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dc.contributor.authorRisinger, Lonen_US
dc.contributor.authorKaikhah, Khosrowen_US
dc.date.accessioned2012-02-24T10:17:51Z
dc.date.available2012-02-24T10:17:51Z
dc.date.issued2004-05-11en_US
dc.identifier.citationRisinger, L. & Kaikhah, K. (2004). Modified bifurcating neuron with leaky-integrate-and-fire model. "Proceedings of the 17th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems," pp. 1033-1042.
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/3814
dc.description.abstractThe Modified Bifurcating Neuron (MBN) is a neuron model that is capable of amplitude-to-phase conversion and volume-holographic memory. Inputs are real valued and temporally spaced. This allows information to be coded in the temporal spacing of inputs and outputs as well as their values. At its core, the MBN incorporates a stateful leaky-integrate-and-fire neuron model. The MBN attempts to produce these properties by simulating mechanisms present in biological neural systems to a greater extent than is normally found in artificial neural networks. MBNs use an object model rather than the normal linear algebra approach. The MBN is conceptually based on the computational model presented in the "Bifurcating Neuron Network 2" by G. Lee and N. Farhat.en_US
dc.formatText
dc.format.extent10 pages
dc.format.medium1 file (.pdf)
dc.language.isoen_US
dc.sourceProceedings of the Seventeenth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 2004, Ottawa, Canada
dc.subjectBifurcatingen_US
dc.subjectNeuronen_US
dc.subjectLeaky-integrate-and-fire modelen_US
dc.subjectMBNen_US
dc.subjectNeural networksen_US
dc.titleModified Bifurcating Neuron with Leaky-Integrate-and-Fire Modelen_US
txstate.documenttypeArticle
txstate.departmentComputer Science


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