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This paper presents a three layer spiking neural network based region proposal network operating on data generated by neuromorphic vision sensors. The proposed architecture consists of refractory, convolution and clustering layers designed…

Neural and Evolutionary Computing · Computer Science 2019-02-27 Jyotibdha Acharya , Vandana Padala , Arindam Basu

Accurate, timely and selective detection of moving obstacles is crucial for reliable collision avoidance in autonomous robots. The area- and energy-inefficiency of CMOS-based spiking neurons for obstacle detection can be addressed through…

Mesoscale and Nanoscale Physics · Physics 2023-09-21 Kartikey Thakar , Bipin Rajendran , Saurabh Lodha

Field-free switching of perpendicularly magnetized ferromagnetic layer by spin orbit torque (SOT) from the spin Hall effect (SHE) is of great interest in the applications of magnetic memory devices. In this paper, we investigate the…

Applied Physics · Physics 2020-04-22 Kai Wu , Diqing Su , Renata Saha , Jian-Ping Wang

Nanoscale resistive memories are expected to fuel dense integration of electronic synapses for large-scale neuromorphic system. To realize such a brain-inspired computing chip, a compact CMOS spiking neuron that performs in-situ learning…

Neural and Evolutionary Computing · Computer Science 2015-11-25 Xinyu Wu , Vishal Saxena , Kehan Zhu , Sakkarapani Balagopal

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)…

Artificial Intelligence · Computer Science 2026-02-10 Xun Su , Huamin Wang , Qi Zhang

We present a circuit model to describe the electron transport through a domain wall in a ferromagnetic nanowire. The domain wall is treated as a coherent 4-terminal device with incoming and outgoing channels of spin up and down and the…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Peter E. Falloon , Rodolfo A. Jalabert , Dietmar Weinmann , Robert L. Stamps

We propose a new type of multi-bit and energy-efficient magnetic memory based on current-driven, field-free, and highly controlled domain wall motion. A meandering domain wall channel with precisely interspersed pinning regions provides the…

Emerging Technologies · Computer Science 2024-05-29 Pengxiang Zhang , Wilfried Haensch , Charudatta M. Phatak , Supratik Guha

With the rise in in-memory computing architectures to reduce the compute-memory bottleneck, a new bottleneck is present between analog and digital conversion. Analog content-addressable memories (ACAM) are being recently studied for…

We propose energy efficient strain control of domain wall (DW) in a perpendicularly magnetized nanoscale racetrack on a piezoelectric substrate that can implement multi state synapse to be utilized in neuromorphic computing platforms. In…

Mesoscale and Nanoscale Physics · Physics 2021-11-29 Walid Al Misba , Tahmid Kaisar , Dhritiman Bhattacharya , Jayasimha Atulasimha

Perpendicular MgO-based Magnetic Tunnel Junctions are optimal candidates as building block of Spin Transfer Torque (STT) magnetoresistive memories. However, up to now, the only STT is not enough to achieve switching current density below…

Materials Science · Physics 2015-03-13 M. Carpentieri , R. Tomasello , M. Ricci , P. Burrascano , G. Finocchio

Control of magnetism without using magnetic fields enables large-scale integration of spintronic devices for memory, computation and communication in the beyond-CMOS era. Mechanisms including spin torque transfer, spin Hall effect, and…

Materials Science · Physics 2017-03-08 Jun-Yang Chen , Li He , Jian-Ping Wang , Mo Li

Neuromorphic computing is an emerging technology enabling low-latency and energy-efficient signal processing. A key algorithmic tool in neuromorphic computing is spiking neural networks (SNNs). SNNs are biologically inspired neural networks…

Machine Learning · Computer Science 2025-08-11 Sanja Karilanova , Subhrakanti Dey , Ayça Özçelikkale

We study the spin-dependent transport properties of a spin valve based on a double quantum dot. Each quantum dot is assumed to be strongly coupled to its own ferromagnetic lead, while the coupling between the dots is relatively weak. The…

Mesoscale and Nanoscale Physics · Physics 2021-07-21 Patrycja Tulewicz , Kacper Wrzesniewski , Szabolcs Csonka , Ireneusz Weymann

Computation on a large volume of data at high speed and low power requires energy-efficient computing architectures. Spiking neural network (SNN) with bio-inspired spike-timing-dependent plasticity learning (STDP) is a promising solution…

Image and Video Processing · Electrical Eng. & Systems 2022-04-12 Sahibia Kaur Vohra , Sherin A Thomas , Mahendra Sakare , Devarshi Mrinal Das

As an intriguing ultra-small particle-like magnetic texture, skyrmion has attracted lots of research interests in next-generation ultra-dense and low power magnetic memory/logic designs. Previous studies have demonstrated a single…

Emerging Technologies · Computer Science 2017-02-23 Zhezhi He , Shaahin Angizi , Deliang Fan

As artificial neural networks become increasingly integrated into safety-critical systems such as autonomous vehicles, devices for medical diagnosis, and industrial automation, ensuring their reliability in the face of random hardware…

Neural and Evolutionary Computing · Computer Science 2024-09-05 Anil Bayram Gogebakan , Enrico Magliano , Alessio Carpegna , Annachiara Ruospo , Alessandro Savino , Stefano Di Carlo

Due to the fundamental limit to reducing power consumption of running deep learning models on von-Neumann architecture, research on neuromorphic computing systems based on low-power spiking neural networks using analog neurons is in the…

Neural and Evolutionary Computing · Computer Science 2022-03-03 Hanseok Kim , Woo-Seok Choi

Spin-orbit torque (SOT) represents an energy efficient method to control magnetization in magnetic memory devices. However, deterministically switching perpendicular memory bits usually requires the application of an additional bias field…

Applied Physics · Physics 2018-10-03 Qianchang Wang , John Domann , Guoqiang Yu , Anthony Barra , Kang L. Wang , Gregory P. Carman

We propose an effect whereby an electric current along the interface between a ferromagnetic and normal metal leads to injection of pure spin current into the normal metal, if the magnetization-direction in the ferromagnet varies along the…

Mesoscale and Nanoscale Physics · Physics 2013-08-28 E. van der Bijl , R. E. Troncoso , R. A. Duine

The use of analog resistance states for storing weights in neuromorphic systems is impeded by fabrication imprecision and device stochasticity that limit the precision of synapse weights. This challenge can be resolved by emulating analog…

Neural and Evolutionary Computing · Computer Science 2021-12-13 Peng Zhou , Julie A. Smith , Laura Deremo , Stephen K. Heinrich-Barna , Joseph S. Friedman