Radon transform is a mathematical tool widely applied in various domains, including biophysics and computer tomography. Previously, it was discovered that applying the Radon transform to a binary image comprising circle forms resulted in discontinuity. As a result, the line detection approach based on it became discontinued. The d-Radon transform is a modified version of the Radon transform that is presented as a solution to this problem. The properties of the circle cause the Radon transform to be discontinuous. This work extends this finding by looking into the Radon transform's regularity property and a proposed modification to a convex shape. We discovered that regularity in the Radon space is determined by the regularity of the shape's point. This leads to the continuity condition for the line detection method.
A compound Ornstein-Uhlenbeck process is applied to create a model that can calculate the dividend yield represented in a sample case of Stock Exchange of Thailand index in which earning yield is randomly determined. Parameter estimations are made through the use of least-square technique, while the outcomes are deduced from the Euler-Maruyama method. We use numerical simulation to determine the effectiveness of the models, comparing our newly proposed model with the previous models. The actual dividend yield data is applied for comparison. The results show that our model performs best among the three models being compared.MSC: 91G80; 91G60; 65C30; 82C80
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