参考信号频率自调整的数字相敏检波器算法的研究

本文提出了一种不需要外接同频参考信号的数字相敏检波器算法。该算法首先提取计算机产生的参考信号与被测信号频率的差值，然后根据该差值调整参考信号的频率直到满足要求。本文还讨论了数字相敏检波器的幅频特性，仿真试验表明理论分析与实际结果是一致的。该算法可以用于同频参考信号不能获得时正弦信号的幅度和相位测量。     

Rectilinear steiner tree heuristics and minimum spanning tree algorithms using geographic nearest neighbors

We study the application of the geographic nearest neighbor approach to two problems. The first problem is the construction of an approximately minimum length rectilinear Steiner tree for a set ofn points in the plane. For this problem, we introduce a variation of a subgraph of sizeO(n) used by YaO [31] for constructing minimum spanning trees. Using this subgraph, we improve the running times of the heuristics discussed by Bern [6] fromO(n ² log n) toO(n log² n). The second problem is the construction of a rectilinear minimum spanning tree for a set ofn noncrossing line segments in the plane. We present an optimalO(n logn) algorithm for this problem. The rectilinear minimum spanning tree for a set of points can thus be computed optimally without using the Voronoi diagram. This algorithm can also be extended to obtain a rectilinear minimum spanning tree for a set of nonintersecting simple polygons.The results in this paper are a part of Y. C. Yee's Ph.D. thesis done at SUNY at Albany. He was supported in part by NSF Grants IRI-8703430 and CCR-8805782. S. S. Ravi was supported in part by NSF Grants DCI-86-03318 and CCR-89-05296.     

Software for dynamic reconfigurable order picking systems

This paper describes an approach, conceptual framework, and software architecture for dynamic reconfiguration of the order picking system. The research and development project was sponsored by the Material Handling Research Center (MHRC), a National Science Foundation sponsored Cooperative Industry/University Research Center. The storage configuration is assumed to be an in-the-aisle order picking system in which stockkeeping units (SKUs) can occupy variable capacity storage locations and stock-splitting is allowed among zones (clusters). The product mix may include multiple product families with different life cycles, correlated demand within families and commonality of demand across families.     

Second-law-based thermodynamic analysis of two-stage and mechanical-subcooling refrigeration cycles

Thermodynamic analysis of HFC-134a vapor-compression refrigeration cycles is investigated by both the first and second laws of thermodynamics. Second-law analysis is carried out for both two-stage and mechanical-subcooling refrigeration cycles. The analysis is performed on each of the system components to determine their individual contribution to the overall system irreversible losses. It is found that most of the losses are due to a low compressor efficiency. Irreversibilities of expansion valves and condenser are also significant. In addition, it is shown that the optimum inter-stage pressure for two-stage and mechanical-subcooling refrigeration systems is very close to the saturation pressure corresponding to the arithmetic mean of the refrigerant condensation and evaporation temperatures. These results are compared with the existing practice in the industry. Furthermore, theoretical results of a two-stage refrigeration system performance are also compared with experimental values for a CFC-22 system.     

基于Apriori算法改进的关联规则提取算法

通过对Apriori算法的基本思想和性能的研究分析，认为Apriori算法存在一些不足。并且根据这些不足提出了相应的改进算法对Apriori算法进行优化，从而得到一种改进的Apriori算法，与原算法相比运算效率大大提高。     

宽线性共轭梯度算法及其在盲多用户检测中的应用

本文提出了一种宽线性共轭梯度算法，分析了算法在均值意义下的收敛性，并给出了算法稳定条件。仿真表明，新算法应用于码分多址系统多址干扰抑制时的性能优于Yin（2003）及Schober（2004）所提出的算法。     

A New Algorithm for the Elimination of Common Subexpressions in Hardware Implementation of Digital Filters by Using Genetic Programming

A new algorithm based on Genetic Programming (GP) for the problem of optimization of Multiple constant Multiplication (MCM) by Common Subexpression Elimination(CSE) is developed. This method is used for hardware optimization for DSP systems. A solution based on Genetic Programming is shown in this paper. The performance of the technique is demonstrated in one- and multi-dimensional digital filters with constant coefficients.     

连铸温度场数值模拟及冷却水参数优化

由于用实验方法来研究工艺参数对铸坯温度场的影响较困难,故而提出了一种在冶金冷却条件指导下的启发式GA(遗传算法)数值模拟优化方法,为优化工艺参数提供了理论依据,并在优化基础上采用MIMO(多输入多输出)系统PID(比例积分微分)控制器实现了二冷段配水的优化控制,改善了铸坯的质量.     

Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction

This paper introduces and evaluates a new class of knowledge model, the recursive Bayesian multinet (RBMN), which encodes the joint probability distribution of a given database. RBMNs extend Bayesian networks (BNs) as well as partitional clustering systems. Briefly, a RBMN is a decision tree with component BNs at the leaves. A RBMN is learnt using a greedy, heuristic approach akin to that used by many supervised decision tree learners, but where BNs are learnt at leaves using constructive induction. A key idea is to treat expected data as real data. This allows us to complete the database and to take advantage of a closed form for the marginal likelihood of the expected complete data that factorizes into separate marginal likelihoods for each family (a node and its parents). Our approach is evaluated on synthetic and real-world databases.