Edge Rewrite
// HTMLRewriter · presentation

This page was redesigned at the edge.

Cloudflare fetched the original article and streamed it through HTMLRewriter to apply an entirely new visual system without rebuilding the source page.

// request.cf · coarse context

A page that knows where it met you.

Only coarse request metadata is shown. This demo does not display or persist visitor IP addresses.

Country
US
Cloudflare location
CMH
Connection
HTTP/2
Language
Not provided

Ray ID: a24db7185a95c6fa

Jump to content

Grossberg network

From Wikipedia, the free encyclopedia

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

[edit]

The shunting model is one of Grossberg's neural network models, based on a Leaky integrator, described by the differential equation

,

where represents the activation level of a neuron, and represent the excitatory and inhibitory inputs to the neuron, and , , and are constants representing the leaky decay rate and the maximum and minimum activation levels.

At equilibrium (where ), the activation reaches the value

.

References

[edit]
  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.