基于重量分析的OBDD变量排序算法

有序的二叉判决图（ＯＢＤＤ）是布尔表达式的一种有效表示方法，但它的体积对变量排序具有较强的依赖性。本文提出一种电路结构图，并在此基础上定义了原始输入重量和节点重量等参数，并建立了用重量分析来指导的ＯＢＤＤ变量排序算法。由于从考虑变量对输出函数的影响出发与从考虑ＯＢＤＤ节点共享性出发对变量排序的要求不同，本文分别设计了两类算法。实验结果表明，本文对大多数标准电路变量排序的效果都优于国际上的同类算法，     

燃煤电厂融合多信号光纤火焰检测器的开发研究

介绍一种新型光纤燃煤炉火焰检测器，阐述其系统组成及特点，并提出了基于模糊推理的多信号融合处理方法。     

A numerical model for the dissolution of spherical particles in binary alloys under mixed mode control

A general numerical model is described for the dissolution kinetics of spherical particles in binary systems for any combination of first order reactions at the particle-matrix interface and long distance diffusion within the matrix. The model is applicable to both finite and infinite media and handles both complete and partial particle dissolution. It is shown that interfacial reactions can have a strong effect on the dissolution kinetics, the solute concentration at the particle-matrix interface and the solute concentration profile in the matrix.     

Fixed collision rate back-off scheme for collision resolution in wireless networks

This investigation proposes a fixed collision rate (FCR) back-off algorithm for wireless networks. The proposed scheme takes advantage of the central unit (CU) in a wireless network to broadcast a common back-off window size to all the users, significantly alleviating the unfairness of bandwidth utilization in conventional binary exponential back-off (BEB) algorithms. It is shown that, when maximum throughput is achieved, collision rate is almost a constant for any traffic load. In the operation of the FCR, the CU dynamically adjusts the back-off window size to keep the collision rate at a constant level for maximum throughput. Simulation results demonstrate that the unfairness of bandwidth utilization in the BEB is significantly lessened and the throughput can be maintained at e^-1≈0.368 when the number of users approaches infinity. The capture effect even further improves system performance.     

Vote counting measures for ensemble classifiers

Various measures, such as Margin and Bias/Variance, have been proposed with the aim of gaining a better understanding of why Multiple Classifier Systems (MCS) perform as well as they do. While these measures provide different perspectives for MCS analysis, it is not clear how to use them for MCS design. In this paper a different measure based on a spectral representation is proposed for two-class problems. It incorporates terms representing positive and negative correlation of pairs of training patterns with respect to class labels. Experiments employing MLP base classifiers, in which parameters are fixed but systematically varied, demonstrate the sensitivity of the proposed measure to base classifier complexity.     

二元光栅照明研究

采用部分相干成象理论对二元光机照明进行了较为详细的研究。分析了二元光栅照明对分辨力，焦，照明能量和照明均匀性的影响，并通过实验研究验证了二元光栅对分辨力和焦深有较大程度的提高，同时能量损失不大。     

The vulnerability of geometric sequences based on fields of odd characteristic

A new method of cryptologic attack on binary sequences is given, using their linear complexities relative to odd prime numbers. We show that, relative to a particular prime number p, the linear complexity of a binary geometric sequence is low. It is also shown that the prime p can be determined with high probability by a randomized algorithm if a number of bits much smaller than the linear complexity is known. This determination is made by exploiting the imbalance in the number of zeros and ones in the sequences in question, and uses a new statistical measure, the partial imbalance.This project was sponsored by the National Security Agency under Grant No. MDA904-91-H-0012. The United States Government is authorized to reproduce and distribute reprints notwithstanding any copyright notation hereon.     

Improving Neural Networks for Mechanism Kinematic Chain Isomorphism Identification

Detection of isomorphism among kinematic chains is essential in mechanical design, but difficult and computationally expensive. It has been shown that both traditional methods and previously presented neural networks still have a lot to be desired in aspects such as simplifying procedure of identification and adapting automatic computation. Therefore, a new algorithm based on a competitive Hopfield network is developed for automatic computation in the kinematic chain isomorphism problem. The neural approach provides directly interpretable solutions and does not demand tuning of parameters. We have tested the algorithm by solving problems reported in the recent mechanical literature. Simulation results show the effectiveness of the network that rapidly identifies isomorphic kinematic chains.