Method for training a neural network

Details Method for training a neural network Method for training a neural network

2005-11-22

2005-11-22

Hirl, Joseph P. (Department: 2129)

Data processing: artificial intelligence

Neural network

Learning task

C706S015000, C706S016000

Reexamination Certificate

active

06968327

ABSTRACT:
A method for training a neural network in order to optimize the structure of the neural network includes identifying and eliminating synapses that have no significant influence on the curve of the risk function. First and second sending neurons are selected that are connected to the same receiving neuron by respective first and second synapses. It is assumed that there is a correlation of response signals from the first and second sending neurons to the same receiving neuron. The first synapse is interrupted and a weight of the second synapse is adapted in its place. The output signals of the changed neural network are compared with the output signals of the unchanged neural network. If the comparison result does not exceed a predetermined level, the first synapse is eliminated, thereby simplifying the structure of the neural network.

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Kishan Mehrotra et al, Elements of Artificial Neural Networks, 1997, MIT Press, 8, 10, 11 and 46.

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