An improved algorithm for the computation of structural invariants of a system pencil and related geometric aspects

In this paper we propose a new recursive algorithm for computing the staircase form of a matrix pencil, and implicitly its Kronecker structure. The algorithm compares favorably to existing ones in terms of elegance, versatility, and complexity. In particular, the algorithm without any modification yields the structural invariants associated with a generalized state-space system and its system pencil. Two related geometric aspects are also discussed: we show that an appropriate choice of a set of nested spaces related to the pencil leads directly to the staircase form; we extend the notion of deflating subspace to the singular pencil case.     

改进的递推主元分析及递推主元回归算法

为了加速模型在线更新的速度以更好地适应实际工业过程的动态变化,通过在已有递推主元分析(PCA)算法的基础上简化了自相关矩阵的递推公式,从而改进了基于秩1更新的递推PCA算法,把原来需要进行2次秩1更新的步骤简化为仅仅需要进行一次秩1更新,并在此基础上提出了递推主元回归算法。仿真结果表明,改进后的基于秩1更新的递推PCA算法比原来的基于秩1更新的递推PCA算法缩短了近一半的运算时间,而新的递推主元回归算法,不但能够适应工业过程的动态变化,并且比批处理的方式节约了存储空间与计算时间。     

Multivariable system structure and parameter identification using the correlation method

This paper describes an algorithm for the structure determination and parameter identification of linear discrete-time multivariable systems from input-output measurements. The algorithm starts by determining the structure parameters of a certain canonical state space representation from an estimate of the correlation functions of the output sequence. Then the parameters of the A matrix are estimated from the estimated correlation functions using the recursive least squares method. Finally a normalized stochastic approximation algorithm is used for the estimation of the parameters of the B matrix from input-output measurements.     

Design of fixed-point smoother algorithm for linear discrete time-delay systems

This paper investigates the fixed-point smoothing problems for linear discrete-time systems with multiple time-delays in the observations.The linear discrete-time systems considered have l + 1 output channels.One is instantaneous observation and the others are delayed.The fixed-point smoothers involving recursive algorithm and non-recursive algorithm are designed by using innovation analysis theory without relying on the system augmentation approach.Also, it is further shown that the design of fixed-point smoother comes down to solving l + 1 Riccati equations with the same dimensions as the original systems.     

快速次优固定区间Wiener平滑器算法

为了克服带相关噪声控制系统的最优固定区间Kalman平滑算法要求较大计算负担的缺点,应用Kalman滤波方法,基于CARMA新息模型,由稳态最优Kalman平滑器导出了带相关噪声控制系统的最优固定区间Wiener递推状态平滑器,它带有系数阵指数衰减到零的高阶多项式矩阵.用截断系数矩阵近似为零的项的方法提出了相应的快速次优固定区间Wiener平滑算法.它显著地减少了计算负担,便于实时应用,还给出了截断误差公式和选择截断指标的公式.仿真例子说明了快速平滑算法的有效性.     

递推计算灵敏度的极大似然估计算法实现

对非线性连续一离散系统的极大似然参数估计方法导出了一种递推计算灵敏度的新算式.该算式借助二水平正交表的性质,避免了原灵敏度递推算式中的矩阵求逆运算.仿真实例验证了该算法的实用性和有效性.     

FIR filters and recursive forms for continuous time-invariant state-space models

An FIR (finite impulse response) filter and an FIR smoother are introduced for continuous time-invariant state-space models. It is shown in this note that finite impulse responses of the FIR filter and smoother can be easily determined by solving a simple Riccati-type matrix differential equation on a finite interval. Especially for systems with stationary processes, finite impulse responses of the FIR filter and smoother become time-invariant and can be computed from simpler equations. For fast computational purposes, recursive forms of the FIR filter and smoother are derived by using adjoint variables. In this case all gains for recursive forms are shown to be constant.     

差分模型参数递推估计的Householder变换法

本文提出了利用Householder变换进行差分模型参数递推估计的新方法.并由该方法导出了新的递推最小二乘法、递推增广矩阵法、递推广义最小二乘法、递推极大似然法. 文中分单变量、多变量两种情况重点讨论了新递推最小二乘法及其与传统递推最小二乘法的比较,并给出了计算实例.     

Recursive estimation for a noisy image represented by a hyperbolic PDE model

A recursive estimation technique is applied to the noisy image which is represented by a hyperbolic partial differential equation (PDE). Approximating a PDE model by a finite-difference approximation leads to an autoregressive (AR) model representation which Jain pointed out. In this paper, we use a new PDE model for the image representation. To apply a recursive estimation scheme to the image which is degraded by white noise, we propose the transformation of the.AR model into a state-space representation. To this representation, we apply a Kalman strip processor to reduce the order of the computation and storage, and the strip smoother (the optimal fixed-interval smoother) is also applied to obtain a better estimated imago. Three numerical examples are illustrated to show the effectiveness of the proposed algorithm.     

Recursive estimation of the parameters of linear multivariable systems

A recursive algorithm is proposed for the identification of linear multivariable systems. Utilization of a canonical state space model minimizes the number of parameters to be estimated. The problem of identification in the presence of noise is solved by using a recursive generalized least-squares method.     

Analysis of a modification of Gusfield's recursive algorithm for reconstructing ultrametric trees

The reconstruction of an ultrametric tree from a distance matrix is a very frequent subproblem in clustering or reconstructing evolutionary trees, both are common problems in Bioinformatics. In his famous book, Gusfield presented a very simple, but not time-optimal recursive algorithm for this problem. We show that a simple modification of Gusfield's algorithm allows a time-optimal solution.     

Recursive exponentially weighted PLS and its applications to adaptive control and prediction

A new and fast recursive, exponentially weighted PLS algorithm which provides greatly improved parameter estimates in most process situations is presented. The potential of this algorithm is illustrated with two process examples: (i) adaptive control of a two by two simulated multivariable continuous stirred tank reactor; and (ii) updating of a prediction model for an industrial flotation circuit. The performance of the recursive PLS algorithm is shown to be much better than that of the recursive least squares algorithm. The main advantage of the recursive PLS algorithm is that it does not suffer from the problems associated with correlated variables and short data windows. During adaptive control, it provided satisfactory control when the recursive least squares algorithm experienced difficulties (i.e., ‘blew’ up) due to the ill-conditioned covariance matrix, (X^TX)_t. For the industrial soft sensor application, the new algorithm provided much improved estimates of all ten response variables.     

一类非线性时变结构系统的辨识方法和预报器

本文对一类非线性时变结构系统,给出一种新型的递推梯度法和结构适应式自校正递推预报器.这种算法能自动改变模型的结构.通过油田预报实践,表明这种预报器能跟踪系统结构性变化,从而提高变结构系统预报的精度.     

A two-level parameter estimation algorithm using the multiple projection approach

An efficient two-level algorithm is developed for parameter estimation using the multiple projection approach. The optimal minimum variance estimate is achieved using a fixed number of iterations. Both the recursive and non-recursive versions of the algorithm are presented. Simulation results of two examples have indicated that the new two-level algorithm provides accurate estimates whilst needing a reduced amount of computational effort.     

基于目标函数的递推子空间辨识算法

针对实际工程中要求对系统参数进行在线估计的问题, 提出一种递推子空间辨识的新方法. 通过引入辅助变量关系将递推子空间辨识问题转化为目标函数的迭代最小化问题. 采用递推最小二乘算法在线估计参数并由传播方法得到更新的广义能观性矩阵, 进而求得子空间辨识模型系统参数. 该算法简单有效且对初值具有鲁棒性. 最后, 通过仿真实例验证算法的有效性.     

Cholesky分解递归算法与改进

递归算法是计算稠密线性代数的一种新的有效方法。递归产生自动、变化的矩阵分块,能充分发挥当今分级存储高性能计算机的效率。对Cholesky分解递归算法进行了研究,给出了算法的详细推导过程,用具有递归功能的Fortran90实现了算法,并通过矩阵元素顺序重排的方法,进一步提高了递归算法的运算速度。研究产生的算法比目前常用的分块算法快15％－25％。     

乔莱斯基分解递归算法的研究

1 引言以乔莱斯基(Cholesky)分解、LU分解等为代表的线性代数问题的数值计算在现代科学研究和工程技术中得到广泛应用。随着计算机结构和技术的发展,实现这些线性代数数值计算的计算机算法和软件也在不断发展。通用的基本线性代数子程序库BLAS(Basic Lin-ear Algebra Subprograms)从70年代的Level-1 BLAS(执行向量一向量运算),发展到80年代的Level-2     

一种不完全信息下递推辨识方法及收敛性分析

针对信号在网络环境下传输带来不完全信息使得在线参数辨识算法和收敛性困难的问题, 不同于传统递推最小二乘方法, 本文提出了一种不完全信息下递推辨识方法并分析其收敛性. 首先运用伯努利分布刻画引起不完全信息的数据丢包特性, 然后基于辅助模型方法补偿不完全信息并构造了新的数据信息矩阵, 并运用矩阵正交变换性质对数据信息矩阵进行QR分解, 推导了融合网络参数的递推辨识新算法, 理论证明了在不完全信息下递推参数辨识算法的收敛性. 最后仿真结果验证了所提方法的可行性和有效性.