ICA based speckle filtering for target extraction in SAR images using adaptive space separation

A novel approach based on independent component analysis (ICA) for speckle filtering and target extraction of synthetic aperture radar (SAR) images is proposed using adaptive space separation with weighted information entropy (WIE) incorporated. First the basis and the independent components are respectively obtained by ICA technique, and WIE of the image is computed; then based on the threshold computed from function T-WIE (threshold versus weighted-information-entropy), independent components are adaptively separated and the bases are classified accordingly. Thus, the image space is separated into two subspaces: "clean" and "noise". Then, a proposed nonlinear operator ABO is applied on each component of the 'clean' subspace for further optimization. Finally, recovery image is obtained reconstructing this subspace and target is easily extracted with binarisation. Note that here T-WIE is an interpolated function based on several representative target SAR images using proposed space separation algorithm.     

On-line Batch Process Monitoring and Diagnosing Based on Fisher Discriminant Analysis

Introduction Nowadays, it has been paying more attentionto the batch or semi-batch process which producedthe high added value and high quality products inchemical industry, such as polymer, pharmaceuti-cal and semiconductor industry.The aim of the batch process monitoring is tokeep the product quality uniform and consistentunder batch-to-batch process and meet specifica-tion limits. The direct approach is to monitor cru-cial product quality variables in batch process.However, quality variables…     

基于SVD的柴油机振动信号盲分离预处理

在利用独立分量分析对缸盖振动信号进行盲分离时,原始采样信号不满足独立分量分析的基本假设,而且缸盖振动信号信噪比较低,影响分离的速度和精度.采用小波阈值降噪的方法进行了降噪处理,提高了信噪比.采用奇异值分解的方法估计了缸盖振动的独立源数,并对缸盖振动信号进行了白化处理,为独立分量分析的应用建立了基础.     

State inspection for transmission lines based on independent component analysis

Monitoring transmission towers is of great importance to prevent severe thefts on them and ensure the reliability and safety of the power grid operation. Independent component analysis (ICA) is a method for finding underlying factors or components from multivariate statistical data based on dimension reduction methods, and it is applicable to extract the non-stationary signals. FastICA based on negentropy is presented to effectively extract and separate the vibration signals caused by human activity in this paper. A new method combined empirical mode decomposition (EMD) technique with the adaptive threshold method is applied to extract the vibration pulses, and suppress the interference signals. The practical tests demonstrate that the method proposed in the paper is effective in separating and extracting the vibration signals.     

An independent component analysis algorithm through solving gradient equation combined with kernel density estimation

A new algorithm for linear instantaneous independent component analysis is proposed based on max-imizing the log-likelihood contrast function which can be changed into a gradient equation. An iterative method is introduced to solve this equation efficiently. The unknown probability density functions as well as their first and second derivatives in the gradient equation are estimated by kernel density method. Computer simulations on artificially generated signals and gray scale natural scene images confirm the efficiency and accuracy of the proposed algorithm.     

优化端元提取方法的高光谱混合像元分解

高光谱图像的混合像元分解将原始图像分解为多种纯净地物及相应的丰度,端元提取是混合像元分解的关键技术. 针对传统算法计算速度慢、搜索范围较大的特点,基于改进的ICA （independent component analysis）算法以及优化的候选端元判断方法,提出了一种优化的混合像元分解方法. 首先使用改进的算法优化端元提取方法;然后利用相邻像素的光谱特征和空间特征信息,结合并行算法对候选端元进行优化;最后利用真实的高光谱数据对该方法的性能进行了验证. 验证结果表明:该方法能有效提高端元提取精度,降低复杂度,与经典的端元提取算法N-FINDER相比,准确度提高了3.55%,解混后得到的地物分类精度有了明显改善（总体分类精度提高了2.88%）.      

基于融合两类核Fisher鉴别函数的人脸识别方法

提出了一种基于两类核Fisher鉴别分析(KFDA)的人脸识别方法,对每2个不同人脸类别求解一个核Fisher鉴别函数,其优点是能针对特定的2个人脸图像类别,抽取区分该2类人脸的最佳鉴别特征,克服了多类KFDA和2类KFDA相比是次优的问题.为解决KFDA计算量大的问题,将MSE推广为基于核的MSE(KMSE),用其得到核Fisher鉴别函数,减少了训练和识别的计算时间.在识别阶段应用了两种融合方法融合各个基于KMSE的核Fisher鉴别函数.     

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为降低物流需求建模中最小二乘支持向量机（LSSVM）的结构复杂性、进一步提高LSSVM对物流需求的预测精度,提出一种基于灰色关联分析（GRA）与核主成分分析（KPCA）的LSSVM预测方法。首先利用GRA找出物流需求的主要影响因素;然后利用KPCA提取主要影响因素的非线性主成分,消除因素之间的多重相关性;最后,将提取出的非线性主成分作为LSSVM的输入变量,构建物流需求预测模型,并采用改进粒子群(IPSO)算法调整LSSVM参数。运用该方法对我国物流需求进行实例分析,结果表明,该方法有效减少了LSSVM输入变量个数,简化了LSSVM结构,并且在一定程度上提高了物流需求预测精度。     

基于GRA 与KPCA 的LSSVM 物流需求预测

为降低物流需求建模中最小二乘支持向量机（LSSVM）的结构复杂性、进一步提高LSSVM对物流需求的预测精度,提出一种基于灰色关联分析（GRA）与核主成分分析（KPCA）的LSSVM预测方法.首先利用GRA找出物流需求的主要影响因素;然后利用KPCA提取主要影响因素的非线性主成分,消除因素之间的多重相关性;最后,将提取出的非线性主成分作为LSSVM的输入变量,构建物流需求预测模型,并采用改进粒子群 (IPSO)算法调整LSSVM参数.运用该方法对我国物流需求进行实例分析,结果表明,该方法有效减少了LSSVM输入变量个数,简化了LSSVM结构,并且在一定程度上提高了物流需求预测精度.     

混合核函数支持向量机在系统建模中的应用

混合核函数兼具了局部核函数和全局核函数的优点,并可通过权重因子调节它们对混合核函数的作用,取得较好的综合辨识效果。针对稀土萃取过程组分含量实时在线检测的难题,将基于混合核函数的支持向量机(SVM)算法用于稀土萃取过程组分含量建模。应用结果表明:基于混合核函数的组分含量软测量模型具有较好的模型拟合精度和满意的预测效果,能满足稀土萃取过程组分含量在线预估的要求。     

基于AHP和DEA方法的公路建设项目评价

建立了公路建设项目的综合评价指标体系,改进了传统的数据包络分析方法;将层次分析法和改进的数据包络分析方法相结合,建立了综合评价模型;实证了运用该模型解决公路建设项目评价问题的可行性.     

Robust digital audio watermarking scheme using blind source separation with global optimal property

The paper proposes a robust digital audio watermarking scheme using blind source separation(BSS) based on the global optimization of independency metric(IM),which is formulated as a generalized eigenvalue(GE) problem.Compared with traditional information-theoretical approaches used in digital audio watermarking,such as fast independent component analysis(FastICA),the proposed scheme has lower complexity without timeconsuming iteration steps used in FastICA.To make full use of the multiresolution characteris...     

THE PARALLEL RECURSIVE AP ADAPTIVE ALGORITHM BASED ON VOLTERRA SERIES

Aiming at the nonlinear system identification problem, a parallel recursive affine projection （AP） adaptive algorithm for the nonlinear system based on Volterra series is presented in this paper. The algorithm identifies in parallel the Volterra kernel of each order, recursively estimate the inverse of the autocorrelation matrix for the Volterra input of each order, and remarkably improve the convergence speed of the identification process compared with the NLMS and conventional AP adaptive algorithm based on Volterra ,series. Simulation results indicate that the proposed method in this paper is efficient.     

Recognizing frequency characteristics of gas sensor array

A novel method based on independent component analyzing （ICA） in frequency domain to distinguish the frequency characteristics of multi-sensor system is presented. The conditions of this type of ICA are considered and each step of resolving the problem is discussed. For a two gas sensor array, the frequency characteristics including amplitude-frequency and phase-frequency are recognized by this method, and cross-sensitivity between them is also eliminated. From the principle of similarity, the recognition mean square error is no more than 0.085.     

Automatic software install/update for embedded Linux

Linux has a special feature of automount in the Linux kernel. Filesystem can be mounted and unmounted automatically. Its performance is similar to MS Windows. It works well under demands of more saving resources and automatization, like memory of system. An approach to install/update software automatically on embedded platform was proposed. This approach derives from above feature based on embedded environment with Linux OS. Configurations of files related to this feature were introduced. An example in practice was given to realize this approach from universal serial bus （USB） memory disk when USB disk is available.     

A Multiple Model Approach to Modeling Based on Fuzzy Support Vector Machines

A new multiple models (MM) approach was proposed to model complex industrial process by using Fuzzy Support Vector Machines(F_SVMs). By applying the proposed approach to a pH neutralization titration experiment, F_SVMs MM not only provides satisfactory approximation and generalization property, but also achieves superior performance to USOCPN multiple modeling method and single modeling method based on standard SVMs.     

A bayesian based process monitoring and fixture fault diagnosis approach in the auto body assembly process

The auto body process monitoring and the root cause diagnosis based on data-driven approaches are vital ways to improve the dimension quality of sheet metal assemblies. However, during the launch time of the process mass production with an off-line measurement strategy, the traditional statistical methods are difficult to perform process control effectively. Based on the powerful abilities in information fusion, a systematic Bayesian based quality control approach is presented to solve the quality problems in condition of incomplete dataset. For the process monitoring, a Bayesian estimation method is used to give out-of-control signals in the process. With the abnormal evidence, the Bayesian network (BN) approach is employed to identify the fixture root causes. A novel BN structure and the conditional probability training methods based on process knowledge representation are proposed to obtain the diagnostic model. Furthermore, based on the diagnostic performance analysis, a case study is used to evaluate the effectiveness of the proposed approach. Results show that the Bayesian based method has a better diagnostic performance for multi-fault cases.     

Kernel Generalized Noise Clustering Algorithm

IntroductionFuzzy clustering is one of the important methodsin pattern recognition. The most widely used fuzzyclustering is the fuzzy c-means (FCM) algorithm[1]which is conceived by Dunn[2]and generalized byBezdek[3]. Based on an objective function, the F…     

独立分量分析原理及其应用

综述了独立分量分析(ICA）的基本原理及基于信息最大化原理的各种方法及其特性，介绍了HJ网络、基于信息最大化的Infomax法及其扩展算法、极大似然估计(MLE)法、负熵最大化法、基于高阶累量的ICA法和Dussage法，对各种方法性能做了比较，说明了ICA在生物医学信号处理中的应用，并对ICA的发展作了展望．     

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无论是经典还是现代控制理论,大多是建立在线性系统基础上,目前对非线性系统还没有比较成熟的理论.常规PID控制在对象变化时,控制器的参数不能自动修改适应.将模糊控制与PID控制相结合,利用模糊推理方法实现对PID参数的在线自整定,设计了一种模糊自适应PID控制器.在分析汽车模型的基础上,采用PID控制、模糊自适应PID控制两种方法,联合Simulink软件分别对汽车的防抱死制动系统（ABS）进行刹车运动仿真研究,极大地提高了模糊控制方法和PID控制算法的应用性能.结果表明,模糊自适应PID控制方法可以达到更好的制动效果,提高了系统的动态性能和安全性能.