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Chaotic neural network with time delay term for sequential patterns. (English) Zbl 1157.68418
Gammerman, A. (ed.), Artificial intelligence and applications. Machine learning. As part of the 26th IASTED international multi-conference on applied informatics. Calgary: International Association of Science and Technology for Development (IASTED); Anaheim, CA: Acta Press (ISBN 978-0-88986-710-9/CD-ROM). 370-375 (2008).
Summary: In this paper, we propose a chaotic neural network with time delay term for sequential patterns (CNNTDSP). The proposed model is based on the conventional chaotic neural network and has two types of connection weights; (1) normal weights for hetero associations and (2) weights with time delay for auto associations. The proposed model deal with the sequential patterns. In the proposed model, associations of the sequential pattern in short term and dynamic associations between sequential patterns in long term are realized. We carried out a series of computer experiments and confirmed the effectiveness of the proposed model.
For the entire collection see [Zbl 1154.68012].
MSC:
68T05 Learning and adaptive systems in artificial intelligence
68T10 Pattern recognition, speech recognition
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