n294006SE Academic Article uri icon

abstract

  • 2016, The Natural Computing Applications Forum. In this paper, an architecture based on memristors is proposed to implement image convolution computation in convolutional neural networks. This architecture could extract different features of input images when using different convolutional kernels. Bipolar memristors with threshold are employed in this work, which vary their conductance values under different voltages. Various kernels are needed to extract information of input images, while different kernels contain different weights. The memristances of bipolar memristors with threshold are convenient to be varied and kept, which make them suitable to act as the weights of kernels. The performances of the design are verified by simulation results.

published proceedings

  • Neural Computing and Applications

author list (cited authors)

  • Zeng, X., Wen, S., Zeng, Z., & Huang, T.

publication date

  • January 1, 2018 11:11 AM