A Mixture of Experts Network Structure Construction Algorithm for Modelling and Control

This paper introduces a new fast, effective and practical model structure construction algorithm for a mixture of experts network system utilising only process data. The algorithm is based on a novel forward constrained regression procedure. Given a full set of the experts as potential model bases, the structure construction algorithm, formed on the forward constrained regression procedure, selects the most significant model base one by one so as to minimise the overall system approximation error at each iteration, while the gate parameters in the mixture of experts network system are accordingly adjusted so as to satisfy the convex constraints required in the derivation of the forward constrained regression procedure. The procedure continues until a proper system model is constructed that utilises some or all of the experts. A pruning algorithm of the consequent mixture of experts network system is also derived to generate an overall parsimonious construction algorithm. Numerical examples are provided to demonstrate the effectiveness of the new algorithms. The mixture of experts network framework can be applied to a wide variety of applications ranging from multiple model controller synthesis to multi-sensor data fusion.     

Face Detection Using Mixture of MLP Experts

This paper presents a face detection method which makes use of a modified mixture of experts. In order to improve the face detection accuracy, a novel structure is introduced which uses the multilayer perceptrons (MLPs), as expert and gating networks, and employs a new learning algorithm to adapt with the MLPs. We call this model Mixture of MLP Experts (MMLPE). Experiments using images from the CMU-130 test set demonstrate the robustness of our method in detecting faces with wide variations in pose, facial expression, illumination, and complex backgrounds. The MMLPE produces promising high detection rate of 98.8% with ten false positives.     

On the Incorporation of Time-delay Regularization into Curvature-based Diffusion

A new anisotropic nonlinear diffusion model incorporating time-delay regularization into curvature-based diffusion is proposed for image restoration and edge detection. A detailed mathematical analysis of the proposed model in the form of the proof of existence, uniqueness and stability of the viscosity solution of the model is presented. Furthermore, implementation issues and computational methods for the proposed model are also discussed in detail. The results obtained from testing our denoising and edge detection algorithm on several synthetic and real images showed the effectiveness of the proposed model in prserving sharp edges and fine structures while removing noise.     

稀疏贝叶斯混合专家模型及其在光谱数据标定中的应用

在光谱数据的多元校正中, 光谱数据通常是在多种不同的环境条件下收集的. 为了建模来源于不同环境中的高维光谱数据, 本文提出了一种新的稀疏贝叶斯混合专家模型, 并将其用来选择多元校正模型的稀疏特征. 混合专家模型能够把训练数据划分到不同的子类, 之后使用不同的预测模型来分别对划分后的数据进行预测, 因此这种方法适合于建模来自于多种环境下的光谱数据. 本文提出的稀疏的混合专家模型利用稀疏贝叶斯的方法来进行特征选择, 不依赖于事先指定的参数; 同时利用probit模型作为门函数以得到解析的后验分布, 避免了在门函数分类模型中进行特征提取时需要的近似. 本文提出的模型与其他几种常用的回归模型在人工数据集和几个公开的光谱数据集上进行了比较, 比较结果显示本文提出的模型对多个来源的光谱数据进行浓度预测时精度比传统的回归方法有一定的提高.     

Regularization of Cheap Periodic Control Problems

A regularization method for cheap periodic control problems is designed. The periodic problem for singularly perturbed Riccati matrix differential equations is reduced to an extended system of singularly perturbed initial problems. This system admits the application of a geometric approach based on the use of integral manifolds and, consequently, dimensional reduction. The solution is asymptotically expanded in fractional powers of a small parameter. An example on control of periodic oscillations of a mechanical system is given.__________Translated from Avtomatika i Telemekhanika, No. 6, 2005, pp. 59–73.Original Russian Text Copyright © 2005 by Smetannikova, Sobolev.This work was supported in part by the Russian Foundation for Basic Research, project no. 04-01-96515, Presidium of the Russian Academy of Sciences, project no. 19, and Boole Centre for Research in Informatics, UCC, Cork, Ireland, under the “Basic Research and Higher Education” Program, CRDF project no. SA-014-02.     

混合概率典型相关性分析

典型相关性分析(canonical correlation analysis, CCA)是一种用来分析2组随机变量之间相关性的统计分析工具,但作为一种线性数学模型,CCA不足以揭示真实世界中大量存在的非线性相关现象.采用局部化的方法,在概率典型相关性分析(probabilistic CCA, PCCA)的基础上,使用概率混合模型框架,提出了混合概率典型相关性分析模型(mixture of probabilistic CCA, MixPCCA)以及估计模型参数的2阶段期望最大化(expectation maximization, EM)算法,并给出了使用聚类融合确定局部线性模型数量的方法和MixPCCA模型应用于模式识别的理论框架.在手写体数据集USPS和MNIST上的实验证明,MixPCCA模型通过混合多个局部线性PCCA模型不仅提供了一种捕捉复杂的全局非线性相关性的解决方案,而且还具备检测只在局部区域才存在的相关性的能力.     

Regularization of a semivariogram

The production of estimates using the technique of kriging, and the evaluation of the accuracy of these estimates depends completely on the production of a model for the semivariogram of the deposit. The process of choosing such a model can be complicated in practice by the bulk and geometry of the samples taken. Some aspects of this problem are discussed and some formulae and a FORTRAN IV subroutine are presented to ease the task of modeling.     

基于距离负相关性的轨迹相似性度量方法

With the development of wireless communication technology and positioning technology, trajectory data emerge in large quantities. Similarity measurement is used in the query and analysis of trajectory data. In this paper, an improved similarity measure- ment is proposed. By introducing the negative correlation between the distance of points and the similarity into the real sequence ed- iting distance, the robustness to noise is preserved and the sensitivity to difference is improved. We apply different similarity mea- sures to the trajectory privacy protection method based on cluster-reconstruction, and verify the effectiveness of the proposed trajec- tory similarity measure by experiment on the real data and the synthetic data.     

迭代学习控制在配料控制系统中的应用

针对某水泥厂原有的配料控制器存在的配比不准、精度不高和稳定性差等方面的不足,着重论述了称量配料过程中的精度控制,通过分析动态称量配料过程的物理机理,建立了动态称量配料过程的数学模型并进行了定性分析,并利用迭代学习的控制算法对水泥配料控制器进行了改进,对控制算法进行了详细的介绍,结果表明,该控制方法较传统控制方法在控制精度上有了明显提高。     

Control of the Effects of Regularization on Variational Optic Flow Computations

We consider a variational model for the determination of the optic-flow in a general setting of non-smooth domains. This problem is ill-posed and its solution with PDE techniques includes a regularization procedure. The goal of this paper is to study a method to solve the optic flow problem and to control the effects of the regularization by allowing, locally and adaptively the choice of its parameters. The regularization in our approach is not controlled by a single parameter but by a function of the space variable. This results in a dynamical selection of the variational model which evolves with the variations of this function. Such method consists of new adaptive finite element discretization and an a posteriori strategy for the control of the regularization in order to achieve a trade-off between the data and the smoothness terms in the energy functional. We perform the convergence analysis and the a posteriori analysis, and we prove that the error indicators provide, as, a by-product, a confidence measure which shows the effects of regularization and serves to compute sparse solutions. We perform several numerical experiments, to show the efficiency and the reliability of the method in the computations of optic flow, with high accuracy and of low density.     

PID模块在负压控制系统中的应用

借助于Lonworks技术和PID控制算法,设计和实现了一种基于Lonworks技术的PID控制模块,并用NeuronC程序设计应用于广州新白云国际机场的隔离留验房负压控制系统。根据隔离留验房压力的实际响应,通过模糊规则进行推理和决策,实现对留验房空气压力的优化控制。实践证明该控制方法有较好的稳定性,运行效果好,具有适应环境变化的控制能力,满足系统控制要求。     

Performance Improvement of Discrete-time Linear Control Systems Subject to Varying Sampling Rates Using the Tikhonov Regularization Method

Machine Intelligence Research - Methods to stabilize discrete-time linear control systems subject to variable sampling rates, i.e., using state feedback controllers, are well known in the...     

Regularization methods for a problem of analytic continuation

In this paper, we prove a sharp stability estimate for the problem of analytic continuation. Based on the obtained stability estimate, a generalized Tikhonov regularization is provided and the corresponding error estimate is obtained. Moreover, we give many other regularization methods. For illustration, a numerical experiment is constructed to demonstrate the feasibility and efficiency of the proposed method.     

基于PLC的化肥配料混合控制系统的研究

设计了一种集配料系统和搅拌系统为一体的混合系统,利用计算机作为上位机提供良好的人机界面,使用WinCC软件实现PLC与计算机的PROFIBUS通信,从而进行系统的监控和管理,通过PROFIBUS网络完成变频器的远程控制,是一套实用型,具有良好应用前景的配料混合控制方案.     

Regularization of a lexicographic vector problem of integer programming

A stability criterion for a vector integer linear problem of lexicographic optimization is obtained. A regularization method is proposed that allows us to reduce a possible unstable output problem to a sequence of perturbed stable equivalent problems. Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 125–130, November–December, 1999.     

From a Gaussian Mixture Model to Nonadditive Fuzzy Systems

This paper presents the formulation of nonadditive generalized fuzzy model (GFM) by using the framework of the Gaussian mixture model, which provides the membership functions for the input fuzzy sets. By treating the consequent part as a function of fuzzy measures, we derive its coefficients. The defuzzified output constructed from both the premise and consequent parts of the GFM rules takes the form of Choquet integral. The computational burden involved with the solution of lambda-measure is mitigated using Q-measure. This nonadditive fuzzy model is applied on two benchmark applications, and the results are found to be better than those obtained from the additive fuzzy models.     

Regularization of a Volterra integral equation by linear inequalities

The determination of a monotone nonincreasing and convex response function arising in reservoir mechanics is investigated from the computational point of view. Regularization by linear inequalities yields the means for overcoming the ill-posedness of the considered convolution type integral equation. In order to find efficient numerical solutions and adapted approach for solving the associated constrained least squares problems is developed. Some simulation studies complete the paper.