Most influence networks are depicted as nodes and links operating in the manner of a feed-forward neural network where both nodes and links appear to be homogenous in their nature....
A two-neural network approach to solving nonlinear optimal control problems is described in this study. This approach called the adaptive critic method consists of one neural netw...
One potential strength of recurrent neural networks (RNNs) is their – theoretical – ability to find a connection between cause and consequence in time series in an constraint-...
In this paper, we study a minimum Connected Dominating Set problem (CDS) in wireless networks, which selects a minimum CDS with property that all intermediate nodes inside every pa...
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...