Improving the Separability of a Reservoir Facilitates Learning Transfer David Norton and Dan Ventura Computer Science Department Brigham Young University [removed], [removed] - Liquid state machine - Document - PDFSEARCH.IO

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	Improving the Separability of a Reservoir Facilitates Learning Transfer David Norton and Dan Ventura Computer Science Department Brigham Young University [removed], [removed] Add to Reading List Document Date: 2008-06-14 21:48:10 Open Document File Size: 693,46 KB Share Result on Facebook Company Neural Information Processing Systems / Artificial Neural Networks / Neural Networks / / / IndustryTerm reservoir computing methods / heterogeneous networks / real-time computing / reservoir computing / learning algorithm / synapse modifying algorithm / / Organization Artificial Copyright Intelligence / Brigham Young University / Association for the Advancement / US Federal Reserve / / Person Goodman / Dan Ventura / David Norton / / Position specific model of reservoir computing / / Technology synapse modifying algorithm / http / machine learning / simulation / neural network / / URL www.lsm.turgraz.at/index.html / www.aaai.org / / SocialTag Biology Cybernetics Computational statistics Cellular neuroscience Neurophysiology Liquid state machine Artificial neural network Neuron Spiking neural network Neural networks

Improving the Separability of a Reservoir Facilitates Learning Transfer David Norton and Dan Ventura Computer Science Department Brigham Young University [removed], [removed]Add to Reading List