Results 81 to 90 of about 1,610,508 (369)

NAX: Co-Designing Neural Network and Hardware Architecture for Memristive Xbar based Computing Systems [PDF]

open access: yesarXiv, 2021
In-Memory Computing (IMC) hardware using Memristive Crossbar Arrays (MCAs) are gaining popularity to accelerate Deep Neural Networks (DNNs) since it alleviates the "memory wall" problem associated with von-Neumann architecture. The hardware efficiency (energy, latency and area) as well as application accuracy (considering device and circuit non ...
arxiv  

Cortical Excitability Before and After Long‐Term Perampanel Treatment for Epilepsy

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Antiseizure medications (ASMs), which may influence cortical excitability, are the mainstay of epilepsy treatment. Transcranial magnetic stimulation (TMS) helps evaluate cortical excitability. We assessed changes in TMS responses using serial TMS measurements in people treated with an adjunctive noncompetitive AMPA‐receptor ...
Robert M. Helling   +6 more
wiley   +1 more source

Discovering Multi-Hardware Mobile Models via Architecture Search [PDF]

open access: yesarXiv, 2020
Hardware-aware neural architecture designs have been predominantly focusing on optimizing model performance on single hardware and model development complexity, where another important factor, model deployment complexity, has been largely ignored. In this paper, we argue that, for applications that may be deployed on multiple hardware, having different
arxiv  

Department of Electrical Engineering and Computer Science Records [PDF]

open access: yes, 2018
The Electrical Engineering and Computer Science Department combines all aspects of electricity, electronics, hardware, and software into one multi-disciplinary unit, offering degree programs in Electrical Engineering and Computer Science with minors in ...
SDSU Archives and Special Collections, Hilton M. Briggs Library
core   +1 more source

The Role of Telematic Practices in Computer Engineering: A Low-cost Remote Power Control in a Network Lab

open access: yesInternational Journal of Online Engineering (iJOE), 2012
The present paper describes a practical solution of e-learning laboratory devoted to the study of computer networks. This laboratory has been proven with two groups of students from the University of Huelva (Spain) during two academic years.
T. M. Sanguino   +2 more
semanticscholar   +1 more source

Translating Muscle RNAseq Into the Clinic for the Diagnosis of Muscle Diseases

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Approximately half of patients with hereditary myopathies remain without a definitive genetic diagnosis after DNA next‐generation sequencing (NGS). Here, we implemented transcriptome analysis of muscle biopsies as a complementary diagnostic tool for patients with muscle disease but no definitive genetic diagnosis after exome ...
Alba Segarra‐Casas   +24 more
wiley   +1 more source

4-H Computer & Internet Project [PDF]

open access: yes, 2018
Knowing how to operate a computer and write code is quickly becoming a required 21st century skill. A 4-H computer project will help you learn about software and/or hardware topics •Learn about computer hardware •Explore and learn to navigate an ...
Borba, John   +7 more
core  

A Multidisciplinary Team Project For Electrical Engineering, Computer Engineering, And Computer Science Majors

open access: yes, 2000
This paper describes an interdisciplinary project for a freshman course designed for electrical engineering, computer engineering, and computer science majors.
Deborah J. Hwang, D. Blandford
semanticscholar   +1 more source

HPC‐GAP: engineering a 21st‐century high‐performance computer algebra system

open access: yesConcurrency and Computation, 2016
Symbolic computation has underpinned a number of key advances in Mathematics and Computer Science. Applications are typically large and potentially highly parallel, making them good candidates for parallel execution at a variety of scales from multi‐core
R. Behrends   +7 more
semanticscholar   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez   +2 more
wiley   +1 more source

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