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

d n d t = A n + ( B n ) E ( C + n ) I {\displaystyle {dn \over dt}\;=\;-An\;+(B-n)E\;-(C+n)I} ,

where n = n ( t ) {\displaystyle n=n(t)} represents the activation level of a neuron, E = E ( t ) {\displaystyle E=E(t)} and I = I ( t ) {\displaystyle I=I(t)} represent the excitatory and inhibitory inputs to the neuron, and A {\displaystyle A} , B {\displaystyle B} , and C {\displaystyle C} are constants representing the leaky decay rate and the maximum and minimum activation levels.

At equilibrium (where d n / d t = 0 {\displaystyle dn/dt=0} ), the activation n {\displaystyle n} reaches the value

n = B E C I A + E + I {\displaystyle n\;=\;{BE-CI \over A+E+I}} .

References

  1. ^ 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.