Competitive learning algorithms for vector quantization
Neural Networks
BYY harmony learning, structural RPCL, and topological self-organizing on mixture models
Neural Networks - New developments in self-organizing maps
IEEE Transactions on Knowledge and Data Engineering
A fast fixed-point BYY harmony learning algorithm on Gaussian mixture with automated model selection
Pattern Recognition Letters
Efficient Training of RBF Networks Via the BYY Automated Model Selection Learning Algorithms
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
The Competitive EM Algorithm for Gaussian Mixtures with BYY Harmony Criterion
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Automatic Straight Line Detection through Fixed-Point BYY Harmony Learning
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
BYY Harmony Learning on Weibull Mixture with Automated Model Selection
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
A BYY Split-and-Merge EM Algorithm for Gaussian Mixture Learning
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
A Gradient BYY Harmony Learning Algorithm for Straight Line Detection
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Detecting the fuzzy clusters of complex networks
Pattern Recognition
An adaptive gradient BYY learning rule for poisson mixture with automated model selection
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Simultaneous model selection and feature selection via BYY harmony learning
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
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In tackling the learning problem on a set of finite samples, Bayesian Ying-Yang (BYY) harmony learning has developed a new learning mechanism that makes model selection implemented either automatically during parameter learning or in help of evaluating a new class of model selection criteria. In this paper, parameter learning with automated model selection has been studied for finite mixture model via an adaptive gradient learning algorithm for BYY harmony learning on a specific bidirectional architecture (BI-architecture). Via theoretical analysis, it has shown that the adaptive gradient learning implements a mechanism of floating rival penalized competitive learning (RPCL) among the components in the mixture. Also, the simulation results are demonstrated well for the adaptive gradient algorithm on the sample data sets from Gaussian mixtures with certain degree of overlap. Moreover, the adaptive gradient algorithm is applied to classification of the Iris data and unsupervised color image segmentation.