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Bipolar Analog Memristors as Artificial Synapses for Neuromorphic Computing
- Source :
- Materials, Vol 11, Iss 11, p 2102 (2018)
- Publication Year :
- 2018
- Publisher :
- MDPI AG, 2018.
-
Abstract
- Synaptic devices with bipolar analog resistive switching behavior are the building blocks for memristor-based neuromorphic computing. In this work, a fully complementary metal-oxide semiconductor (CMOS)-compatible, forming-free, and non-filamentary memristive device (Pd/Al2O3/TaOx/Ta) with bipolar analog switching behavior is reported as an artificial synapse for neuromorphic computing. Synaptic functions, including long-term potentiation/depression, paired-pulse facilitation (PPF), and spike-timing-dependent plasticity (STDP), are implemented based on this device; the switching energy is around 50 pJ per spike. Furthermore, for applications in artificial neural networks (ANN), determined target conductance states with little deviation (
Details
- Language :
- English
- ISSN :
- 19961944
- Volume :
- 11
- Issue :
- 11
- Database :
- Directory of Open Access Journals
- Journal :
- Materials
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.1d894dbfa6f4dc1a07c97a4e651fccd
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/ma11112102