Learning automata: an introduction
Learning automata: an introduction
Networks of spiking neurons: the third generation of neural network models
Transactions of the Society for Computer Simulation International - Special issue: simulation methodology in transportation systems
Pulsed neural networks
Computing with spiking neurons
Pulsed neural networks
Self-Organizing Maps
Self-organization of spiking neurons using action potential timing
IEEE Transactions on Neural Networks
International Journal of Systems Science
Hi-index | 0.01 |
In this paper, a new delay shift approach for learning in an RBF-like neural network structure of spiking neurons is introduced. The synaptic connections between the input and the RBF neurons are single delayed connections and the delays are adapted during an unsupervised learning process. Each synaptic connection in this network is modeled by a learning automaton. The action of the automaton associated with each connection is considered as the delay of the corresponding synaptic connection. It is shown through simulations that the clustering precision of the proposed network is considerably higher than that of the existing similar neural networks.