Jul 28, 2023 · Our study suggests a promising application of CNN by combining conductances of memristor for classifying stress states.
Jan 23, 2024 · In this study, we propose a memristor-based CNN (M-CNN) model by updating the weights according to the memristor's conductances to improve the ...
Oct 22, 2024 · It is critical to obtain high linear conductance in the memristor to avoid abrupt changes in current. To obtain the high linearity of the ...
To solve these problems, we proposed a memristor-based CNN (M-CNNs) This model's weight update process involves using stochastic gradient descent with momentum ...
Memristor-Based CNNs for Detecting Stress Using Brain Imaging Signals
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2021. Memristor-based CNNs for detecting stress using brain imaging signals. SJ Bak, J Park, J Lee, J Jeong. IEEE Transactions on Emerging Topics in ...
Memristor-Based CNNs for Detecting Stress Using Brain Imaging Signals. IEEE Transactions on Emerging Topics in Computational Intelligence. 2024-02 | Journal ...
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... using fNIRS-based functional connectivity." PLOS ONE 19, no. 5: e0303144. Journal article. Memristor-Based CNNs for Detecting Stress Using Brain Imaging Signals.
Mar 25, 2021 · This paper proposes a configurable full-binary convolutional neural network (CFB-CNN) architecture, whose inputs, weights, and neurons are all binary values.
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Feb 24, 2015 · Such a device can be modeled as a second-order memristor and allow the implementation of critical synaptic functions realistically using simple spike forms.