A Plausible Memristor Implementation of Deep Learning Neural Networks

A possible method for hardware implementation of multilayer neural networks with the back-propagation learning algorithm employing memristor cross-bar matrices for weight storage is modeled. The proposed approach offers an efficient way to perform both learning and recognition operations. The solution of several arising problems, such as the representation and multiplication of signals as well as error propagation is proposed.