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Learning by mistakes in memristor networks

Carbajal, Juan Pablo et al · American Physical Society · 2022

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Author / responsible party
Carbajal, Juan Pablo et al
Publisher
American Physical Society
Year
2022
ISSN
1539-3755
ISSN
1539-3755
Language
English

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Recent results revived the interest in the implementation of analog devices able to perform brainlike operations. Here we introduce a training algorithm for a memristor network which is inspired by previous work on biological learning. Robust results are obtained from computer simulations of a network of voltage-controlled memristive devices. Its implementation in hardware is straightforward, being scalable and requiring very little peripheral computation overhead. Fil: Carbajal, Juan Pablo. University of Applied Sciences of Eastern Switzerland; Suiza Fil: Mártin, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias Físicas. - Universidad Nacional de San Martín. Instituto de Ciencias Físicas; Argentina

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APA 7

Carbajal, J. P. E. A. (2022). Learning by mistakes in memristor networks. http://hdl.handle.net/11336/213954

MLA

Carbajal, Juan Pablo et al. "Learning by mistakes in memristor networks." 2022. http://hdl.handle.net/11336/213954.

Chicago

Carbajal, Juan Pablo et al. 2022. "Learning by mistakes in memristor networks.". http://hdl.handle.net/11336/213954.

Harvard

Carbajal, J. P. E. A. 2022, Learning by mistakes in memristor networks, American Physical Society, available at: http://hdl.handle.net/11336/213954 [Accessed 7 Aug. 2026].

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Title
Learning by mistakes in memristor networks
Author / contributors
Carbajal, Juan Pablo et al
Publisher
American Physical Society
Publication year
2022
ISSN
1539-3755
ISSN
1539-3755
Language
English

Subjects

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MEMRISTOR; NETWORKS; NEUROMORPHING; NEURAL NETWORKS; https://purl.org/becyt/ford/1.3; https://purl.org/becyt/ford/1
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