Chaotic Neural Network for Biometric Pattern Recognition

dc.contributor.authorAhmadian, Kushan
dc.contributor.authorGavrilova, Marina
dc.date.accessioned2018-09-27T11:53:59Z
dc.date.available2018-09-27T11:53:59Z
dc.date.issued2012-08-30
dc.date.updated2018-09-27T11:53:59Z
dc.description.abstractBiometric pattern recognition emerged as one of the predominant research directions in modern security systems. It plays a crucial role in authentication of both real-world and virtual reality entities to allow system to make an informed decision on granting access privileges or providing specialized services. The major issues tackled by the researchers are arising from the ever-growing demands on precision and performance of security systems and at the same time increasing complexity of data and/or behavioral patterns to be recognized. In this paper, we propose to deal with both issues by introducing the new approach to biometric pattern recognition, based on chaotic neural network (CNN). The proposed method allows learning the complex data patterns easily while concentrating on the most important for correct authentication features and employs a unique method to train different classifiers based on each feature set. The aggregation result depicts the final decision over the recognized identity. In order to train accurate set of classifiers, the subspace clustering method has been used to overcome the problem of high dimensionality of the feature space. The experimental results show the superior performance of the proposed method.
dc.description.versionPeer Reviewed
dc.identifier.citationKushan Ahmadian and Marina Gavrilova, “Chaotic Neural Network for Biometric Pattern Recognition,” Advances in Artificial Intelligence, vol. 2012, Article ID 124176, 9 pages, 2012. doi:10.1155/2012/124176
dc.identifier.doihttps://doi.org/10.1155/2012/124176
dc.identifier.urihttp://hdl.handle.net/1880/108376
dc.language.rfc3066en
dc.rights.holderCopyright © 2012 Kushan Ahmadian and Marina Gavrilova. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.titleChaotic Neural Network for Biometric Pattern Recognition
dc.typeJournal Article
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