搜索三个目标

本文通过建立简洁而有效的搜索方法 ,证明了对于无穷多个n来说 ,三个目标的最优搜索问题的最小试验次数等于信息论下界 .同时也研究了上述问题的修正情形 ,证明了对于所有整数n来说 ,对应的最小试验次数或者等于信息论下界或者超过信息论下界 1次并且对于无穷多个区间 ,信息论下界均是可以达到的 .     

On a new stochastic global optimization algorithm based on censored observations

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.     

On the performance of peeling algorithms

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.     

数字调节器的切换方法分析

本文在分析数字调节器控制算法的基础上，重点分析了数字调节器正常运行时各运行状态间的切换方法。     

Winograd矩阵乘法算法用于任意阶矩阵时的一种新处理方法

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.     

一种利用绝对最小Lipshitz延拓的医学图像插值算法

提出一种基于最小Lipshitz延拓的图像插值半隐式算法,并用医学图像放大实验初步验证了算法的有效性.     

二叉分裂算法的随机路径长度

用泊松变换的方法研究了由二叉分裂算法所产生的随机树上的随机路径的长度,首次得到了关于其数学期望的确切表达式.在此基础上,对该期望的渐近性状进行了分析,证明了当被分裂的集合的大小n趋于无穷时,随机路径长度的期望具有log2n的阶.     

一个检测超流的早期淘汰算法

超流是网络中具有大量不同宿IP/源IP链接的源IP/宿IP.实时检测出高速网络（OC48、OC192等）中的超流对网络安全具有非常重要的意义.近年来已经有论文提出了不同超流检测算法,但是这些算法都没有考虑控制测量过程中超流缓存空间的大小.论文在超流检测过程中增加了早期淘汰功能,将超流缓存中链接数较少的记录提前淘汰,以便腾出空间用于存储新检测到的IP记录,实现对超流缓存资源的控制.论文最后还使用实际网络日志数据对算法进行验证,实验表明：早期淘汰算法可以使系统以更少的内存空间和测量资源检测超流信息.     

信用风险优化模型及其智能计算

采用模糊规划的方法,对模糊不确定环境下的信用风险度量和投资优化问题进行了模型的构建与仿真研究。基于具有自对偶性的可信性测度,提出了模糊条件在险价值作为信用风险度量,并构建了带有投资和收益等约束条件限制的信用风险最小化模型。其中,所考虑市场信用资产预期收益的可能性分布,用指数型模糊变量来刻画。最后,对该信用资产优化模型设计了智能算法,并进行了仿真分析。仿真结果表明,优化后的信用风险明显优于原始的信用风险。     

A new algorithm for fixed design regression and denoising

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.