We propose a network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, biol...
Abstract. This article underlines the learning and discrimination capabilities of a model of associative memory based on artificial networks of spiking neurons. Inspired from neuro...
Abstract. We previously proposed a neural segmentation model suitable for implementation with complementary metal-oxide-semiconductor (CMOS) circuits. The model consists of neural ...
Gessyca Maria Tovar, Tetsuya Asai, Yoshihito Amemi...
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...
– We have developed and tested a novel artificial neural network for the processing of temporal signals. The working of the units (TempUnit) is based on the mechanism of temporal...