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MATLAB data files for the manuscript "In situ training of feedforward and recurrent convolutional memristor networks" published on Nature Machine Intelligence, 2019. The MATLAB data file "exp_mnist.mat" consists of all experimental data on implementing the convolutional neural network with the 1-transistor 1-memristor array that is used for plotting the Figure 1 and 2 of the manuscript. The MATLAB data file "exp_mnistsequence.mat" consists of all experimental data on implementing the convolutional long short-term memory network on the 1-transistor 1-memristor array that is used for plotting the Figure 3 and 4 of the manuscript. The code that generated these data files are provided by the link within the manuscript. Alternatively, the code can be accessed via https://github.com/zhongruiwang/memristorCNN.
{"references": ["Wang, Zhongrui et al. (2019) In situ training of feed-forward and recurrent convolutional memristor networks, Nat. Mach. Intell."]}
resistive switch, processing in memory, in-memory computing, resistive switching, memristor, RRAM, artificial neural network
resistive switch, processing in memory, in-memory computing, resistive switching, memristor, RRAM, artificial neural network
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