STDP Based Online Learning for a Current-Controlled Memristive Synapse
Author:
Affiliation:
1. University of Tennessee, Knoxville,Department of Electrical Engineering and Computer Science,Knoxville,Tennessee,USA,37996
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9859262/9859267/09859294.pdf?arnumber=9859294
Reference11 articles.
1. Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type
2. Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs
3. Energy-Efficient Neuron, Synapse and STDP Integrated Circuits
4. Memristor-The missing circuit element
5. Circuit Techniques for Online Learning of Memristive Synapses in CMOS-Memristor Neuromorphic Systems
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2. HfO2-Based Synaptic Spiking Neural Network Evaluation to Optimize Design and Testing Cost;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19
3. Enhanced read resolution in reconfigurable memristive synapses for Spiking Neural Networks;Scientific Reports;2024-04-17
4. An Efficient and Accurate Memristive Memory for Array-Based Spiking Neural Networks;IEEE Transactions on Circuits and Systems I: Regular Papers;2023-12
5. Optimizations for a Current-Controlled Memristor- Based Neuromorphic Synapse Design;IEEE Journal on Emerging and Selected Topics in Circuits and Systems;2023-12
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