Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
We present an application of arti cial neural networks to machine condition monitoring. Since several signal preprocessing methods produce high dimensional feature vectors there i...
Abstract - In this paper we develop and analyze Spiking Neural Network (SNN) versions of Resilient Propagation (RProp) and QuickProp, both training methods used to speed up trainin...
Abstract. The aim of our research was to apply well-known data mining techniques (such as linear neural networks, multi-layered perceptrons, probabilistic neural networks, classifi...
Marcin Paprzycki, Ajith Abraham, Ruiyuan Guo, Srin...
The implementation of larger digital neural networks has not been possible due to the real-estate requirements of single neurons. We present an expandable digital architecture whic...
Valentina Salapura, Michael Gschwind, Oliver Maisc...