基于一种特定混沌映射的跳频序列

使用一种简单的分段线性映射构造混沌跳频序列。用于跳频通信中取代传统的伪随机序列（PN序列），分析了此混沌序列的周期性。平衡性，汉明相关特性和线性间隔，最后给出了混沌序列的神经网络实现。仿真和实验结果表明，此序列具有较好的统计特性。应用于跳频多址通信中，可获得较好的抗干扰。抗截获能力。     

蒸发器泄漏原因分析及处理

对锦州石化分公司第三套催化裂化装置系统蒸发器泄漏原因进行了分析,并提出处理措施。收到较好的效果。     

心电图信号的频域分析

提出了一种简便有效的、由心电图（ECG）曲线提取QRS-T复合波的新方法，从而获得P波（当房颤未发生时）或f波（当房颤时）；利用功率谱、自相关、互相关等信号处理技术，对它进行了处理和分析，特别是，比较了未房颤时和发生房颤时的相关信息的显著差别。     

Pruning Redundant Alarm Correlation Patterns

1　ＩｎｔｒｏｄｕｃｔｉｏｎＴｈｅｓｔｉｃｋｉｎｇｐｏｉｎｔｏｆａｓｓｏｃｉａｔｉｏｎｒｕｌｅａｌｇｏｒｉｔｈｍｓｄｅｐｅｎｄｓｏｎｅｆｆｅｃｔｉｖｅｌｙｆｉｎｄｉｎｇａｌｌｃｏｒｒｅｌａｔｉｏｎｐａｔｔｅｒｎｓｔｈａｔｓａｔｉｓｆｙｖａｌｕｅｒｅｑｕｉｒｅｍｅｎｔｉｎｔｈｅｍａｇｎａｎｉｍｉｔｙｏｆｄａｔａ.Ｂｕｔｔｈｅａｌｇｏｒｉｔｈｍｓａｌｓｏｂｒｉｎｇａｎｅｇａｔｉｖｅｅｆ ｆｅｃｔ:ｔｈｅｎｕｍｂｅｒｏｆａｓｓｏｃｉａｔｉｏｎｒｕｌｅｓｉｓｖｅｒｙｌａｒｇｅ.Ａｌｓｏｉｎｆｏｒｍａｔｉｏｎ…     

广西水利工程管理单位亏损情况及扭亏措施

广西国营水利工程管理单位运行困难，亏损严重。为此对亏损情况及存在问题进行分析，提出相应措施及扭亏为盈的弥补思路。     

预应力钢筒混凝土管穿越地下管线的施工措施

文中介绍了预应力钢筒混凝土管的概念、优越性，并结合山西省万家寨联接段引黄工程的实际施工，总结出了穿越各种地下管线的施工经验。     

Introduction of a nonlinearity measure for principal component models

Although principal component analysis (PCA) is an important tool in standard multivariate data analysis, little interest has been devoted to assessing whether the underlying relationship within a given variable set can be described by a linear PCA model or whether nonlinear PCA must be utilized. This paper addresses this deficiency by introducing a nonlinearity measure for principal component models. The measure is based on the following two principles: (i) the range of recorded process operation is divided into smaller regions; and (ii) accuracy bounds are determined for the sum of the discarded eigenvalues. If this sum is within the accuracy bounds for each region, the process is assumed to be linear and vice versa. This procedure is automated through the use of cross-validation. Finally, the paper shows the utility of the new nonlinearity measure using two simulation studies and with data from an industrial melter process.     

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本文应用天然气中甲烷、乙烷的碳同位素,甲烷的氢同位素,汞含量及天然气成分等指标,探讨了四川盆地天然气成因分类;并结合地质情况对气源层进行了探讨。     

60Si2Mn合金钢发蓝泛红的分析研究

本文探讨了60Si2Mn合金钢发蓝原理，针对其膜层泛红问题，分析了热处理、表面前处理、发蓝及浸油等过程对发蓝质量的影响，由此采取了相应的技术措施，生产实践证明发蓝质量稳定，生产效率明显提高。     

A stochastic realization algorithm via block LQ decomposition in Hilbert space

A stochastic realization problem of a stationary stochastic process is re-visited, and a new stochastically balanced realization algorithm is derived in a Hilbert space generated by second-order stationary processes. The present algorithm computes a stochastically balanced realization by means of the singular value decomposition of a weighted block Hankel matrix derived by a “block LQ decomposition”. Extension to a stochastic subspace identification method explains how the proposed abstract algorithm is implemented in system identification.