Related papers: Straintronic spin-neuron
Spiking Neural Networks (SNNs) are increasingly recognized for their biological plausibility and energy efficiency, positioning them as strong alternatives to Artificial Neural Networks (ANNs) in neuromorphic computing applications. SNNs…
Magnetic tunnel junctions (MTJs) are the key building blocks of high-performance spintronic devices. While conventional MTJs rely on ferromagnetic (FM) materials, employing antiferromagnetic (AFM) compounds can significantly increase…
We report the possibility of achieving an order of magnitude reduction in the energy dissipation needed to write bits in perpendicular magnetic tunnel junctions (p-MTJs) by simulating the magnetization dynamics under a combination of…
Complementary metal oxide semiconductor (CMOS) devices display volatile characteristics, and are not well suited for analog applications such as neuromorphic computing. Spintronic devices, on the other hand, exhibit both non-volatile and…
Diffusive memristors owing to their ability to produce current spiking when a constant or slowly changing voltage is applied are competitive candidates for the development of artificial electronic neurons. These artificial neurons can be…
Ensuring high performance, while meeting the power budget is a challenging task as the world is moving towards next-generation computing. Researchers and designers are in search of new solutions for efficient computation. Spintronics…
This paper investigates the impact of thermal stability relaxation in double-barrier magnetic tunnel junctions (DMTJs) for energy-efficient spin-transfer torque magnetic random access memories (STT-MRAMs) operating at the liquid nitrogen…
In this work, we simulate the functionality of artificial neuron and synapse using spin-orbit torque-based spintronic devices and implemented a fully connected artificial neural netwrok (ANN). These neuro-synaptic devices are emulated using…
Spiking Neural Networks (SNNs) are distinguished from Artificial Neural Networks (ANNs) for their complex neuronal dynamics and sparse binary activations (spikes) inspired by the biological neural system. Traditional neuron models use…
To mitigate climate change, our global society is harnessing direct (solar irradiation) and indirect (wind/water flow) sources of renewable electrical power generation. Emerging direct sources include current-producing thermal gradients in…
Brain-inspired learning in physical hardware has enormous potential to learn fast at minimal energy expenditure. One of the characteristics of biological learning systems is their ability to learn in the presence of various noise sources.…
A non-volatile SRAM cell is proposed for low power applications using Spin Transfer Torque-Magnetic Tunnel Junction (STT-MTJ) devices. This novel cell offers non-volatile storage, thus allowing selected blocks of SRAM to be switched off…
Speech Emotion Recognition (SER) is widely deployed in Human-Computer Interaction, yet the high computational cost of conventional models hinders their implementation on resource-constrained edge devices. Spiking Neural Networks (SNNs)…
Spintronic devices based on domain wall (DW) motion through ferromagnetic nanowire tracks have received great interest as components of neuromorphic information processing systems. Previous proposals for spintronic artificial neurons…
Shifting electrically a magnetic domain wall (DW) by the spin transfer mechanism is one of the future ways foreseen for the switching of spintronic memories or registers. The classical geometries where the current is injected in the plane…
Spintronic neurons which emit sharp voltage spikes are required for the realization of hardware neural networks enabling fast data processing with low-power consumption. In many neuroscience and computer science models, neurons are…
We propose a spintronic strain sensor capable of sensing strain with a sensitivity of 1E-13/sqrt{Hz} at room temperature with an active sensing area of 1 cmE2 and power dissipation of 1 watt. This device measures strain by monitoring the…
Molecular conduction channels between two ferromagnetic electrodes can produce strong exchange coupling and dramatic effect on the spin transport, thus enabling the realization of novel logic and memory devices. However, fabrication of…
We study current-induced switching in magnetic tunnel junctions (MTJs) in the presence of a field-like spin-transfer torque and titled pinned-layer magnetization in the high current limit at finite temperature. We consider both the…
Convolutional neural networks are state-of-the-art and ubiquitous in modern signal processing and machine vision. Nowadays, hardware solutions based on emerging nanodevices are designed to reduce the power consumption of these networks.…