Papers by Keyword: B-Spline Function

Abstract: A novel controller based on the fuzzy B-spline neural network is presented, which combines the advantages of qualitative defining capability of fuzzy logic, quantitative learning ability of neural networks and excellent local controlling ability of B-spline basis functions, which are being used as fuzzy functions. A hybrid learning algorithm of the controller is proposed as well. The results show that it is feasible to design the fuzzy neural network control of autonomous underwater vehicle by the hybrid learning algorithm.

Abstract: In order to meet the needs of boundary conditions and eliminate the residual of governing equations, the weighted residuals method is combined with least squares method solve the nonlinear bending problem of symmetrically angle-lay orthotropic laminated composite plate, and the double fifth B-spline is taken as trial function to seek an efficient method for large deflection of plate. The analytical solution of bending problems of symmetrically angle-lay orthotropic laminated composite plate with clamped boundary conditions is obtained by using the weighted residual method. The results from the present method are in good agreement with those derived from other methods, and the present method has the advantages of simple principle, high calculation efficiency and easy to satisfy boundary conditions as well, superiority to finite element method. In addition, the design of computer program is simple and it is easy to be programmed.

Abstract: B-spline method plays an important role in data interpolating, fitting and smoothing. Through analyzing the computed path of the de Boor-Cox algorithm, a new method for calculating B-spline function is given based on the vector extending operation. The proposed method has a parallel computing architecture and is suitable to realize by computers. Compared with the de Boor-Cox algorithm, the proposed method can improve computing efficiency by (2k+1) times in the task of calculating all nonzero values of k-degree B-spine functions. As an application in B-spline curve fitting, it shows that the proposed algorithm can reduce the computing efforts obviously.

Abstract: A material testing methodology is investigated in line with non-invasive manner using XRay CT images for characterizing biological tissues. Three-dimensional digital image volumes are generated for initial and loaded states. Tentative displacement field is represented by basis function of B-spline. Unknown parameters included in the functions are identified through an inverse problem minimizing error in terms of pixel intensity between actual deformed image volume and virtual one according to the tentative displacement field of B-spline. A constraint of incompressibility affects well for stable and prompt solution search. The proposed methodology is demonstrated in identification problem of three-dimensional displacement field by using an experimental data of compressive specimen.