Grossberg network
Grossberg network is an artificial neural network introduced by Stephen Grossberg. It is a self organizing, competitive network based on continuous time.[1] Grossberg, a neuroscientist and a biomedical engineer, designed this network based on the human visual system.
Shunting model
The shunting model is one of Grossberg's neural network models, based on a Leaky integrator, described by the differential equation
- [math]\displaystyle{ {dn\over dt} \; = \; -An \; + (B - n)E \; - (C + n)I }[/math],
where [math]\displaystyle{ n=n(t) }[/math] represents the activation level of a neuron, [math]\displaystyle{ E=E(t) }[/math] and [math]\displaystyle{ I=I(t) }[/math] represent the excitatory and inhibitory inputs to the neuron, and [math]\displaystyle{ A }[/math], [math]\displaystyle{ B }[/math], and [math]\displaystyle{ C }[/math] are constants representing the leaky decay rate and the maximum and minimum activation levels.
At equilibrium (where [math]\displaystyle{ dn/dt=0 }[/math]), the activation [math]\displaystyle{ n }[/math] reaches the value
- [math]\displaystyle{ n \; = \; {BE-CI\over A+E+I} }[/math].
References
- ↑ Martin T. Hagan; Howard B. Demuth; Mark H. Beale (January 2002) [1996]. "Chapter 15: Grossberg Network". Neural Network Design (1st ed.). PWS Publishing Co.. pp. 15–1. ISBN 978-0971732100.
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