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The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems
Nikola Kasabov
Department of Information Science, University of Otago P.O Box 56, Dunedin, New Zealand
Received:May 20, 1998Accepted:August 28, 1998Published:December 20, 1998
Keywords:Evolving connectionist systems, On-line adaptive learning, Multi-modal information processing, Adaptive fuzzy neural networks, Person voice identification
Abstract
This paper introduces a paradigm of connectionist architectures and an approach to building on-line, adaptive intelligent systems. This approach is called evolving connectionist systems (ECOS). EGOS evolve through incremental, on-line learning, both supervised and unsupervised. They can accommodate new input data, including new features, new classes, etc. The ECOS framework is presented and illustrated on a particular type of evolving neural networks - evolving fuzzy neural networks. The task of voice recognition and person identification is used as a case study.
Cite this article as:N. Kasabov, “The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems,” J. Adv. Comput. Intell. Intell. Inform., Vol.2 No.6, pp. 195-202, 1998.Data files:
