Results 241 to 250 of about 58,998 (260)

Regular Perturbations of Parameters

2004
A difference between real and idealized systems is very often reduced to perturbation of the input parameters. For instance, a thickness of a plate (or shell) is described via formula h = h 0 + eh(x, y) (h 0 = const, e ≪ 1); contour of the circle plate slightly differs from a circle via relation r(θ) = r 0 + e cos nθ, etc. Although often the considered
I. Andrianov, J. Awrejcewicz, L. I. Manevitch   +2 more
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Regular SR Parameters

2013
This chapter presents the classification and samples of all three types of ELF radio signals. The continuous signal is a composition of individual pulses from the global lightning activity. Signals of the second kind are the ELF-flashes: the intense pulses from the nearby thunderstorms occurring within 1,000–2,000 km distance from the observatory.
Alexander Nickolaenko, Masashi Hayakawa
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Selection of the Regularization Parameter

2016
The success of all currently available regularization techniques relies heavily on the proper choice of the regularization parameter. Although many regularization parameter selection methods (RPSMs) have been proposed, very few of them are used in engineering practice.
Mongi A. Abidi, Andrei V. Gribok, Joonki Paik   +2 more
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Regularization of Parameter Estimation

IFAC Proceedings Volumes, 1996
Abstract In recursive parameter estimation tasks, the least-squares estimates often tend to become badly behaving. This paper derives algorithms for regularising the parameter estimation process. In the derived algorithms, the excessive growth of the parameter variance is avoided in different ways. The first algoritlun defines an explicit upper limit
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Optimal Regularization Parameter Estimation for Regularized Discriminant Analysis

2011
Regularized linear discriminant analysis (RLDA) is a popular LDA-based method for dimension reduction. Despite its good performance, how to choose the parameter of the regularizer efficiently is still unanswered, especially for multi-class situation. In this paper, we first prove that regularizing LDA is equivalent to augmenting the training set in a ...
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A new choice rule for regularization parameters in Tikhonov regularization

Applicable Analysis, 2011
This article proposes and analyses a novel heuristic rule for choosing regularization parameters in Tikhonov regularization for inverse problems. The existence of solutions to the regularization parameter equation is shown, and a variational characterization of the inverse solution is provided.
Kazufumi Ito, Bangti Jin, Jun Zou
openaire   +1 more source

Properties of the Proximate Parameter Tuning Regularization Algorithm

Bulletin of Mathematical Biology, 2010
An important aspect of systems biology research is the so-called "reverse engineering" of cellular metabolic dynamics from measured input-output data. This allows researchers to estimate and validate both the pathway's structure as well as the kinetic constants.
Brown, Martin, He, Fei, Wilkinson, Stephen J.   +2 more
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Regularization of incorrectly posed problems and the choice of regularization parameter

USSR Computational Mathematics and Mathematical Physics, 1966
Let \(H\) be a Hilbert space. Let \(L\) be a self-adjoint, positive-definite linear operator, whose domain is \(D_L\), and denote by \(H_L\) the completion of \(D_L\) in the sense of the scalar product \((u,w)_{H_L} = (Lu,w) = (u,w)_L\), \((u,w\in D_L)\). Let \(A\) be a symmetric, positive linear operator, whose domain \(D_A\) contains \(H_L\). Suppose
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A comprehensive survey on regularization strategies in machine learning

Information Fusion, 2022
Yingjie Tian
exaly  

Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks

ACM Computing Surveys, 2022
Claudio Santos, João Paulo Papa
exaly