Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
A Hybrid modeling approach, combining an analytical model with a radial basis function neural network is introduced in this paper. The modeling procedure is combined with genetic a...
Primoz Potocnik, Igor Grabec, Marko Setinc, Janez ...
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...