A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a pos...
—The stationarity hypothesis is largely and implicitly assumed when designing classifiers (especially those for industrial applications) but it does not generally hold in practic...
—In this paper, we proposed a reduced polynomial neural swarm net (RPNSN) for the task of classification. Classification task is one of the most studied tasks of data mining. In ...
Analog neural signals must be converted into spike trains for transmission over electrically leaky axons. This spike encoding and subsequent decoding leads to distortion. We quant...
While synaptic learning mechanisms have always been a core topic of neural computation research, there has been relatively little work on intrinsic learning processes, which change...