Výsledky vyhledávání - "David E. Stewart"

Akademický článek

Nonuniqueness and fractional index convolution complementarity problems

Autor: David E. Stewart

Publikováno v: Electronic Journal of Differential Equations, Vol 2014, Iss 226,, Pp 1-9 (2014)

Uniqueness of solutions of fractional index convolution complementarity problems (CCPs) has been shown for index $1+\alpha$ with $-1

Externí odkaz: https://doaj.org/article/62410a21b90b4500acf47d3a3a3a6bd9

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Elektronická kniha

Writing Scientific Software : A Guide to Good Style

Autor: Suely Oliveira, David E. Stewart

The core of scientific computing is designing, writing, testing, debugging and modifying numerical software for application to a vast range of areas: from graphics, meteorology and chemistry to engineering, biology and finance. Scientists, engineers

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Recorp: Receiver-oriented Policies for Industrial Wireless Networks

Autor: David E. Stewart, Kowsar Hossain, Octav Chipara, Ryan Brummet, Ted Herman

Publikováno v: ACM Transactions on Sensor Networks. 17:1-32

Future Industrial Internet-of-Things (IIoT) systems will require wireless solutions to connect sensors, actuators, and controllers as part of high data rate feedback-control loops over real-time flows. A key challenge in such networks is to provide p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82f69ba8a2191a0f3400966764d53543
https://doi.org/10.1145/3460618

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Approximation Properties of Ridge Functions and Extreme Learning Machines

Autor: David E. Stewart, Palle Jorgensen

Publikováno v: SIAM Journal on Mathematics of Data Science. 3:815-832

For a compact set $D\subset\mathbb{R}^{m}$ we consider the problem of approximating a function $f$ over $D$ by sums of ridge functions ${x}\mapsto\varphi({w}^{T}{x})$ with ${w}$ in a given set $\ma...

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::086c6befcd8a8a2d1a5e24912a995960
https://doi.org/10.1137/20m1356348

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A modified Lanczos Algorithm for fast regularization of extreme learning machines

Autor: Edward R. Ratner, Kaj-Mikael Björk, Amaury Lendasse, David E. Stewart, Renjie Hu

Publikováno v: Neurocomputing. 414:172-181

This paper presents a new regularization for Extreme Learning Machines (ELMs). ELMs are Randomized Neural Networks (RNNs) that are known for their fast training speed and good accuracy. Nevertheless the complexity of ELMs has to be selected, and regu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f3224290dec1f4423f48d0b0bc32a19e
https://doi.org/10.1016/j.neucom.2020.07.015

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