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Artificial neural networks are promising systems for information processing with many advantages, such as self-teaching and parallel distributed computing. However, conventional ones consist of extremely intricate circuits to guarantee accurate behaviors of the neurons and synapses. We demonstrate an apoptotic self-organized electronic device using thin-film transistors for artificial neural networks...
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...
Artificial neural networks are promising systems for information processing that have many advantages. Here, we demonstrate an artificial neural network using poly-Si TFTs. It may be possible to integrate a large-scale artificial neural network comparable to the human brain. Particularly in this presentation, we verify that the artificial neural network can be re-organized by multiple overwriting.
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