EVENT-BASED INFERENCE AND LEARNING FOR STOCHASTIC SPIKING BAYESIAN NETWORKS

A method of performing event-based Bayesian inference and learning includes receiving input events at each node. The method also includes applying bias weights and/or connection weights to the input events to obtain intermediate values. The method further includes determining a node state based on t...

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Bibliographic Details
Main Authors WANG XIN, BEHABADI BARDIA FALLAH, KHOSROWSHAHI AMIR
Format Patent
LanguageEnglish
Published 27.08.2015
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:A method of performing event-based Bayesian inference and learning includes receiving input events at each node. The method also includes applying bias weights and/or connection weights to the input events to obtain intermediate values. The method further includes determining a node state based on the intermediate values. Further still, the method includes computing an output event rate representing a posterior probability based on the node state to generate output events according to a stochastic point process.
Bibliography:Application Number: US201414281220