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Neural Networks

This is Anthony Robins's Neural Networks page (part of the AI Group).

Below you will find general information about neural networks, descriptions of neural network related research and teaching at Otago, or the paper COSC460 Neural Networks.




NEURAL NETS INFORMATION

Despite its slow "hardware" the brain is a much more powerful and sophisticated computational system than any computer ever built. What can the brain teach us about computation and how to perform complex tasks such as natural language processing, vision, and control and optimisation problems? Neural networks are a family of methods that try to address these issues and explore "brain-like" computation, information processing and learning.

An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurons. This is true of ANNs as well.
Its Applications are follows


Voice Recognition - Transcribing spoken words into ASCII text.

Target Recognition - Military application which uses video and/or infrared image data to determine if an enemy target is present.

Medical Diagnosis - Assisting doctors with their diagnosis by analyzing the reported symptoms and/or image data such as MRIs or X-rays.

Process Modeling and Control - Creating a neural network model for a physical plant then using that model to determine the best control settings for the plant

Credit Rating - Automatically assigning a company's or individuals credit rating based on their financial condition.

Targeted Marketing - Finding the set of demographics, which have the highest response rate for a particular marketing campaign.

Financial forecasting - Using the historical data of a security to predict the future movement of that security.