Learning to recognize or predict sequences using long-term context has many applications. However, practical and theoretical problems are found in training recurrent neural networ...
Abstract. This paper is concerned with arti cial evolution of neurocontrollers with adaptive synapses for autonomous mobile robots. The method consists of encoding on the genotype ...
A particularly difficult task in molecular imaging is the analysis of fluorescence microscopy images of neural tissue, as they usually exhibit a high density of objects with diffu...
Julia Herold, Manuela Friedenberger, Marcus Bode, ...
In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...