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Nuromorphic devices are powerful information processing systems and realize low power consumption. We proposed cellular neural networks with polycrystalline-silicon (Poly-Si) thin film transistors (TFTs). The neuron element consists of eight TFTs and the synapse element of only one TFT. We actually succeeded in confirming the operation of learning of logics. In this presentation, we succeeded the...
We are developing cellular neural networks using thin-film transistors (TFTs). Although simplification of the circuits for the neurons and synapses is also needed for the cellular neural network, the detailed discussion is not sufficient for the cellular neural network. Particularly in this study, we tried simplification of synapse devices. We used discrete trimmer resistors and capacitors for the...
We are developing cellular neural networks using thin-film transistors (TFTs). Although simplification of the processing elements such as neurons and synapses is also needed for the cellular neural network, it is difficult and time-consuming to fabricate and evaluate actual devices. Therefore, we are studying the simplification of the processing elements in the neural networks by using circuit simulation...
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