Practical Hardware Implementation of Self-configuring Neural Networks
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
GUEST EDITORIAL: Computational intelligence in solving bioinformatics problems
Artificial Intelligence in Medicine
Spiking Neural Network Self-configuration for Temporal Pattern Recognition Analysis
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Recognition of partially occluded and rotated images with a network of spiking neurons
IEEE Transactions on Neural Networks
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Spatio-temporal coding that combines spatial constraints with temporal sequencing is of great interest to brain-like circuit modelers. In this paper we present some new ideas of how these types of circuits can self-organize. We introduce a temporal correlation rule based on the time difference between the firing of neurons. With the aid of this rule we show an analogy between a graph and a network of spiking neurons. The shortest path, clustering based on the nearest neighbor, and the minimal spanning tree algorithms are solved using the proposed approach