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Construction of Hierarchical Neural Classifiers by Self-Organizing Error Back-Propagationстатья
- Авторы: Dolenko S.A., Orlov Yu V., Persiantsev I.G., Shugai Ju S.
- Сборник: Proc.Int.ICSC/IFAC Symposium on Neural Computation, Sept 23-25 1998, Vienna, Austria. Ed. M.Heiss
- Год издания: 1998
- Место издания: ICSC Academic Press International Computer Science Conventions Canada/Switzerland
- Первая страница: 113
- Последняя страница: 116
- Аннотация: The paper describes main principles of a novel algorithm for creation of hierarchical neural network classifiers. The algorithm is based on a modification of error backpropagation, combining supervised learning with self-organization. Recursive use of the algorithm results in creation of compact and computationally effective self-organized structures of neural classifiers. The algorithm performance has been tested on model data and on real-world problems.
- Добавил в систему: Доленко Сергей Анатольевич