Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Extensions and modifications of the Kohenen-SOM and applications in remote sensing image analysis
Self-Organizing neural networks
Evolving neural networks through augmenting topologies
Evolutionary Computation
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Improving performance of self-organising maps with distance metric learning method
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
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In this paper, we study instances of complex neural networks, i.e. neural networks with complex topologies. We use Self-Organizing Map neural networks whose neighborhood relationships are defined by a complex network, to classify handwritten digits. We show that topology has a small impact on performance and robustness to neuron failures, at least at long learning times. Performance may however be increased (by almost $10\%$) by evolutionary optimization of the network topology. In our experimental conditions, the evolved networks are more random than their parents, but display a more heterogeneous degree distribution.