一种改进的LMS自适应算法研究

传统的LMS算法的精度不高,收敛速度慢,并且跟踪性能不好.本论文主要研究了一种改进型的变步长的LMS自适应算法NLMS,并基于MATLAB仿真软件设计完成了一种改进型的NLMS自适应滤波器,对该算法进行仿真验证.结果表明:该改进型的自适应算法NLMS平均误差更小,精度更高.     

一种并行微粒群的改进算法

在对标准微粒群算法（PSO）分析的基础上,提出了一种并行微粒群算法（PPSO）。文章详细介绍了该并行算法的流程,它改变了原来子种群之间周期性的通讯,而采用即时更新最优值的方法。仿真结果表明,PPSO在收敛速度和达标率方面有显著的优越性。     

输油管布置优化模型与算法实现

在直角坐标系中建立了输油管铺设费用与管道节点坐标的函数模型,并针对两炼油厂到铁路线的距离和两炼油厂间距离的各种不同情形,设计出铺设管道的最佳路线;在管线铺设划分区域时,建立了非线性优化模型,并利用共轭梯度法编程求解。     

g-r循环矩阵求逆的Euclid算法

利用交换环的同构理论,结合多项式最大公因式的Euclid算法,给出了求g-r循环矩阵逆矩阵的一种新算法,并结合数值例子给出了该算法的应用.     

求解C-A指派问题的差值法

C-A指派问题是实际分配任务数不仅小于总任务数,而且小于总人数,并且规定一人一事和一事一人,是一类非标准形式的指派问题.鉴于用匈牙利法求解这类非标准形式C-A指派问题的计算复杂性,给出一种新的算法,该算法首先用差值法找出可行解,然后通过行、列调整找到最优解.     

基于传感器网络的港口拖车调度系统设计

港口拖车调度管理系统设计对智能控制能力要求很高,是一个经典问题。由于拖车在港口中完全是动态的,因此采用基于无线传感器网络的定位算法,能够很好地解决拖车动态定位问题。在采用基于无线传感器网络的定位算法的基础上,研究基于遗传算法的拖车调度策略并设计港口拖车管理系统,具有较高的实践意义和实用价值。     

高职高专《数据结构》课程教学实践探究

在高等职业院校计算机应用技术专业所开设的多门专业课中,《数据结构》是一门非常重要的核心课程,也是一门比较难学的理论基础课程．因此,有必要对该课程的教学方法、教学过程进行深入探讨．     

一类三阶非线性系统的李雅普诺夫函数的构造

本文用能量度量算法构造了一类三阶非线性系统的李雅普诺夫函数,从而研究了它们零解的全局渐近稳定性．     

A Systematic Evaluation and Comparison Between Exploratory Structural Equation Modeling and Bayesian Structural Equation Modeling

In this study, we contrast two competing approaches, not previously compared, that balance the rigor of CFA/SEM with the flexibility to fit realistically complex data. Exploratory SEM (ESEM) is claimed to provide an optimal compromise between EFA and CFA/SEM. Alternatively, a family of three Bayesian SEMs (BSEMs) replace fixed-zero estimates with informative, small-variance priors for different subsets of parameters: cross-loadings (CL), residual covariances (RC), or CLs and RCs (CLRC). In Study 1, using three simulation studies, results showed that (1) BSEM-CL performed more closely to ESEM; (2) BSEM-CLRC did not provide more accurate model estimation compared with BSEM-CL; (3) BSEM-RC provided unstable estimation; and (4) different specifications of targeted values in ESEM and informative priors in BSEM have significant impacts on model estimation. The real data analysis (Study 2) showed that the differences in estimation between different models were largely consistent with those in Study1 but somewhat smaller.     

Arguments around weighting the first year in degree classification algorithms

The UK’s HE system is mired in public debate around ‘grade inflation’, and there is substantial pressure to address the perceived devaluation of degrees through blunt policy measures such as modifying classification algorithms. Policy-makers should be aware of the impact of their actions upon students’ learning; this article frames some of the neglected pedagogical arguments in concise syllogistic forms, focusing particularly on the issues around weighting the first year of a traditional UK bachelor’s degree classification algorithm.