Abstract
Simplification of processing elements is greatly desired in cellular neural networks to realize ultra-large scale integration. First, we propose reducing a neuron to two-inverter two-switch circuit, two-inverter one-switch circuit, or two-inverter circuit. Next, we propose reducing a synapse only to one variable resistor or one variable capacitor. Finally, we confirm the correct workings of the cellular neural networks using circuit simulation. These results will be one of the theoretical bases to apply cellular neural networks to brain-type integrated circuits.
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Kimura, M., Nakamura, N., Yokoyama, T., Matsuda, T., Kameda, T., Nakashima, Y. (2016). Simplification of Processing Elements in Cellular Neural Networks. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9948. Springer, Cham. https://doi.org/10.1007/978-3-319-46672-9_35
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DOI: https://doi.org/10.1007/978-3-319-46672-9_35
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