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Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element

https://doi.org/10.1109/ted.2015.2439635
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9/9 checkable references clean · checked 2026-07-23

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

The 9 checked references that resolve
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Reflections on Cognition and Parallel Distributed Processing
resolves10.1109/5.726791
Gradient-based learning applied to document recognition
resolves10.1109/TED.2012.2227969
Specifications of Nanoscale Devices and Circuits for Neuromorphic Computational Systems
resolves10.1126/science.1127647
Reducing the Dimensionality of Data with Neural Networks
resolves10.1109/IEDM.2014.7047135
Experimental demonstration and tolerancing of a large-scale neural network (165,000 synapses), using phase-change memory as the synaptic weight element
resolves10.1109/LED.2015.2418342
Optimization of Conductance Change in Pr<sub>1–<i>x</i></sub>Ca<sub><i>x</i></sub>MnO<sub>3</sub>-Based Synaptic Devices for Neuromorphic Systems
resolves10.1109/IEDM.2011.6131488
Phase change memory as synapse for ultra-dense neuromorphic systems: Application to complex visual pattern extraction
resolves10.1109/VLSIT.2007.4339743
Novel Lithography-Independent Pore Phase Change Memory
resolves10.1145/2463585.2463588
Nanoscale electronic synapses using phase change devices
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