Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Parallel Models of Associative Memory
Parallel Models of Associative Memory
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pairwise Data Clustering by Deterministic Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
A linear assignment clustering algorithm based on the least similar cluster representatives
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Robust clustering methods: a unified view
IEEE Transactions on Fuzzy Systems
An integrated approach to fuzzy learning vector quantization and fuzzy c-means clustering
IEEE Transactions on Fuzzy Systems
A new neural network for cluster-detection-and-labeling
IEEE Transactions on Neural Networks
Dynamics of selective recall in an associative memory model with one-to-many associations
IEEE Transactions on Neural Networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
ICICS'07 Proceedings of the 9th international conference on Information and communications security
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A novel neural network, named Associative Clustering Neural Network (ACNN), is developed for clustering data whose underlying distribution shapes are arbitrary. ACNN is a dynamic model that collectively measures and updates the similarity of any two patterns through the interaction of a group of patterns. Such a new measure of similarity helps to achieve more robust clustering performance than using the existing measures that are staticly and individually based on the distances among the isolated pairwise data. The efficience of ACNN has been verified through the performance study.