Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Robust Clustering with Applications in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Learning from Data: Concepts, Theory, and Methods
Learning from Data: Concepts, Theory, and Methods
Neural Networks
The LBG-U Method for Vector Quantization – an Improvement over LBGInspired from Neural Networks
Neural Processing Letters
IWANN '99 Proceedings of the International Work-Conference on Artificial and Natural Neural Networks: Foundations and Tools for Neural Modeling
Clustering using a coarse-grained parallel genetic algorithm: a preliminary study
CAMP '95 Proceedings of the Computer Architectures for Machine Perception
Vector quantization of image subbands: a survey
IEEE Transactions on Image Processing
Fuzzy algorithms for learning vector quantization
IEEE Transactions on Neural Networks
Conditional fuzzy clustering in the design of radial basis function neural networks
IEEE Transactions on Neural Networks
Optimal adaptive k-means algorithm with dynamic adjustment of learning rate
IEEE Transactions on Neural Networks
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Unsupervised learning using K-means techniques is successfully employed in several application fields. When the training set and the number of reference vectors increases, the computational effort can become prohibitive for mono-processor computers. This paper illustrates the parallelization of two clustering techniques using the MULTISOFT machine, a commodity supercomputer, built at the University of Messina. The particular management policy of the MULTISOFT machine and the implementation techniques have shown very interesting results: the speedup increases together with the complexity of the problem to be solved.