Learning Rule for a Quantum Neural Network Inspired by Hebbian Learning

Modular neural networks with Hebbian learning rule

The paper consists of two parts, each of them describing a learning neural network with the same modular architecture and with a similar set of functioning algorithms. Both networks are artificially partitioned into several equal modules according to the number of classes that the network has to recognize. Hebbian learning rule is used for network training. In the first network, learning proces...

HebbNets: Dynamic network with Hebbian learning rule

It has been demonstrated that one of the most striking features of the nervous system, the so called ’plasticity’ (i.e high adaptability at different structural levels) is primarily based on Hebbian learning which is a collection of slightly different mechanisms that modify the synaptic connections between neurons. The changes depend on neural activity and assign a special dynamic behavior to t...

Sensorimotor Sequential Learning by a Neural Network Based on Redefined Hebbian Learning

A two-jointed arm is used to discuss the conditions under which a neural controller can acquire a precise internal model of a plant to be controlled without the help of an external superviser. The problem can be solved by a 'modified Hebbian rule' ensuring convergence of the synaptic strengths, a feedforward network called 'power network', and a learning algorithm called 'auto-imitation'. The m...

A learning rule with generalized Hebbian synapses

We study the convergence behavior of a learning model with generalized Hebbian synapses.  2002 Elsevier Science (USA). All rights reserved.

A multistage on-line learning rule for multilayer neural network