Results 261 to 270 of about 75,209 (310)

On Error Bounds for Quasinormal Programs

Journal of Optimization Theory and Applications, 2010
Let \(I\) and \(I_{0}\) be finite index sets, \(h_{i}:\mathbb{R}^{m}\rightarrow \mathbb{R}\) \((i\in I\cup I_{0})\) be continuously differentiable functions, and \(C:=\{y\in \mathbb{R}^{m}:h_{i}(y)\leq 0\) \((i\in I),\) \(h_{i}(y)=0\) \((i\in I_{0})\}\). The main result states that, assuming that the gradients \(\nabla h_{i}(y)\) \((i\in I\cup I_{0})\)
Leonid Minchenko, Alexander Tarakanov
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On bounded‐error identification of feedback systems

International Journal of Adaptive Control and Signal Processing, 1995
This paper studies identification of linear feedback systems from closed loop time series. Unfalsified approximate bounded error identification is shown to result in a control-relevant identification methodology for robustness optimization under BIBO ...
P M Mäkilä, Jonathan R Partington
exaly   +2 more sources

Error-bounded compatible remeshing

ACM Transactions on Graphics, 2020
We present a novel method to construct compatible surface meshes with bounded approximation errors. Given two oriented and topologically equivalent surfaces and a sparse set of corresponding landmarks, our method contains two steps: (1) generate compatible meshes with bounded approximation errors and (2) reduce mesh complexity while ensuring that ...
Yang Yang 0065, Wen-Xiang Zhang, Yuan Liu 0025, Ligang Liu 0001, Xiao-Ming Fu 0001   +4 more
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Sufficient Conditions for Error Bounds

SIAM Journal on Optimization, 2002
Summary: For a lower semicontinuous (l.s.c.) inequality system on a Banach space, it is shown that error bounds hold, provided every element in an abstract subdifferential of the constraint function at each point outside the solution set is norm bounded away from zero. A sufficient condition for a global error bound to exist is also given for an l.s.c.
Zili Wu, Jane J. Ye
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On the Complexity of Computing Error Bounds

Foundations of Computational Mathematics, 2001
The authors study the cost of estimating the norm of an inverse matrix. They conjecture that finding even a coarse error bound is as costly as that of matrix inversion itself. Conversely, any fast condition estimate must sometimes mis-estimate by a sizable amount, specified quantitatively in the paper.
James Demmel, Benjamin Diament, Gregorio Malajovich   +2 more
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Error estimation and error bounds for neural networks

Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, 2002
A method is proposed to estimate the standard error of predicted values in multilayer perceptron (MLP). It is based on likelihood theory. It holds for all feedforward networks, irrespective of the topology or the specific task at hand. In addition, the bounds on a neural network with perturbed weights and inputs is analytically derived.
Hualou Liang, Guiliang Dai
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Bounds and error estimates for radiosity

Proceedings of the 21st annual conference on Computer graphics and interactive techniques - SIGGRAPH '94, 1994
We present a method for determining a posteriori bounds and estimates for local and total errors in radiosity solutions. The ability to obtain bounds and estimates for the total error is crucial fro reliably judging the acceptability of a solution. Realistic estimates of the local error improve the efficiency of adaptive radiosity algorithms, such as ...
Dani Lischinski, Brian E. Smits, Donald P. Greenberg   +2 more
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Bounds and error bounds for queueing networks

Annals of Operations Research, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Error Bound for Conic Inequality

Vietnam Journal of Mathematics, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zheng, Xi Yin, Ng, Kung Fu
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Error Bounds for Convex Polynomials

SIAM Journal on Optimization, 2009
In this paper, the author establishes new properties of convex multivariate polynomials, using convex analysis. The author shows that for a convex polynomial \(f\) which is not constant on any affine subspace, if the lower level set of \(f\) (i.e., the set where \(f\) is nonpositive) is unbounded, then \(f\) can be represented as a sum of a convex ...
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