一种在Kalman滤波中引入径向速度测量的新方法

研究在距离和径向速度测量噪声统计相关的情形下把径向速度测量引入Kalman滤波的新方法。分析了径向速度测量噪声与位置测量更新后状态滤波误差的统计相关性,根据Gauss-Markov定理导出了对应于径向速度测量的滤波方程由此而得到一种序贯滤波算法。两个不同的蒙特卡罗仿真表明,通过采用这一新算法引人径向速度测量,不仅可以大大提高状态估计的精度,而且其估计性能和计算效率优于传统的EKF。     

Impact of uncertainties on estimations of heat pump cycle performance

Sensitivity analysis is used to show how uncertainties in basic factors, such as heat transfer, pressure drop, compressor efficiency, and thermophysical properties, influence the result of heat pump cycle performance estimations. By comparing the results of this analysis with uncertainty levels of estimations and experimental determinations, it is established to what extent improvements in accuracy are needed. The investigation was carried out for several different applications and, as working fluids, both pure substances and non-azeotropic mixtures were examined. It was found that evaporation heat transfer and compressor efficiency are two areas where improvements are needed. It is also shown that estimates using very accurate, substance-specific, equations of state differ from those using more general types by up to 1 % for COP and 2% for capacity.     

Comments on the shortcomings of predicting the precision of Cavalieri volume estimates based upon assumed measurement functions

It is well known that the estimation of an object's volume by means of serial cross-sections, the so-called Cavalieri method, yields an unbiased estimate. But by itself it provides no means by which to estimate how precise this estimate is unless the shape of the volume is fully known beforehand. This knowledge can only be partially determined from the serial section information that is collected. Methods have been developed that claim to surmount this difficulty by using the serial section data to create a mathematical model of the volume's shape properties. The model then is used to estimate (predict) the precision of the volume estimate (its CE) from the single set of data available. Unfortunately, the theory underlying the model is flawed and so the model itself amounts to no more than an unsubstantiated guess about the shape of the volume. Therefore, the precision of the volume estimates that one obtains from the method is only as good as the model and this cannot be ascertained from the single set of acquired data. In this letter I explain the inadequacies of the modelling method. I suggest that it be used only with caution, if at all. Instead I suggest two alternative ways to predict the CE, one that is based upon a rule-of-thumb approach to the object's shape, and another that is based upon spectral analysis of the measurement function and that is easy to implement with available computer software.     

The smooth fractionator

A modification of the general fractionator sampling technique called the smooth fractionator is presented. It may be used in almost every situation in which sampling is performed from distinct items that are uniquely defined, often they are physically separated items or clusters like pieces, blocks, slabs, sections, etc. To each item is associated a ‘guesstimate’ or an associated variable with a more‐or‐less close – and possibly biased ? relationship to the content of the item. The smooth fractionator is systematic sampling among the items arranged according to the guesstimates in a unique, symmetric sequence with one peak and minimal jumps. The smooth fractionator is both very simple to implement and so efficient that it should probably always be used unless the natural sequence of the sampling items is equally smooth. So far, there is no theory for the prediction of the efficiency of smooth fractionator designs in general, and their properties are therefore illustrated with a range of real and simulated examples. At the cost of a slightly more elaborate sampling scheme, it is, however, always possible to obtain an unbiased estimate of the real precision and of some of the variance components. The only real practical problem for always obtaining a high precision with the smooth fractionator is specimen inhomogeneity, but that is detectable at almost no extra cost. With careful designs and for sample sizes of about 10, the sampling variation for the primary, smooth fractionator sampling step may in practice often be small enough to be ignored.     

高精度节能型电力稳压器

分析了现有交流稳压器的特点和不足,提出了新一代数控稳压器的理论和实际无均差系统的方法,给出了超高精度无均差稳压系统的实现方法.经全乐科技公司模拟试验,获得了很好的结果.市电220.4 V和220.5 V,试验样机采用3 V、9 V和27 V这3个变压器,已达到优于±1%的精度,符合大部分负载的实际需要,经用户单位试用半年,效果非常满意.     

Adaptive Lipschitz Observer Design for a Mammalian Model

This paper deals with observer designs for a proposed mathematical model of circadian rhythms which exist in almost every living organism. A 7th order model for mammalian circadian rhythms which captures the main dynamic features is considered in this paper. A recent result of one‐sided Lipschitz observer design in the literature is applied to this mammalian model to show a possibility of reducing measurements for circadian models in system biology. The mammalian model presented may contain an uncertainty parameter. An adaptive design of the Lipschitz observer is then applied to deal with this case. Besides detailed designs of both observers, detailed analysis is also performed for nonlinear functions in the mammalian model to show that the Lipschitz observers can indeed be applied. Several simulation studies of the proposed observers are carried out with the results shown in this paper.     

C~2C~3中无偏的不可扩展最大纠缠基

为了研究在量子计算和量子信息数据处理中起着重要作用的不可扩展最大纠缠基和无偏基,首先在C2C3空间上研究了不可扩展的最大纠缠基.其次构造了C2C3上两组无偏的不可扩展的最大纠缠基,并给出其一般形式,从而推广了文[9]在C2C3空间上构造的无偏基的结论,给出了更一般化的构造方法.     

基于社会经济指标影响的电力系统月度负荷组合预测模型

电力负荷受到多种因素影响,用负荷历史数据进行负荷预测结果往往不准确.考虑社会经济指标的影响,采用无偏灰色预测模型与偏最小二乘模型相结合的方法对月度电力负荷进行预测.首先通过无偏灰色理论的方法预测各社会经济指标,然后针对社会经济指标与电力月度负荷的变化特点进行偏最小二乘建模.最后拟合出负荷与各指标之间的线性关系式.实例证明,该组合预测模型具有较高精度.     

正则化稀疏模型

正则化稀疏模型在机器学习和图像处理等领域发挥着越来越重要的作用,它具有变量选择功能,可以解决建模中的过拟合等问题．Tibshirani 提出的 Lasso 使得正则化稀疏模型真正开始流行．文中总结了各种正则化稀疏模型,指出了各个稀疏模型被提出的原因、所具有的优点、适宜解决的问题及其模型的具体形式．最后,文中还指出了正则化稀疏模型未来的研究方向．