The Experts below are selected from a list of 42 Experts worldwide ranked by ideXlab platform

I L Andronov - One of the best experts on this subject based on the ideXlab platform.

  • phenomenological modeling of the light Curves of algol type eclipsing binary stars
    Astrophysics, 2012
    Co-Authors: I L Andronov
    Abstract:

    We propose a special class of functions for mathematical modeling of periodic signals of a special type with a nonuniform distribution of the arguments. This method has been developed for determining the phenomenological characteristics of light Curves required for listing in the “General Catalog of Variable Stars” (GCVS) and other data bases. For eclipsing binary stars with smooth light Curves (types EB and EW) a trigonometric polynomial of optimal degree in a complete or symmetric form is recommended. For eclipsing binary systems with relatively narrow minima, approximating the light Curves by a class of nonpolynomial spline functions is statistically optimal. A combination of a second order trigonometric polynomial (TP2, which describes “reflection”, ellipsoidal” and “spotting” effects) and localized contributions of the minima (parametrized with respect to depth and profile separately for the primary and secondary minima) is used. This approach is characterized by a statistical accuracy of the Smoothing Curve that is a factor of ~1.5-2 times better than for a trigonometric polynomial of statistically optimal degree, and by the absence of false “waves” in the light Curve associated with the Gibbs effect. Besides finding the width of the minimum, which cannot be determined using a trigonometric polynomial approximation, this method can be used to determine its depth with better accuracy, and to separate the effects of the eclipse and the part outside the eclipse. For multicolor observations, the improved accuracy of the Smoothing Curve for each filter makes it possible to obtain more accurate plots of the variation in the color index. The efficiency of the proposed method increases as the width of the eclipse becomes smaller. This method supplements the trigonometric polynomial approximation. The method, referred to as the NAV (New Algol Variable) method, is illustrated by applying it to the eclipsing binary systems VSX J022427.8-104034=USNO-B1.0 0793-0023471 and BM UMa. An alternative “double period” model is examined for VSX J022427.8-104034.

  • phenomenological modeling of the light Curves of algol type eclipsing binary stars
    arXiv: Solar and Stellar Astrophysics, 2012
    Co-Authors: I L Andronov
    Abstract:

    We introduce a special class of functions for mathematical modeling of periodic signals of special shape with irregularly spaced arguments. This method was developed for determination of phenomenological characteristics of the light Curves, which are necessary for registration in the "General Catalogue of Variable Stars" and other databases. For eclipsing binary stars with smooth light Curves - of types EB and EW - it is recommended a trigonometric polynomial of optimal degree in a complete or symmetric form. For eclipsing binary systems with narrow minima (EA-type), statistically optimal is an approximation in a class of non-polynomial spline functions. It is used a combination of the second-order trigonometric polynomial (TP2, what describes effects of "reflection", "ellipsoidality" and "spotness") and localized contributions of minima (parametrized in depth and profile separately for primary and secondary minima). Such an approach is characterized by a statistical accuracy of the Smoothing Curve, which is up to ~1.5-2 times better than the trigonometric polynomial of statistically optimal degree, and the absence of false "waves" in the light Curve associated with the effect of Gibbs. In addition to the minimum width, which can not be determined by a trigonometric polynomial approximation, the method allows to determine with better accuracy its depth, as well as to separate the effects of the eclipse and out-of-eclipse parts. For multi-color observations, improving the accuracy of the Smoothing of the Curve in each filter will allow to obtain with better accuracy the Curves of the color index variations. Effectivity of the proposed method increases with decreasing eclipse depth. The method called NAV ("New Algol Variable"), was applied to eclipsing binary systems VSX J022427.8-104034=USNO-B1.0 0793-0023471 and BM UMa. For VSX0224, an alternative model of "double period" is discussed.

Ranjay Hazra - One of the best experts on this subject based on the ideXlab platform.

  • a new algorithm of image segmentation using Curve fitting based higher order polynomial Smoothing
    Optik, 2016
    Co-Authors: Soumen Biswas, Dibyendu Ghoshal, Ranjay Hazra
    Abstract:

    Abstract Image segmentation plays an efficient role in image analysis which discriminates the objects from its background in pixel level. In accordance with the application, image segmentation is widely spread over various fields. The motivation of this paper is to focus on the application of statistical analysis in image segmentation. In this paper, we have incorporated Curve fitting technique on an image to acquire the segmented image thereby extracting information from the images. By using higher order polynomial Smoothing Curve, appropriate result is obtained from detection of the object. Furthermore, we have calculated the image quality metrics which is a method of statistical analysis to get the quality measures and performance analysis of images. Extensive experiments show that the proposed approach outperforms the existing approaches namely histogram based segmentation, edge detection based segmentation, Ostu’s segmentation and Watershed segmentation. The outcome is derived by applying the proposed algorithm and results obtained are appreciable.

Soumen Biswas - One of the best experts on this subject based on the ideXlab platform.

  • a new algorithm of image segmentation using Curve fitting based higher order polynomial Smoothing
    Optik, 2016
    Co-Authors: Soumen Biswas, Dibyendu Ghoshal, Ranjay Hazra
    Abstract:

    Abstract Image segmentation plays an efficient role in image analysis which discriminates the objects from its background in pixel level. In accordance with the application, image segmentation is widely spread over various fields. The motivation of this paper is to focus on the application of statistical analysis in image segmentation. In this paper, we have incorporated Curve fitting technique on an image to acquire the segmented image thereby extracting information from the images. By using higher order polynomial Smoothing Curve, appropriate result is obtained from detection of the object. Furthermore, we have calculated the image quality metrics which is a method of statistical analysis to get the quality measures and performance analysis of images. Extensive experiments show that the proposed approach outperforms the existing approaches namely histogram based segmentation, edge detection based segmentation, Ostu’s segmentation and Watershed segmentation. The outcome is derived by applying the proposed algorithm and results obtained are appreciable.

Jing Yang - One of the best experts on this subject based on the ideXlab platform.

  • a two step method for interpolating interval data based on cubic hermite polynomial models
    Applied Mathematical Modelling, 2020
    Co-Authors: Xuli Han, Jing Yang
    Abstract:

    Abstract We propose a two-step modelling method to build a Smoothing Curve or surface representation model for interpolating given interval data. Due to the difficulties of building interpolation models with explicit expressions directly on given multivariable interval data in existing studies, the first step is about building a cubic Hermite spline model to construct a Smoothing piecewise parametric Curve of C k ( k = 1 , 2 ) continuity to show the implicit relationship between variables. Thereinto, we formulate the Hermite spline model as a finite convex optimization problem. Then in the second step, sample points are taken from the optimal parametric spline Curve in the first step as the interpolation points to establish the explicit expressions and illustrate the direct relationship between variables. Some numerical examples are provided to compare with other interpolation methods and show the feasibility and advantages of the proposed method.

Deng Shuguang - One of the best experts on this subject based on the ideXlab platform.