Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/9080
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dc.contributor.authorAzian Azamimi-
dc.contributor.authorUwate, Yoko-
dc.contributor.authorNishio, Yoshifumi-
dc.date.accessioned2010-08-25T02:53:40Z-
dc.date.available2010-08-25T02:53:40Z-
dc.date.issued2010-04-21-
dc.identifier.citationp.1-4en_US
dc.identifier.isbn978-1-4244-7121-8-
dc.identifier.urihttp://ezproxy.unimap.edu.my:2080/search/srchabstract.jsp?tp=&arnumber=5545250&queryText%3DEffect+of+Chaos+Noise%26openedRefinements%3D*%26searchField%3DSearch+All-
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/9080-
dc.descriptionLink to publisher's homepage at http://ieeexplore.ieee.org/en_US
dc.description.abstractIn the area of artificial neural networks, the Back Propagation (BP) learning algorithm has proved to be efficient in many engineering applications especially in pattern recognition, signal processing and system control. Although the BP learning has been a significant research area of neural network, it has also been known as an algorithm with a poor convergence rate. Many attempts have been made on the learning algorithm to improve the performance on convergence speed and learning efficiency. In this study, we propose a new modified BP learning algorithm by adding chaotic noise into weight update process during error propagation. The chaotic noise is generated using various chaotic maps such as Logistic map, Skew Tent map and Bernoulli Shift map. By computer simulations, we confirm that our proposed algorithm can give a better convergence rate and can find a good solution in early time compared to the conventional BP learning algorithm. Weight update position, noise amplitude and control parameter of chaos can give a big effect on the learning ability of feed forward neural network.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Elctronics Engineering (IEEE)en_US
dc.relation.ispartofseriesProceedings of the 6th International Colloqium on Signal Processing & Its Applications (CSPA) 2010en_US
dc.subjectChaos noiseen_US
dc.subjectBack propagationen_US
dc.subjectNeural networksen_US
dc.subjectLearning algorithmen_US
dc.subjectInternational Colloquium on Signal Processing & Its Applications (CSPA)en_US
dc.titleEffect of chaos noise on the learning ability of back propagation algorithm in feed forward neural networken_US
dc.typeWorking Paperen_US
Appears in Collections:Conference Papers



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