|Title||An adjustable memristor model and its application in small-world neural networks|
|Publication Type||Conference Paper|
|Year of Publication||2014|
|Authors||X Hu, G Feng, H Li, Y Chen, and S Duan|
|Conference Name||Proceedings of the International Joint Conference on Neural Networks|
This paper presents a novel mathematical model for the TiO2 thin-film memristor device discovered by Hewlett-Packard (HP) labs. Our proposed model considers the boundary conditions and the nonlinear ionic drift effects by using a piecewise linear window function. Four adjustable parameters associated with the window function enable the model to capture complex dynamics of a physical HP memristor. Furthermore, we realize synaptic connections by utilizing the proposed memristor model and provide an implementation scheme for a small-world multilayer neural network. Simulation results are presented to validate the mathematical model and the performance of the neural network in nonlinear function approximation.