Zobrazeno 1 - 10
of 534
pro vyhledávání: '"Rough functions"'
Deep neural networks and the ENO procedure are both efficient frameworks for approximating rough functions. We prove that at any order, the ENO interpolation procedure can be cast as a deep ReLU neural network. This surprising fact enables the transf
Externí odkaz:
http://arxiv.org/abs/1912.06732
For given $p\in\lbrack1,\infty]$ and $g\in L^{p}\mathbb{(R)}$, we establish the existence and uniqueness of solutions $f\in L^{p}(\mathbb{R)}$, to the equation \[ f(x)-af(bx)=g(x), \] where $a\in\mathbb{R}$, $b\in\mathbb{R} \setminus \{0\}$, and $\le
Externí odkaz:
http://arxiv.org/abs/1412.3871
Publikováno v:
In Journal of Approximation Theory September 2016 209:23-43
Autor:
Brownlee, R. A., Light, W. A.
Publikováno v:
IMA J. Numer. Anal., 24(2):179-192, 2004
In this paper we consider the approximation of functions by radial basis function interpolants. There is a plethora of results about the asymptotic behaviour of the error between appropriately smooth functions and their interpolants, as the interpola
Externí odkaz:
http://arxiv.org/abs/0705.4281
Publikováno v:
SeMA Journal, 79 (3)
The essentially non-oscillatory (ENO) procedure and its variant, the ENO-SR procedure, are very efficient algorithms for interpolating (reconstructing) rough functions. We prove that the ENO (and ENO-SR) procedure are equivalent to deep ReLU neural n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3aed36d3029066c77150e821f6074cd4
Akademický článek
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Autor:
De Ryck, Tim
Deep neural networks and the ENO procedure are both efficient frameworks for approximating rough functions. We prove that at any order, the stencil shifts of the ENO and ENO-SR interpolation procedures can be exactly obtained using a deep ReLU neural
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0051f86e353c6aff312bad0464e658e
Publikováno v:
SAM Research Report, 2020-07
Deep neural networks and the ENO procedure are both efficient frameworks for approximating rough functions. We prove that at any order, the ENO interpolation procedure can be cast as a deep ReLU neural network. This surprising fact enables the transf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______150::389778c74a078da86c452fe175cdf26f
https://hdl.handle.net/20.500.11850/429916
https://hdl.handle.net/20.500.11850/429916
Akademický článek
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Publikováno v:
Journal of Approximation Theory. 209:23-43
For given $p\in\lbrack1,\infty]$ and $g\in L^{p}\mathbb{(R)}$, we establish the existence and uniqueness of solutions $f\in L^{p}(\mathbb{R)}$, to the equation \[ f(x)-af(bx)=g(x), \] where $a\in\mathbb{R}$, $b\in\mathbb{R} \setminus \{0\}$, and $\le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0f8b27361f3b5ba57230eb255204cc9