TEACHING ARTIFICIAL
NEURAL NETWORKS

Noel McGilvray

Wynnum North State High School. 1995

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ABSTRACT

This session will look at the theory behind how Artificial Neural Networks work using the Back-Error Propagation model as an example. Key concepts such as layers, neurons, weights and transfer functions will be explained in simple terms and sample student exercises will be worked through.

After the theory of ANNís has been covered, a computer simulation of a rocket guided by a neural network to track down a jet fighter will be demonstrated, leading to a discussion of possible student projects in this interesting area of Artificial Intelligence.

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