Results 71 to 80 of about 4,696,608 (299)

Nitrospinics: Nitride Materials for Spin‐Orbit and Orbital Torques From Memory to Artificial Intelligence

open access: yesAdvanced Functional Materials, EarlyView.
Further advances in applications can be anticipated through the development of unique and functional materials beyond conventional alloys. Nitrogen enables tailor‐made orbital textures in various transition‐metal hosts, paving the way for devices ranging from spintronics memory to artificial intelligence hardware.
Prabhat Kumar   +3 more
wiley   +1 more source

A Hardware Generator of Multi-point Distributed Random Numbers for Monte Carlo Simulation [PDF]

open access: yes
Monte Carlo simulation of weak approximations of stochastic differential equations constitutes an intensive computational task. In applications such as finance, for instance, to achieve "real time" execution, as often required, one needs highly efficient
Filippo Martini   +3 more
core  

Neuromorphic Devices for Extreme Environments: State‐Variable Reliability and Stabilization Strategies

open access: yesAdvanced Functional Materials, EarlyView.
Neuromorphic devices for extreme environments are interpreted through the physical states that store and process information. Radiation, temperature extremes, and vacuum can perturb vacancies, filaments, trapped charges, polarization, interfaces, and readout signals.
Taehyun Park   +7 more
wiley   +1 more source

Hardware Implementation of Digital Base Band Videophone

open access: yesTongxin xuebao, 1995
The design and realization of 64kb/s digital monochrome videophone,which has been implemented in hardware,is discussed in this paper.The structure graph of hardware system,as well as flowsheet of control software in codec is showed.
秦仁忠, 孟焱, 张家谋
doaj   +2 more sources

On the Hardware Implementation of Triangle Traversal Algorithms for Graphics Processing [PDF]

open access: yes, 2010
Current GPU architectures provide impressive processing rates in graphical applications because of their specialized graphics pipeline. However, little attention has been paid to the analysis and study of different hardware architectures to implement ...
Royer del Barrio, Pablo   +3 more
core  

Programming Neuromorphic Plasticity Through Ionic and Electronic Coupling in Organic Electrochemical Transistors

open access: yesAdvanced Functional Materials, EarlyView.
Neuromorphic plasticity in OECTs is governed by the post‐stimulus evolution of coupled ionic and electronic states. Semiconductor chemistry and morphology, electrolyte composition and interfaces, and device architecture regulate ion injection, transport, confinement, and release, shifting responses from rapidly relaxing STP to metastable memory and ...
Inho Lee   +9 more
wiley   +1 more source

Design and implementation of parallel CRC algorithm for fibre channel on FPGA

open access: yesThe Journal of Engineering, 2019
Fibre channel (FC) provides the high-speed and low-latency communication between the end systems, widely used in data storage, aerospace applications and large electronic equipment including radar systems.
Wu Chuxiong, Shi Haifeng
doaj   +1 more source

A High Performance SOFM Hardware-System [PDF]

open access: yes, 1997
Rüping S, Porrmann M, Rückert U. A High Performance SOFM Hardware-System. In: Proceedings of the International Work-Conference on Artificial and Natural Neural Networks (IWANN´97).
Porrmann, Mario ; https://orcid.org/   +2 more
core  

Digitally Printed Eco‐Friendly Electronic Devices

open access: yesAdvanced Functional Materials, EarlyView.
Fabrication of electronics using eco‐friendly materials through digital printing routes is a promising strategy for improving life cycle sustainability and reducing the environmental impacts of conventional manufacturing. This review highlights state‐of‐the‐art eco‐friendly materials, green ink formulations, various resource‐efficient digital printing ...
Nitheesh M. Nair   +5 more
wiley   +1 more source

Power scalable implementation of artificial neural networks

open access: yes, 2005
As the use of Artificial Neural Network (ANN) in mobile embedded devices gets more pervasive, power consumption of ANN hardware is becoming a major limiting factor. Although considerable research efforts are now directed towards low-power implementations
Modi, Sankalp   +5 more
core   +2 more sources

Home - About - Disclaimer - Privacy