一种基于多级查找表的高效Huffman编码算法

本文研究了适用于数字信号处理器的一种高效的Huffman编码算法的问题.利用多级查找表建立规则,并将Huffman树分割为若干子树且为分割后的所有子树建立一个统一的查找表的方法,获得了可用较小的查找表来存储Huffman树且能对比特流进行快速解码的结果.     

Kalman particle swarm optimized polynomials for data classification

Data classification is an important area of data mining. Several well known techniques such as decision tree, neural network, etc. are available for this task. In this paper we propose a Kalman particle swarm optimized (KPSO) polynomial equation for classification for several well known data sets. Our proposed method is derived from some of the findings of the valuable information like number of terms, number and combination of features in each term, degree of the polynomial equation etc. of our earlier work on data classification using polynomial neural network. The KPSO optimizes these polynomial equations with a faster convergence speed unlike PSO. The polynomial equation that gives the best performance is considered as the model for classification. Our simulation result shows that the proposed approach is able to give competitive classification accuracy compared to PNN in many datasets.     

Recursive state estimation for hybrid systems

The paper deals with recursive state estimation for hybrid systems. An unobservable state of such systems is changed both in a continuous and a discrete way. Fast and efficient online estimation of hybrid system state is desired in many application areas. The presented paper proposes to look at this problem via Bayesian filtering in the factorized (decomposed) form. General recursive solution is proposed as the probability density function, updated entry-wise. The paper summarizes general factorized filter specialized for (i) normal state-space models; (ii) multinomial state-space models with discrete observations; and (iii) hybrid systems. Illustrative experiments and comparison with one of the counterparts are provided.     

General and multiplicative non-parametric corporate performance models with interval ratio data

The increasing intensity of global competition has led organizations to utilize various types of performance measurement tools for improving the quality of their products and services. Data envelopment analysis (DEA) is a methodology for evaluating and measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. All the data in the conventional DEA with input and/or output ratios assumes the form of crisp numbers. However, the observed values of data in real-world problems are sometimes expressed as interval ratios. In this paper, we propose two new models: general and multiplicative non-parametric ratio models for DEA problems with interval data. The contributions of this paper are fourfold: (1) we consider input and output data expressed as interval ratios in DEA; (2) we address the gap in DEA literature for problems not suitable or difficult to model with crisp values; (3) we propose two new DEA models for evaluating the relative efficiencies of DMUs with interval ratios, and (4) we present a case study involving 20 banks with three interval ratios to demonstrate the applicability and efficacy of the proposed models where the traditional indicators are mostly financial ratios.     

含右删失数据的ZIP模型及其应用

零膨胀Poisson回归(ZIP)是处理零频数过多计数资料的有效模型,而计数数据一般含有删失或不精密的特点.本文将删失数据引入到ZIP模型中来,分别建立含右删失数据的固定效应ZIP模型,随机效应ZIP模型,通过极大边际似然函数估计法对模型进行参数估计.最后,利用实例分析验证了上述模型的可行性.     

“最小二乘法变点冰水情数据处理算法”的研究与应用

将非线性统计学中的变点分析方法应用于基于空气、冰与水的物理特性差异实现冰水情自动检测过程的现场数据处理中,提出了利用被测物质物理参数的动态变点替代经验阈值来确定空气、冰与水界面位置的"最小二乘法变点冰水情数据处理算法",较好地解决了原始采样数据中奇异值引起误判的工程难题,提高了冰情数据分析的准确度.利用该算法对黄河河道现场冰水情采集数据进行分析,得到了较准确的结果,实现了对冰层生消全过程的自动监测.     

房地产行业的数学建模分析

分别建立了需求模型,供给模型,房地产与其他产业的关系模型,房价模型及房地产发展趋势的预测模型,并对影响模型的相应因素做了简要的分析.     

小麦发育后期茎秆抗倒伏问题研究

围绕小麦抗倒伏问题,综合运用数据预处理、相关性分析、数据拟合、数理方程、微分方程等方法,根据已有的抗倒伏模型,进行了模型修正,运用修正的模型,计算了六种小麦的倒伏指数,计算结果与试验结论基本吻合,并从生活常识的角度对模型的合理性进行论证,在对小麦茎秆性状相关性分析中,讨论了小麦最优性状特征,得出不同穗重下的最优株型结构,在考虑麦穗自重的前提下,进行力矩分析,运用最小势能原理进行理论推导,建立茎秆抗倒伏数理方程模型,并从数值计算和图形分析两个方面对模型的合理性进行了论证.     

基于虚拟仪器的比例溢流阀调压测量系统的设计与实现

针对工业设备中比例溢流阀调压特性不易测量的难点问题,提出"实验测量与分析模块化"和"数据三维可视化"的测控思路,设计了新的比例溢流阀调压特性实验方案和基于虚拟仪器LabVIEW与MATLAB相结合的测量系统,实现了对多点压力信号的实时采集和对数据信号的线性度、组合时频、三维可视化等多样分析;实验表明:所测比例溢流阀的线性度与测试精度分别达到2.47%和0.01%;并准确捕捉到100ms(毫秒级)内调压信息;实测证明该测量系统设计合理,突显了其自动化测量与智能化分析的优点,为今后比例阀的开发与工程实测拓宽研究思路、提供参考依据。