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JACIII Vol.2 No.6 pp. 195-202
doi: 10.20965/jaciii.1998.p0195
(1998)

Paper:

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, 1998
Accepted:
August 28, 1998
Published:
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:
Nikola 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.
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