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Wyszukujesz frazę "regularization" wg kryterium: Temat


Wyświetlanie 1-5 z 5
Tytuł:
Regularization parameter selection in discrete ill-posed problems—The use of the U-curve
Autorzy:
Krawczyk-Stańdo, D.
Rudnicki, M.
Powiązania:
https://bibliotekanauki.pl/articles/929617.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
problem niewłaściwie postawiony
regularyzacja Tichonowa
parametr regularyzacji
ill-posed problems
Tikhonov regularization
regularization parameter
L-curve
U-curve
Opis:
To obtain smooth solutions to ill-posed problems, the standard Tikhonov regularization method is most often used. For the practical choice of the regularization parameter \alfa we can then employ the well-known L-curve criterion, based on the L-curve which is a plot of the norm of the regularized solution versus the norm of the corresponding residual for all valid regularization parameters. This paper proposes a new criterion for choosing the regularization parameter \alfa, based on the so-called U-curve. A comparison of the two methods made on numerical examples is additionally included.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2007, 17, 2; 157-164
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adaptation of the Regularization Parameters in the Nm-Delta Networks
Autorzy:
Gołąbek, P.
Kosiński, W.
Powiązania:
https://bibliotekanauki.pl/articles/911150.pdf
Data publikacji:
2000
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
regularyzacja
Levenberg-Marquardt
NM-Delta
M-Delta
regularization
quasi-Newton
Opis:
The paper describes an application of regularization techniques to an automatic choice of parameters driving the learning process in the NM-Delta neural network architecture. The heterogeneous learning algorithm is identified as very similar to the Levenberg-Marquardt method but with a considerably smaller computational cost and different justification of parameter selection. The performance of the modified algorithm proves to be comparable with that of the Levenberg-Marquardt.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2000, 10, 4; 779-790
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On a regularization method for variational inequalities with P0 mappings
Autorzy:
Konnov, I.
Mazurkevich, E.
Ali, M.
Powiązania:
https://bibliotekanauki.pl/articles/908486.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
nierówność wariacyjna
metoda regularyzacji
variational inequalitie
partial regularization approach
P0-mappings
Opis:
We consider partial Browder-Tikhonov regularization techniques for variational inequality problems with P0 cost mappings and box-constrained feasible sets. We present classes of economic equilibrium problems which satisfy such assumptions and propose a regularization method for these problems.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2005, 15, 1; 35-44
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Tikhonov regularization and constrained quadratic programming for magnetic coil design problems
Autorzy:
Garda, B.
Galias, Z.
Powiązania:
https://bibliotekanauki.pl/articles/330150.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
coil design problem
constrained quadratic programming
Tikhonov regularization
projektowanie cewki
programowanie kwadratowe
regularyzacja Tikhonova
Opis:
In this work, the problem of coil design is studied. It is assumed that the structure of the coil is known (i.e., the positions of simple circular coils are fixed) and the problem is to find current distribution to obtain the required magnetic field in a given region. The unconstrained version of the problem (arbitrary currents are allowed) can be formulated as a Least-SQuares (LSQ) problem. However, the results obtained by solving the LSQ problem are usually useless from the application point of view. Moreover, for higher dimensions the problem is ill-conditioned. To overcome these difficulties, a regularization term is sometimes added to the cost function, in order to make the solution smoother. The regularization technique, however, produces suboptimal solutions. In this work, we propose to solve the problem under study using the constrained Quadratic Programming (QP) method. The methods are compared in terms of the quality of the magnetic field obtained, and the power of the designed coil. Several 1D and 2D examples are considered. It is shown that for the same value of the maximum current the QP method provides solutions with a higher quality magnetic field than the regularization method.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 2; 249-257
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A well-posed multiscale regularization scheme for digital image denoising
Autorzy:
Prasath, V. B. S.
Powiązania:
https://bibliotekanauki.pl/articles/930148.pdf
Data publikacji:
2011
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
odtworzenie obrazu
sterowanie adaptacyjne
regularyzacja
image restoration
edge-preserving
regularization
normalized local variance
adaptive parameter
Opis:
We propose an edge adaptive digital image denoising and restoration scheme based on space dependent regularization. Traditional gradient based schemes use an edge map computed from gradients alone to drive the regularization. This may lead to the oversmoothing of the input image, and noise along edges can be amplified. To avoid these drawbacks, we make use of a multiscale descriptor given by a contextual edge detector obtained from local variances. Using a smooth transition from the computed edges, the proposed scheme removes noise in flat regions and preserves edges without oscillations. By incorporating a space dependent adaptive regularization parameter, image smoothing is driven along probable edges and not across them. The well-posedness of the corresponding minimization problem is proved in the space of functions of bounded variation. The corresponding gradient descent scheme is implemented and further numerical results illustrate the advantages of using the adaptive parameter in the regularization scheme. Compared with similar edge preserving regularization schemes, the proposed adaptive weight based scheme provides a better multiscale edge map, which in turn produces better restoration.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2011, 21, 4; 769-777
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-5 z 5

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