Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6862988 | Neural Networks | 2018 | 8 Pages |
Abstract
Memristor describes the relationship between charge and flux. Although several window functions for memristors based on the HP linear and nonlinear dopant drift models have been studied, most of them are inadequate to capture the full characteristics of memristors. To address this issue, this paper proposes a unified window function to describe a general memristor with restrictions of its parameters given. Compared with other window functions, the proposed function demonstrates high validity and accuracy. In order to make the simulation results have high consistency with the results of actual circuit, we apply the new window function to the simulation of a memristor-based multilayer neural network (MNN) circuit. The overall accuracy will vary with the change of control parameters in the window function. It implies that the proposed model can guide the design of actual memristor-based circuits.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Shiping Wen, Xudong Xie, Zheng Yan, Tingwen Huang, Zhigang Zeng,