Efficient Vector Quantization Using the WTA-Rule with Activity Equalization
Neural Processing Letters
A Multi-purpose Visual Classification System
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
Model-based Clustering with Soft Balancing
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Combining spatial and colour information for content based image retrieval
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
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The focus of this paper is a convergence study of the frequency sensitive competitive learning (FSCL) algorithm. We approximate the final phase of FSCL learning by a diffusion process described by the Fokker-Plank equation. Sufficient and necessary conditions are presented for the convergence of the diffusion process to a local equilibrium. The analysis parallels that by Ritter-Schulten (1988) for Kohonen's self-organizing map. We show that the convergence conditions involve only the learning rate and that they are the same as the conditions for weak convergence described previously. Our analysis thus broadens the class of algorithms that have been shown to have these types of convergence characteristics