OutStar Learning Rule | Artificial Neural Networks
Also referred to as Grossberg learning rule, it is a supervised algorithm learning rule, introduced by Grossberg.
In this rule, all neurons are arranged in organized layers. All weights connected to a certain neuron should equal the desired output for all neurons connected by those specific weights. The rule is specially designed to produce the desired output p, for the layer of n neurons.
The Out-Star rule is used in supervised learning when neurons are organized in layers
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OutStar Learning Rule | ANN Learning Rules
Artificial Neural Networks | thetqweb