Adaptive neural network is a powerful tool for prediction of air pollution abatement scenarios. But it is often difficult to avoid overfit during the training of adaptive neural n...
Abstract. Inspired on psycholinguistics and neuroscience, a symbolicconnectionist hybrid system called θ-Pred (Thematic Predictor for natural language) is proposed, designed to re...
In this paper, we study the problem of transmission power control and its effects on the link-scheduling performance when a set of end-to-end flows established in the network are g...
Abstract—In this contribution, the application of fully connected recurrent neural networks (FCRNNs) is investigated in the context of narrowband channel prediction. Three differ...
In this paper, a neural network scheme is presented for modeling VBR MPEG-2 video sources. In particular, three non linear autoregressive models (NAR) are proposed to model the ag...
Anastasios D. Doulamis, Nikolaos D. Doulamis, Stef...