English
Related papers

Related papers: Spin-Orbit Torque Induced Spike-Timing Dependent P…

200 papers

The spin-orbit torques (SOTs) generated from topological insulators (TIs) have gained increasing attention in recent years. These TIs, which are typically formed by epitaxially grown chalcogenides, possess extremely high SOT efficiencies…

Materials Science · Physics 2020-02-18 Tian-Yue Chen , Cheng-Wei Peng , Tsung-Yu Tsai , Wei-Bang Liao , Chun-Te Wu , Hung-Wei Yen , Chi-Feng Pai

Spike-Timing Dependent Plasticity (STDP) is believed to play an important role in learning and the formation of computational function in the brain. The classical model of STDP which considers the timing between pairs of pre-synaptic and…

Neural and Evolutionary Computing · Computer Science 2013-03-21 Mostafa Rahimi Azghadi , Said Al-Sarawi , Nicolangelo Iannella , Derek Abbott

Spintronic nano-neurons offer a promising route towards energy-efficient, high-performance hardware neural networks thanks to their inherent low-input nonlinear dynamics. However, training such networks remains a major bottleneck as it…

Magnetic skyrmions are particle-like topological spin configurations, which can carry binary information and thus are promising building blocks for future spintronic devices. In this work, we investigate the relationship between the…

Applied Physics · Physics 2020-03-25 Xue Liang , Xichao Zhang , Jing Xia , Motohiko Ezawa , Yuelei Zhao , Guoping Zhao , Yan Zhou

Magnetic devices are a leading contender for implementing memory and logic technologies that are nonvolatile, that can scale to high density and high speed, and that do not suffer wear-out. However, widespread applications of magnetic…

Mesoscale and Nanoscale Physics · Physics 2015-06-18 A. R. Mellnik , J. S. Lee , A. Richardella , J. L. Grab , P. J. Mintun , M. H. Fischer , A. Vaezi , A. Manchon , E. -A. Kim , N. Samarth , D. C. Ralph

We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high efficiency associated with neuromorphic implementations, we…

Neurons and Cognition · Quantitative Biology 2016-10-14 Simon Friedmann , Johannes Schemmel , Andreas Gruebl , Andreas Hartel , Matthias Hock , Karlheinz Meier

Spiking neural networks (SNN) are considered as a perspective basis for performing all kinds of learning tasks - unsupervised, supervised and reinforcement learning. Learning in SNN is implemented through synaptic plasticity - the rules…

Neural and Evolutionary Computing · Computer Science 2021-11-15 Mikhail Kiselev

Spin transfer torques allow the electrical manipulation of the magnetization at room temperature, which is desirable in spintronic devices such as spin transfer torque memories. When combined with spin-orbit coupling, they give rise to…

Analog electronic non-volatile memories mimicking synaptic operations are being explored for the implementation of neuromorphic computing systems. Compound synapses consisting of ensembles of stochastic binary elements are alternatives to…

Applied Physics · Physics 2019-10-02 Vaibhav Ostwal , Ramtin Zand , Ronald DeMara , Joerg Appenzeller

Spintronics, the use of spin of an electron instead of its charge, has received huge attention from research communities for different applications including memory, interconnects, logic implementation, neuromorphic computing, and many…

The adaptive changes in synaptic efficacy that occur between spiking neurons have been demonstrated to play a critical role in learning for biological neural networks. Despite this source of inspiration, many learning focused applications…

Neural and Evolutionary Computing · Computer Science 2022-05-30 Samuel Schmidgall , Julia Ashkanazy , Wallace Lawson , Joe Hays

The demand for computing power has been growing exponentially with the rise of artificial intelligence (AI), machine learning, and the Internet of Things (IoT). This growth requires unconventional computing primitives that prioritize energy…

The recent surge of interest in brain-inspired computing and power-efficient electronics has dramatically bolstered development of computation and communication using neuron-like spiking signals. Devices that can produce rapid and…

A device based on current-induced spin-orbit torque (SOT) that functions as an electronic neuron is proposed in this work. The SOT device implements an artificial neuron's thresholding (transfer) function. In the first step of a two-step…

Emerging Technologies · Computer Science 2015-06-23 Abhronil Sengupta , Sri Harsha Choday , Yusung Kim , Kaushik Roy

Spiking neural networks (SNNs) communicate via discrete spikes in time rather than continuous activations. Their event-driven nature offers advantages for temporal processing and energy efficiency on resource-constrained hardware, but…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Karol C. Jurzec , Tomasz Szydlo , Maciej Wielgosz

Molecule-based devices are envisioned to complement silicon devices by providing new functions or already existing functions at a simpler process level and at a lower cost by virtue of their self-organization capabilities. Moreover, they…

Mesoscale and Nanoscale Physics · Physics 2010-02-04 F. Alibart , S. Pleutin , D. Guerin , C. Novembre , S. Lenfant , K. Lmimouni , C. Gamrat , D. Vuillaume

Magnetic skyrmion-based data storage and unconventional computing devices have gained increasing attention due to their topological protection, small size, and low driving current. However, skyrmion creation, deletion, and motion are still…

Materials Science · Physics 2023-01-11 Aijaz H. Lone , Arnab Ganguly , Selma Amara , Gobind Das , H. Fariborzi

Spin-orbit torque is a promising mechanism for writing magnetic memories, while field-effect transistors are the gold-standard device for logic operation. The spin-orbit torque field effect transistor (SOTFET) is a proposed device that…

Triplet-based Spike Timing Dependent Plasticity (TSTDP) is a powerful synaptic plasticity rule that acts beyond conventional pair-based STDP (PSTDP). Here, the TSTDP is capable of reproducing the outcomes from a variety of biological…

Neural and Evolutionary Computing · Computer Science 2013-04-02 Mostafa Rahimi Azghadi , Said Al-Sarawi , Derek Abbott , Nicolangelo Iannella

Neuromorphic computing has recently gained momentum with the emergence of various neuromorphic processors. As the field advances, there is an increasing focus on developing training methods that can effectively leverage the unique…

Emerging Technologies · Computer Science 2025-04-15 Sanaz Mahmoodi Takaghaj , Jack Sampson
‹ Prev 1 3 4 5 6 7 10 Next ›