Pattern recognition with memristor networks

In this paper we develop the concept of implementing pattern recognition algorithms in analog memristor networks. First, a device model is presented with experimental results demonstrating the feasibility of using WOx-based memristors to represent the tunable weights in a neural network. Next, simulation results demonstrate that an array of these memristors can be used to implement an unsupervised learning algorithm for pattern recognition. Handwritten digits are classified as an example problem while the concept is developed for more general use.