Introduction to the theory of neural computation
Introduction to the theory of neural computation
A comparative study of the Kohonen self-organizing map and the elastic net
Proceedings of the workshop on Computational learning theory and natural learning systems (vol. 2) : intersections between theory and experiment: intersections between theory and experiment
A type of duality between self-organizing maps and minimal wiring
Neural Computation
Combining Lateral and Elastic Interactions: Topology-Preserving Elastic Nets
Neural Processing Letters
Topology-Preserving Elastic Nets
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Deriving cortical maps and elastic nets from topology-preserving maps
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
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Lateral and elastic interactions are known to build a topology in different systems. We demonstrate how the models with weak lateral interactions can be reduced to the models with corresponding weak elastic interactions. Namely, the batch version of soft topology-preserving map can be rigorously reduced to the elastic net. Owing to the latter, both models produce similar behaviour when applied to the TSP. Unlike, the incremental (online) version of soft topology-preserving map is reduced to the cortical map only in the limit of low temperature, which makes their behaviours different when applied to the ocular dominance formation.