Solving regularized least squares with qualitatively controlled adaptive cross‐approximated matrices

The adaptive cross‐approximation (ACA) technique is applied to accelerating an inverse‐problem solver that estimates charge distribution on a dielectric spacer. The ACA generates an approximated system‐matrix that enables us to carry out high‐speed inverse calculation. We designed an approximation procedure based on ACA with some additional concepts, that is, (a) partitioning of matrix based on algebraic information, (b) approximation quality control based on matrix norms, and so on. The tested solver (LSQR for regularized least squares) with ACA demonstrates about 10 times faster performance than that without ACA. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 159(3): 10–18, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20326     

Model predictive control for systems with stochastic multiplicative uncertainty and probabilistic constraints

Robust predictive control handles constrained systems that are subject to stochastic uncertainty but propagating the effects of uncertainty over a prediction horizon can be computationally expensive and conservative. This paper overcomes these issues through an augmented autonomous prediction formulation, and provides a method of handling probabilistic constraints and ensuring closed loop stability through the use of an extension of the concept of invariance, namely invariance with probability p.     

一种16QAM调制实现技术的研究

讨论了16QAM调制时应用不同类型和参数的滤波器对系统性能的影响．针对16QAM的特点，采用了存储波形累加求和法来代替一般的滤波成形，提高了调制速度．并利用其相位对称的特点将波形存储表压缩为原容量的1／4，有效地节约了存储空间．     

Two Modified Semicircle Control Charts for Detecting Process Improvement

A semicircle control chart can be used in detecting both increases and decreases in the mean and/or variance. In this paper, we propose two modified semicircle charts for detecting a reduction in the process variance, a.k.a. process improvement. Each of these modified semicircle charts, namely, SC1 and SC2 has two limits, defined by the inner and outer semicircles. A process improvement is detected by the SC1 scheme if a point is plotted inside the smallest semicircle, or if two successive points are plotted between the inner and outer semicircles and by the SC2 scheme if a point plots inside the smallest semicircle or if two of three successive points plot between the inner and outer semicircles. It will be shown that the two modified semicircle charts have superior average run length (ARL) performances to the basic semicircle chart in the detection of process improvement. The ARL study is conducted by means of a simulation.     

Structured Latent Curve Models for the Study of Change in Multivariate Repeated Measures.

This article considers a structured latent curve model for multiple repeated measures. In a structured latent curve model, a smooth nonlinear function characterizes the mean response. A first-order Taylor polynomial taken with regard to the mean function defines elements of a restricted factor matrix that may include parameters that enter nonlinearly. Similar to factor scores, random coefficients are combined with the factor matrix to produce individual latent curves that need not follow the same form as the mean curve. Here the associations between change characteristics in multiple repeated measures are studied. A factor analysis model for covariates is included as a means of relating latent covariates to the factors characterizing change in different repeated measures. An example is provided. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

广义逆的计算与最小二乘估计

给出了某些广义逆的计算方法,将这些结果应用于观测系统的参数估计,给出了系统无加权和加权最小二乘的最新估计结果,推广了[1]的工作,同时简化了[2]中求多个相容矩阵方程公共解的算法。     

A Recursive Orthogonal Least Squares Algorithm for Training RBF Networks

A recursive orthogonal least squares (ROLS) algorithm for multi-input, multi-output systems is developed in this paper and is applied to updating the weighting matrix of a radial basis function network. An illustrative example is given, to demonstrate the effectiveness of the algorithm for eliminating the effects of ill-conditioning in the training data, in an application of neural modelling of a multi-variable chemical process. Comparisons with results from using standard least squares algorithms, in batch and recursive form, show that the ROLS algorithm can significantly improve the neural modelling accuracy. The ROLS algorithm can also be applied to a large data set with much lower requirements on computer memory than the batch OLS algorithm.     

基于支持向量机与神经网络的间谐波测量混合算法

针对目前缺乏国家标准规范间谐波对电能质量的影响,也缺乏有效的手段监测间谐波的问题,用支持向量机理论对其进行了探索。支持向量机理论将间谐波这个非线性问题变换到更高维的空间中进行线性回归,它基于迭代权调整最小二乘法,引入反向传播神经网络算法整定算法参数,通过反馈现场采集、分析信号,并将教师信号与计算信号的差值作为调整参数的驱动信号,在此基础上通过反向遗传算法(BPNN)的反向传播能力对参数进行基于负反馈的调整,提高了算法的收敛速度。通过数值实验对比,该算法比没有使用差动信号的混合算法效率提高约13%。