部分线性模型的渐近性

考虑Ｙｉ＝Ｘ＾ｔｉβ＋ｇ（ｔｉ）＋εｉ，１≤ｉ≤，忱里Ｘｉ是一固定设计点列，ｔｉ是独立同分布随机变量并且服从［０，１］上均匀分布。     

负反馈放大电路的网络参数分析法

利用双口网络参数分析负反馈放大电路的方法．通过对典型电流串联负反馈电路的z参数分析，得到了与其它分析方法相同的结果．分析过程简洁，物理概念清晰．     

关于正线性算子的Woronovskaja－型定理

本文对可用正线性算子｛Ｌ＿ｎ｝逼近的满足一定的可微性条件的函数类给出Ｗｏｒｏｎｏｖｓｋａｊａ——型定理，并将所得结果应用到几个特殊的正线性算子上，从而基本上解决了这些正线性算子的Ｗｏｒｏｎｏｖｓｋａｊａ——型问题。     

用网络拓扑分析含受控源电路的一种系统方法

通过３个实例分析，阐明用网络拓扑分析含受控源电路的一种系统方法。     

现代控制论中能控性定理证明方法之比较

就目前在现代控制论科教书中关于战性定常系统的状态能控性的几种常用证明方法提出异议，阐述看法并进行比较。     

关于互联网管理与国家安全的思考

从国家安全和讲政治的角度以及目前互联网管理现状出发，分析了加强互联网管理的必要性和重要性，在此基础上探讨了公安机关参与互联网管理应注意处理的关系及管理策略．     

Samples Selection for Artificial Neural Network Training in Preliminary Structural Design

An artificial neural network (ANN) is applied in the preliminary structural design of reticulated shells. Major efforts are made to enhance the generalization ability of networks through well-selected training samples. Number-theoretic methods (NTMs) are adopted to generate samples with low discrepancy, i.e.uniformly scattered in the domain, where discrepancy is a quantitative measurement of the uniformity. The discrepancy of the NTM-based sample set is 1/6-1/7 that of samples with equal spacing. In a case study,networks trained by NTM-based samples are compared with those trained by equal-spaced samples in generalizing performance. The results show that both the computational precision and stability of the former ANNs are more satisfactory than those of the latter. It is concluded that the flexibility of ANNs in generalizing can be effectively increased by use of uniformly distributed training samples rather than simply piling data.More reliable uniformity should be obtained, however, through NTMs instead of equal-spaced samples.     

Mechanism and Defense on Malicious Code

With the explosive growth of network applications, the threat of the malicious code against network security becomes increasingly serious. In this paper we explore the mechanism of the malicious code by giving an attack model of the maliciouscode, and discuss the critical techniques of implementation and prevention against the malicious code. The remaining problems and emerging trends in this area are also addressed in the paper.     

人工神经网络紫外分光光度法同时测定苯和甲苯

应用三层ANN_BP网络解析苯和甲苯的吸收光谱 ,不经分离 ,用紫外分光光度法同时测定苯和甲苯 .使用改进的BP算法 ,避免了神经网络学习过程中可能产生的麻痹现象 ,提出了目标向量的简单变换方法及便于网络参数选择的收敛评价函数 .实验验证了方法的有效性 ,同时表明 ,苯在 0 - 72 0mg/L和甲苯在 0 - 84 0mg/L范围内服从比尔定律