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Spintronic nano-oscillators with reduced non-linearity could offer key benefits for realizing neuromorphic applications such as spike-based neurons and frequency multiplexing in neural networks. Here, we experimentally demonstrate the…

Artificial intelligence is widely used in everyday life. However, an insufficient computing efficiency due to the so-called von Neumann bottleneck cannot satisfy the demand for real-time processing of rapidly growing data. Memristive…

Applied Physics · Physics 2024-02-23 Jing Yang , Lingxiang Hu , Liufeng Shen , Jingrui Wang , Peihong Cheng , Huanming Lu , Fei Zhuge , Zhizhen Ye

Spin-orbit torque (SOT) can drive sustained spin wave (SW) auto-oscillations in a class of emerging microwave devices known as spin Hall nano-oscillators (SHNOs), which have highly non-linear properties governing robust mutual…

Memristive associative learning has gained significant attention for its ability to mimic fundamental biological learning mechanisms while maintaining system simplicity. In this work, we introduce a high-order memristive associative…

Neural and Evolutionary Computing · Computer Science 2024-10-23 Shengbo Wang , Xuemeng Li , Jialin Ding , Weihao Ma , Ying Wang , Luigi Occhipinti , Arokia Nathan , Shuo Gao

Memristors are nonlinear two-terminal circuit elements whose resistance at a given time depends on past electrical stimuli. Recently, networks of memristors have received attention in neuromorphic computing since they can be used to…

Optimization and Control · Mathematics 2025-07-22 H. M. Heidema , H. J. van Waarde , B. Besselink

Neuromorphic computing, inspired by the brain's parallel and energy-efficient processing, offers a transformative approach to artificial intelligence. In this study, we fabricated optimized spin-transfer torque nano-oscillators (STNOs) and…

Artificial neural networks are intensively used to perform cognitive tasks such as image classification on traditional computers. With the end of CMOS scaling and increasing demand for efficient neural networks, alternative architectures…

Emerging Technologies · Computer Science 2017-11-29 Damir Vodenicarevic , Nicolas Locatelli , Damien Querlioz

Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Their additive…

We demonstrate and experimentally validate an end-to-end hybrid CMOS-memristor auditory encoder that realises adaptive-threshold, asynchronous delta-modulation (ADM)-based spike encoding by exploiting the inherent volatility of HfTiOx…

Audio and Speech Processing · Electrical Eng. & Systems 2025-12-08 Dongxu Guo , Deepika Yadav , Patrick Foster , Spyros Stathopoulos , Mingyi Chen , Themis Prodromakis , Shiwei Wang

Constriction-based spin Hall nano-oscillators (SHNOs) show great promise for application as highly tunable microwave sources with straightforward scalability toward large coupled networks. However, details of the magnetization dynamics…

Brain-inspired computing architectures attempt to emulate the computations performed in the neurons and the synapses in human brain. Memristors with continuously tunable resistances are ideal building blocks for artificial synapses. Through…

We report a memory resistance (memristor) behavior with nonlinear current-voltage characteristics and bipolar hysteretic resistance switching in the nanocolumnar manganite (LSMO) films. The switching from a high (HRS) to a low (LRS)…

Mesoscale and Nanoscale Physics · Physics 2010-02-03 V. Moshnyaga , M. Esseling , L. Sudheendra , O. I. Lebedev , K. Gehrke , G. Van Tendeloo , K. Samwer

Memristive devices whose resistance can be hysteretically switched by electric field or current are intensely pursued both for fundamental interest as well as potential applications in neuromorphic computing and phase-change memory. When…

Emerging non-volatile memory (NVM), or memristive, devices promise energy-efficient realization of deep learning, when efficiently integrated with mixed-signal integrated circuits on a CMOS substrate. Even though several algorithmic…

Neural and Evolutionary Computing · Computer Science 2018-04-23 Vishal Saxena , Xinyu Wu , Kehan Zhu

The advent of nanoscale memristors raised hopes of being able to build CMOL (CMOS/nanowire/moLecular) type ultra-dense in-memory-computing circuit architectures. In CMOL, nanoscale memristors would be fabricated at the intersection of…

Emerging Technologies · Computer Science 2022-09-14 L. A. Camuñas-Mesa , E. Vianello , C. Reita , T. Serrano-Gotarredona , B. Linares-Barranco

Memristors, as emerging nano-devices, offer promising performance and exhibit rich electrical dynamic behavior. Having already found success in applications such as neuromorphic and in-memory computing, researchers are now exploring their…

Cryptography and Security · Computer Science 2023-12-05 Ziang Chen , Li-Wei Chen , Xianyue Zhao , Kefeng Li , Heidemarie Schmidt , Ilia Polian , Nan Du

Memristors have shown promising features for enhancing neuromorphic computing concepts and AI hardware accelerators. In this paper, we present a user-friendly software infrastructure that allows emulating a wide range of neuromorphic…

Neural and Evolutionary Computing · Computer Science 2022-07-19 Jinqi Huang , Spyros Stathopoulos , Alex Serb , Themis Prodromakis

Controllable quantized conductance states of TiN/Ti/HfO$_x$/TiN memristors are realized with great precision through a pulse-mode reset procedure, assisted with analytical differentiation of the condition of the set procedure, which…

Mesoscale and Nanoscale Physics · Physics 2021-09-29 Min-Hsuan Peng , Ching-Yang Pan , Hao-Xuan Zheng , Ting-Chang Chang , Pei-hsun Jiang

Here we demonstrate that both, tunnel magneto resistance (TMR) and resistive switching (RS), can be observed simultaneously in nano-scale magnetic tunnel junctions. The devices show bipolar RS of 6 % and TMR ratios of about 100 %. For each…

Materials Science · Physics 2015-05-13 P. Krzysteczko , G. Reiss , A. Thomas

The dynamics of memristive device in response to neuron-like signals and coupling electronic neurons via memristive device has been investigated theoretically and experimentally. The simplest experimental system consists of electronic…