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UMBC High Performance Computing Facility
Please note that this page is under construction. We are documenting the 240-node cluster maya that will be available after Summer 2014. Currently, the 84-node cluster tara still operates independently, until it becomes part of maya at the end of Summer 2014. Please see the 2013 Resources Pages under the Resources tab for tara information.
Testing a computational model of biological neural networks
James T. Lo, Department of Mathematics and Statistics, UMBC
Bryce Carey, Department of Mathematics and Statistics, UMBC

A computational model of neural networks was proposed that is a recurrent network of processing units each comprising new models of dendritic trees, synapses, spiking/nonspiking somas, unsupervised/supervised learning mechanisms, and a maximal generalization scheme. The model shows how neural networks encode, learn, memorize, recall and generalize.

In the project, we will test these capabilities and evaluate the model as a learning machine for pattern clustering, detection, recognition and localization on large benchmark data sets. Comparison with prior learning machines will be performed.