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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Analysis on Wang’s kWTA with Stochastic Output Nodes
verfasst von : John Pui-Fai Sum, Chi-Sing Leung, Kevin Ho
Erschienen in: Neural Information Processing
Verlag: Springer Berlin Heidelberg
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Recently, a Dual Neural Network-based
k
WTA has been proposed, in which the output nodes are defined as a Heaviside step activation function. In this paper, we extend this model by considering that the output nodes are stochastic. Precisely, we define this stochastic behavior by the logistic function. It is shown that the DNN-based
k
WTA with stochastic output nodes is able to converge and the convergence rates of this network are three folds. Finally, the energy function governing the dynamical behavior of the network is unveiled.