The Bifurcating Neuron Network 2: an analog associative memory
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| Title: | The Bifurcating Neuron Network 2: an analog associative memory |
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| Authors: | Lee, Geehyuk1, Farhat, Nabil H.1 farhat@ee.upenn.edu |
| Source: | Neural Networks. Jan2002, Vol. 15 Issue 1, p69. 16p. |
| Subjects: | Artificial neural networks, Time code (Audiovisual technology), Electronic modulation, Bifurcation theory |
| Abstract: | The Bifurcating Neuron (BN), a chaotic integrate-and-fire neuron, is a model of a neuron augmented by coherent modulation from its environment. The BN is mathematically equivalent to the sine-circle map, and this equivalence relationship allowed us to apply the mathematics of one-dimensional maps to the design of a BN network. The study of the bifurcating diagram of the BN revealed that the BN, under a suitable condition, can function as an amplitude-to-phase converter. Also, being an integrate-and-fire neuron, it has an inherent capability to function as a coincidence detector. These two observations led us to the design of the BN Network 2 (BNN-2), a pulse-coupled neural network that exhibits associative memory of multiple analog patterns. In addition to the usual dynamical properties as an associative memory, the BNN-2 was shown to exhibit volume-holographic memory: it switches to different pages of its memory space as the frequency of the coherent modulation changes, meaning context-sensitive memory. [Copyright &y& Elsevier] |
| Copyright of Neural Networks is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 7767763 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: The Bifurcating Neuron Network 2: an analog associative memory – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Lee%2C+Geehyuk%22">Lee, Geehyuk</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Farhat%2C+Nabil+H%2E%22">Farhat, Nabil H.</searchLink><relatesTo>1</relatesTo><i> farhat@ee.upenn.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Neural+Networks%22">Neural Networks</searchLink>. Jan2002, Vol. 15 Issue 1, p69. 16p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Time+code+%28Audiovisual+technology%29%22">Time code (Audiovisual technology)</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+modulation%22">Electronic modulation</searchLink><br /><searchLink fieldCode="DE" term="%22Bifurcation+theory%22">Bifurcation theory</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The Bifurcating Neuron (BN), a chaotic integrate-and-fire neuron, is a model of a neuron augmented by coherent modulation from its environment. The BN is mathematically equivalent to the sine-circle map, and this equivalence relationship allowed us to apply the mathematics of one-dimensional maps to the design of a BN network. The study of the bifurcating diagram of the BN revealed that the BN, under a suitable condition, can function as an amplitude-to-phase converter. Also, being an integrate-and-fire neuron, it has an inherent capability to function as a coincidence detector. These two observations led us to the design of the BN Network 2 (BNN-2), a pulse-coupled neural network that exhibits associative memory of multiple analog patterns. In addition to the usual dynamical properties as an associative memory, the BNN-2 was shown to exhibit volume-holographic memory: it switches to different pages of its memory space as the frequency of the coherent modulation changes, meaning context-sensitive memory. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Neural Networks is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/S0893-6080(01)00100-9 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 69 Subjects: – SubjectFull: Artificial neural networks Type: general – SubjectFull: Time code (Audiovisual technology) Type: general – SubjectFull: Electronic modulation Type: general – SubjectFull: Bifurcation theory Type: general Titles: – TitleFull: The Bifurcating Neuron Network 2: an analog associative memory Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lee, Geehyuk – PersonEntity: Name: NameFull: Farhat, Nabil H. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2002 Type: published Y: 2002 Identifiers: – Type: issn-print Value: 08936080 Numbering: – Type: volume Value: 15 – Type: issue Value: 1 Titles: – TitleFull: Neural Networks Type: main |
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