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We have developed a cellular neural network formed by simplified processing elements composed of thin-film transistors. First, we simplified the neuron circuit into a two-inverter two-switch circuit and the synapse device into only a transistor. Next, we composed the processing elements of thin-film transistors, which are promising for giant microelectronics applications, and formed a cellular neural...
We are developing neural networks using thin-film transistors (TFTs). By adopting an interconnect-type neural network and utilizing a characteristic degradation of poly-Si TFTs as a variable strength of synapse connection, which was originally an issue, we realized the neuron consisting of eight TFTs and synapse of only one TFT. Particularly in this presentation, we confirmed that the learning efficiency...
It was tried to form Pickering emulsion by use of paraffin wax as a phase change material (PCM) and SiC as solid powder and to apply to the preparation of the hybrid microcapsules with the interfacial polycondensation reaction. Pickering emulsion could be formed by stirring PCM and SiC in the continuous water phase. The mean diameter of PCM droplets in the (O/W) emulsion decreased with the added amount...
We are developing device-level neural networks using poly-Si TFTs. We succeeded in dramatically reducing the number of transistors in neurons and synapses to integrate a lot of devices, and we also succeeded in actually checking the operation of learning of logics. In this presentation, for the purpose of improvement of learning efficiency, we changed the synapse TFTs from the SD structure to the...
We are developing neural networks of device level using thin-film transistors (TFT). By adopting an interconnect-type neural network and utilizing a characteristic shift of poly-Si TFTs as a variable strength of synapse connection, which was originally an issue, we realized the neuron consisting of eight TFTs and synapse of only one TFT. Particularly in this presentation, we confirmed the working...
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