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This book is the first of a two-volume set that constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007, held in Porto, Portugal, September 2007. Coverage includes advances in neural network learning methods, advances in neural network architectures, neural dynamics and complex systems, data analysis, evolutionary computing, agents learning, as well as temporal synchronization and nonlinear dynamics in neural networks.
This book explains the minimum error entropy (MEE) concept applied to data classification machines. Discusses theoretical results, offers a clustering algorithm using a MEE-like concept, and includes tests, evaluation experiments and comparative applications.
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