;&amp;gt;{{cite book |author=Martin T. Hagan |coauthors=Howard B. Demuth, Mark H. Beale |title=Neural Network Design |edition=1st |date=January 2002 |origyear=1996 |publisher=PWS Publishing Co.|isbn=978-0971732100 |page=15-1 |chapter=Chapter 15: Grossberg Network}}&amp;lt;/ref&amp;gt; Grossberg a neuroscientist and a biomedical engineer designed this network based on the [[Human visual system model|human visual system]].&lt;br /&gt;
&lt;br /&gt;
== Shunting model ==&lt;br /&gt;
Shunting model is one of the Grossberg&amp;#039;s neural network model based on [[Leaky integrator]], given by the expression:&lt;br /&gt;
:&amp;lt;math&amp;gt;\epsilon dn(t)/dt = -n(t) + (b^+ - n(t))p^+ - (n(t) + b^-)p^- \, &amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
{{Reflist}}&lt;br /&gt;
&lt;br /&gt;
[[Category:Neural networks]]&lt;/div&gt;</summary>
		<author><name>71.212.15.27</name></author>
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