Formation of Weighting Coefficients in an Artificial Neural Network Based on the Memristive Effect in Metal–Oxide–Metal Nanostructures

Experimental study of gradual/abrupt dynamics of HfO2-based memristive devices

(2016) S. Brivio et al.   APPLIED PHYSICS LETTERS

Neuromorphic elements and systems as the basis for the physical implementation of artificial intelligence technologies

(2016) V. A. Demin et al.   CRYSTALLOGRAPHY REPORTS

Resistive switching memories based on metal oxides: mechanisms, reliability and scaling

(2016) Daniele Ielmini   SEMICONDUCTOR SCIENCE AND TECHNOLOGY

First steps towards the realization of a double layer perceptron based on organic memristive devices

(2016) A. V. Emelyanov et al.   AIP Advances

Realization of Boolean Logic Functionality Using Redox-Based Memristive Devices

(2015) Anne Siemon et al.   ADVANCED FUNCTIONAL MATERIALS

A Circuit-Based Learning Architecture for Multilayer Neural Networks With Memristor Bridge Synapses

(2015) Shyam Prasad Adhikari et al.   IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS

Bipolar resistive switching and charge transport in silicon oxide memristor

(2015) Alexey N. Mikhaylov et al.   Materials Science and Engineering B-Advanced Functional Solid-State Materials

Training and operation of an integrated neuromorphic network based on metal-oxide memristors

(2015) M. Prezioso et al.   NATURE

Hardware elementary perceptron based on polyaniline memristive devices

(2015) V.A. Demin et al.   ORGANIC ELECTRONICS

Associative memory realized by a reconfigurable memristive Hopfield neural network

(2015) S.G. Hu et al.   Nature Communications

Bipolar resistive switching and charge transport in silicon oxide memristor

(2015) Alexey N. Mikhaylov et al.   Materials Science and Engineering B-Advanced Functional Solid-State Materials

Resistive switching phenomena in thin films: Materials, devices, and applications

(2012) D.B. Strukov et al.   MRS BULLETIN

Experimental demonstration of associative memory with memristive neural networks

(2010) Yuriy V. Pershin et al.   NEURAL NETWORKS