面向鲁棒控制的l1中心估计算法及其误差界

分析了具有ｌ１误差的线性时不变系统的最不利情况的辨识问题，对系统假设的先验信息是未知系统的脉冲响应函数控制稳定，并且假设实验数据具有有界噪声干扰的一般输入响应样本，提出了中心估计算法，分析了其最不利情况的误差界限，所给算法和辨识结果是面向鲁棒控制的。     

信息安全与数学科学

随着互联网、计算机和通信技术的飞速发展,全球正步入信息化时代.每天有海量信息在互联网上传输,其中不乏有大量涉及政治、经济、金融及人们生活的敏感信息.     

高油玉米三种遗传效应综合利用模式研究

高油玉米三个遗传效应的综合利用生产模式是未来高油玉米生产的一种重要方式，而高油玉米雄性不育化研究又是实现三利用生产模式的关键技术环节，采用不育型高油玉米杂交种X超高油玉米杂交种的生产模式，可有效地提高高油玉米的含油量。     

论遗传因素对运动能力的影响

通过采用文献资料法探讨体操运动员形态、遗传和心理因素对运动能力的影响,为体操运动员选材提供参考依据。     

冒泡排序算法的改进

本文作者对传统的冒泡排序算法进行了时间复杂性分析，指出其效率不高的缺陷，提出了双向同时浮沉的改进方法，并编程予以实现。其效率较传统的冒泡排序算法有一定程度的提高．     

Improved genetic operator for genetic algorithm

The mutation operator has been seldom improved because ressearchers hardly suspect its ability to prevent genetic algorithm(GA) from converging prematurely.Due to its importance to GA,the authors of this paper study influence on the diversity of genes in the same locus,and point out that traditional mutation,to some extent,can result in premature convergence of genes(PCG) in the same locus.The above drawback of the traditional mutation operator causes the loss of critical alleles.Inspired by digital technique,we introduce two kinds of boolean operation into GA to develop a novel mutation operator and discuss its contribution of preventing the loss of critical alleles.The experimental results of function optimizatioin show that the improved mutation operator can effectively prevent premature convegence,and can provide a wide selection range of control parameters for GA.     

三对角方程组行处理法并行算法模拟

给出一个串行模拟在分布式存储ＭＩＭＤ一级３叉树机上求解任意三对角线性代数方程组的分布式迭代算法的Ｃ语言程序。     

A ciosed-loop algorithm to detect human face using color and reinforcement learning

A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color “like“ that of human skin are selected as candidates for human face. In the next stage, the candidates are matched with a face model and given an evaluation of the match degree by the matching module. And if the evaluation of the match result is too low, a reinforcement learning stage will start to search the best parameters of the skin-color selector. It has been tested using many photos of various ethnic groups under various lighting conditions, such as different light source, high light and shadow. And the experiment result proved that this algorithm is robust to the vary-ing lighting conditions and personal conditions.