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16 Citations

6,205 Views

13 Pages

Memristive Spiking Neural Networks Trained with Unsupervised STDP

Errui Zhou,
Liang Fang and
Binbin Yang

Electronics2018, 7(12), 396;https://doi.org/10.3390/electronics7120396

6 December 2018

Neuromorphic computing systems are promising alternatives in the fields of pattern recognition, image processing, etc. especially when conventional von Neumann architectures face several bottlenecks. Memristors play vital roles in neuromorphic comput...

(This article belongs to the Section Computer Science & Engineering)

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Review

194 Views

67 Pages

Memristive Neural Networks-Assisted Training Algorithms: Current State and Future Challenges

Natasa M. Samardzic,
Vuk Vranjkovic,
Predrag Teodorovic,
Jovana Maricic and ,
Sergey Shchanikov,
Susanna Gordleeva,
Alexey Mikhaylov,
Max Talanov,
Victor Kazantsev and
Victor Erokhin
+ 6 authors+ 1 author

Electronics2026, 15(21), 4892;https://doi.org/10.3390/electronics15214892

22 October 2026

Existing challenges in modern AI architectures, including the von Neumann bottleneck and high energy demand, have led to increased research efforts towards the development of novel computing paradigms based on memristive technologies. This comprehens...

(This article belongs to the Special Issue Memristor Device and Memristive System)

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