DAVE ANDERSON, GEORGE MCNEILL – ARTIFICIAL NEURAL NETWORKS TECHNOLOGY

The purpose of this report is to help the reader understand what Artificial Neural Networks are, how to use them, and where they are currently being used.

The wave of the future in computing is Artificial Neural Networks. They do not require the traditional skills of a programmer. misunderstandings have arisen. Writers think that the neuron-inspired processors can do anything. Potential users who have tried and failed to solve their problems with neural networks have been disappointed. Neural nets are often thought of as complicated and confusing by application builders.

That confusion came from the industry. There are a lot of different neural networks, all with unique claims and specific examples. Some of the neuron-based structures are being used commercially. The feedforward, backpropagation network is the most popular structure. The models for thinking that are still being evolved in the laboratories are represented by most of the other neural network structures. The only real demand that these networks make is that the network architect learns how to use them.

The report is intended to help the process by explaining the structures and rules for tweaking the nuts and bolts.

What types of applications are currently utilizing the different structures and how some structures lend themselves to specific solutions are discussed in this report.

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