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121.
We make a thorough non-covariant analysis of the derivation of the equation of motion for a charged particle, including radiation reaction, by means of a simple model for the charge: a dumbbell. This model and our method to expand retarded quantities, based on complex-variable theory, allow us to avoid some of the usual approximations, so we can show several features of the radiation reaction problem. 相似文献
122.
New concepts for the study of incompressible plane or axisymmetric flows are analysed by the stream tube method. Flows without eddies and pure vortex flows are considered in a transformed domain where the mapped streamlines are rectilinear or circular. The transformation between the physical domain and the computational domain is an unknown of the problem. In order to solve the non-linear set of relevant equations, we present a new algorithm based on a trust region technique which is effective for non-convex optimization problems. Experimental results show that the new algorithm is more robust compared to the Newton-Raphson method. 相似文献
123.
首先利用Lagrange对偶 ,将球约束凸二次规划问题转化为无约束优化问题 ,然后运用单纯形法求解无约束优化问题 ,从而获得原问题的最优解 相似文献
124.
125.
Fabio Schoen 《Journal of Global Optimization》1994,4(1):17-35
In this paper a new algorithm is proposed for global optimization problems. The main idea is that of modifying a standard clustering approach by sequentially sampling the objective function while adaptively deciding an appropriate sample size. Theoretical as well as computational results are presented. 相似文献
126.
The peeling of a d-dimensional set of points is usually performed with successive calls to a convex hull algorithm; the optimal worst-case convex hull algorithm, known to have an O(n˙ Log (n)) execution time, may give an O(n˙n˙ Log (n)) to peel all the set; an O(n˙n) convex hull algorithm, m being the number of extremal points, is shown to peel every set with an O(n-n) time, and proved to be optimal; an implementation of this algorithm is given for planar sets and spatial sets, but the latter give only an approximate O(n˙n) performance. 相似文献
127.
Winograd矩阵乘法算法用于任意阶矩阵时的一种新处理方法 总被引:3,自引:0,他引:3
摘要t矩阵乘法StraSsen算法及其变形winograd算法用分而治之的方法把矩阵乘法时间复杂性由传统的D(n。)改进到0(佗kg。n.但是对于奇数阶矩阵,在划分子矩阵时,要作特殊处理才能继续使用此算法.本文提出了一种非等阶“十”字架划分方法,可以最少化填零,最大化性能,使得奇数阶矩阵乘法的时间复杂性更加接近偶数阶矩阵乘法的效果.计算实例显示该方法是有效的. 相似文献
128.
In this paper, we present a new algorithm to estimate a regression function in a fixed design regression model, by piecewise
(standard and trigonometric) polynomials computed with an automatic choice of the knots of the subdivision and of the degrees
of the polynomials on each sub-interval. First we give the theoretical background underlying the method: the theoretical performances
of our penalized least-squares estimator are based on non-asymptotic evaluations of a mean-square type risk. Then we explain
how the algorithm is built and possibly accelerated (to face the case when the number of observations is great), how the penalty
term is chosen and why it contains some constants requiring an empirical calibration. Lastly, a comparison with some well-known
or recent wavelet methods is made: this brings out that our algorithm behaves in a very competitive way in term of denoising
and of compression. 相似文献
129.
130.
We address the problem of computing homotopic shortest paths in the presence of obstacles in the plane. Problems on homotopy of paths received attention very recently [Cabello et al., in: Proc. 18th Annu. ACM Sympos. Comput. Geom., 2002, pp. 160–169; Efrat et al., in: Proc. 10th Annu. European Sympos. Algorithms, 2002, pp. 411–423]. We present two output-sensitive algorithms, for simple paths and non-simple paths. The algorithm for simple paths improves the previous algorithm [Efrat et al., in: Proc. 10th Annu. European Sympos. Algorithms, 2002, pp. 411–423]. The algorithm for non-simple paths achieves O(log2n) time per output vertex which is an improvement by a factor of O(n/log2n) of the previous algorithm [Hershberger, Snoeyink, Comput. Geom. Theory Appl. 4 (1994) 63–98], where n is the number of obstacles. The running time has an overhead O(n2+) for any positive constant . In the case k<n2+, where k is the total size of the input and output, we improve the running to O((n+k+(nk)2/3)logO(1)n). 相似文献