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    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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