Capacitive neural network with neuro-transistors. Academic Article uri icon


  • Experimental demonstration of resistive neural networks has been the recent focus of hardware implementation of neuromorphic computing. Capacitive neural networks, which call for novel building blocks, provide an alternative physical embodiment of neural networks featuring a lower static power and a better emulation of neural functionalities. Here, we develop neuro-transistors by integrating dynamic pseudo-memcapacitors as the gates of transistors to produce electronic analogs of the soma and axon of a neuron, with "leaky integrate-and-fire" dynamics augmented by a signal gain on the output. Paired with non-volatile pseudo-memcapacitive synapses, aHebbian-like learning mechanism is implemented in a capacitive switching network, leading to the observed associative learning. A prototypical fully integrated capacitive neural network is built and used to classify inputs of signals.

published proceedings

  • Nat Commun

altmetric score

  • 14.25

author list (cited authors)

  • Wang, Z., Rao, M., Han, J., Zhang, J., Lin, P., Li, Y., ... Yang, J. J.

citation count

  • 192

complete list of authors

  • Wang, Zhongrui||Rao, Mingyi||Han, Jin-Woo||Zhang, Jiaming||Lin, Peng||Li, Yunning||Li, Can||Song, Wenhao||Asapu, Shiva||Midya, Rivu||Zhuo, Ye||Jiang, Hao||Yoon, Jung Ho||Upadhyay, Navnidhi Kumar||Joshi, Saumil||Hu, Miao||Strachan, John Paul||Barnell, Mark||Wu, Qing||Wu, Huaqiang||Qiu, Qinru||Williams, R Stanley||Xia, Qiangfei||Yang, J Joshua

publication date

  • August 2018