Wisconsin Alumni Research Foundation

Information Technology
Information Technology
Training System For Artificial Neural Networks Having A Global Weight Constrainer
WARF: P180189US01

Inventors: Vikas Singh, Sathya Ravi, Vishnu Sai Rao Suresh Lokhande, Tuan Dinh

The Invention
An architecture for training the weights of artificial neural networks provides a global constrainer modifying the neuron weights in each iteration not only by the back-propagated error but also by a global constraint constraining these weights based on the value of all weights at that iteration. The ability to accommodate a global constraint is made practical by using a constrained gradient descent which approximates the error gradient deduced in the training as a plane, offsetting the increased complexity of the global constraint.
Additional Information
For More Information About the Inventors
For current licensing status, please contact Jeanine Burmania at [javascript protected email address] or 608-960-9846