An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to...
Paris A. Mastorocostas, Dimitris N. Varsamis, Cons...
The first successful FPGA implementation [1] of artificial neural networks (ANNs) was published a little over a decade ago. It is timely to review the progress that has been made i...
In this paper, we consider the problem of implementation of neural network in the context of the level 2 trigger of HESS2 project. We propose a hardware architecture which which ta...
In this paper a novel procedure to select the input nodes in neural network modeling is presented and discussed. The approach is developed in a multiple testing framework and so it...
We present a computational model of amygdala neural networks. It is used to simulate neuronal activation in amygdala nuclei at different stages of aversive conditioning experiments...