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Real-time motion deblurring algorithm with robust noise suppression

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Journal of Zhejiang University-Science C(Computers and Electronics) 2010年第5期11卷 375-380页

作者： hua-jun FENG Yong-pan WANG Zhi-hai xu qi LI hua LEI Ju-feng ZHAO State Key Lab of Modern Optical Instrumentation Zhejiang University Hangzhou 310027 China

In an image restoration process,to obtain good results is challenging because of the unavoidable existence of noise even if the blurring information is already *** suppress the deterioration caused by noise during the image deblurring process,we propose a new deblurring method with a known ***,the noise in the measurement process is assumed to meet the Gaussian distribution to fit the natural noise ***,the first and second orders of derivatives are supposed to satisfy the independent Gaussian distribution to control the non-uniform *** results show that our method is obviously superior to the Wiener filter,regularized filter,and Richardson-Lucy(RL) ***,owing to processing in the frequency domain,it runs faster than the other algorithms,in particular about six times faster than the RL algorithm.

关键词： Motion blurring Motion kernel Gaussian distribution

Qualitative and quantitative uncertainties in regional rainfall frequency analysis

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2015年第3期16卷 194-203页

作者： qian ZHU Xiao xu Chao GAO qi-hua Yue-ping xu Institute of Hydrology and Water Resources Zhejiang University Hangzhou 310058 China

Uncertainty exists widely in hydrological analysis, and this makes the process of uncertainty assessment very im- portant for making robust decisions. In this study, uncertainty sources in regional rainfall frequency analysis are identified for the first time. The numeral unite spread assessment pedigree （NUSAP） method is introduced and is first employed to quantify qual- itative uncertainty in regional rainfall frequency analysis. A pedigree matrix is particularly designed for regional rainfall frequency analysis, by which the qualitative uncertainty can be quantified. Finally, the qualitative and quantitative uncertainties are com- bined in an uncertainty diagnostic diagram, which makes the uncertainty evaluation results more intuitive. From the integrated diagnostic diagram, it can be determined that the uncertainty caused by the precipitation data is the smallest, and the uncertainty from different grouping methods is the largest. For the downstream sub-region, a generalized extreme value （GEV） distribution is better than a generalized logistic （GLO） distribution; for the south sub-region, a Pearson type III （PE3） distribution is the better choice; and for the north sub-region, GEV is more appropriate.

关键词： Qualitative uncertainty Uncertainty analysis Numeral unite spread assessment pedigree (NUSAP) method Regional rainfall frequency analysis Pedigree matrix Diagnostic diagram

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神经网络集成在发动机故障诊断中的应用研究

航空动力学报 2005年第5期20卷 847-852页

作者：徐启华师军淮海工学院电子工程系江苏连云港222005 西北工业大学自动化学院陕西西安710072

提出一种基于A daBoost的集成神经网络故障诊断方法,利用多层前向神经网络作为故障弱分类器,通过简单地训练若干个单一神经网络并将其预测结果进行合成,实现了对航空发动机多类故障的诊断。针对一个涡轮喷气发动机气路部件的仿真实验表... 详细信息

提出一种基于A daBoost的集成神经网络故障诊断方法,利用多层前向神经网络作为故障弱分类器,通过简单地训练若干个单一神经网络并将其预测结果进行合成,实现了对航空发动机多类故障的诊断。针对一个涡轮喷气发动机气路部件的仿真实验表明,这种方法提高了最终故障分类器的泛化能力,便于工程应用。

关键词：航空、航天推进系统航空发动机 Boosting算法神经网络集成故障诊断泛化

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基于支持向量机的航空发动机故障诊断

航空动力学报 2005年第2期20卷 298-302页

作者：徐启华师军淮海工学院电子工程系江苏连云港222005 西北工业大学自动控制系陕西西安710072

支持向量机是一种具有完备统计学习理论基础和出色学习性能的新型机器学习方法,它能够较好地克服神经网络容易出现的过学习和泛化能力低等缺陷。提出一种基于支持向量机的航空发动机故障诊断方法,应用该方法成功地对发动机气路部件的几... 详细信息

支持向量机是一种具有完备统计学习理论基础和出色学习性能的新型机器学习方法,它能够较好地克服神经网络容易出现的过学习和泛化能力低等缺陷。提出一种基于支持向量机的航空发动机故障诊断方法,应用该方法成功地对发动机气路部件的几种典型故障进行了正确诊断。在对检验样本施加噪声后,支持向量机构成的故障分类器仍然能够满足发动机故障诊断的要求,表明提出的故障诊断算法具有良好的鲁棒性,可以作为工程应用的基础。

关键词：航空、航天推进系统航空发动机支持向量机故障诊断鲁棒性

一种新型多分类支持向量算法及其在故障诊断中的应用

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系统仿真学报 2005年第11期17卷 2766-2768,2784页

作者：徐启华师军淮海工学院电子工程系江苏连云港222005 西北工业大学自动化学院陕西西安710072

层次支持向量机(H-SVM)比通常的多分类支持向量算法具有更快的训练速度和分类速度,便于实现在线分类。提出一种基于H-SVM的多类故障诊断方法,根据特征空间中各类故障样本中心之间的距离来逐层划分子类,距离较近的故障样本归为同一个子... 详细信息

层次支持向量机(H-SVM)比通常的多分类支持向量算法具有更快的训练速度和分类速度,便于实现在线分类。提出一种基于H-SVM的多类故障诊断方法,根据特征空间中各类故障样本中心之间的距离来逐层划分子类,距离较近的故障样本归为同一个子类进行训练,得到的H-SVM层次结构合理,各层的SVM分类间隔大、泛化性能强。另外,用ν-SVM代替通常的C-SVM作为两类分类器,分类器参数意义明确、变化范围小,更容易确定。针对一个涡轮喷气发动机气路部件故障诊断的仿真实验表明,设计的故障分类器具有良好的分类准确性和泛化性能,可以对发动机气路部件的典型故障进行快速诊断。作为应用实例,对JT9D发动机的6种实际故障进行了有效诊断。

关键词：支持向量机故障诊断多类分类仿真应用

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应用SVM的发动机故障诊断若干问题研究

航空学报 2005年第6期26卷 686-690页

作者：徐启华师军淮海工学院电子工程系江苏连云港222005 西北工业大学自动化学院陕西西安710072

支持向量机能够克服一般神经网络容易出现的过学习和泛化能力低等不足。提出一种基于支持向量机的航空发动机气路部件故障诊断方法,讨论了支持向量机的核函数选择和参数确定问题,并对“块算法”进行了分析。仿真实验表明,设计的正则化... 详细信息

支持向量机能够克服一般神经网络容易出现的过学习和泛化能力低等不足。提出一种基于支持向量机的航空发动机气路部件故障诊断方法,讨论了支持向量机的核函数选择和参数确定问题,并对“块算法”进行了分析。仿真实验表明,设计的正则化参数和核参数合理,故障分类器具有良好的分类准确性和泛化性能,可以对发动机气路部件的典型故障进行正确诊断。

关键词：航空发动机支持向量机故障诊断核函数泛化

Fault Diagnosis for Aero-engine Applying a New Multi-class Support Vector Algorithm

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Chinese Journal of Aeronautics 2006年第3期19卷 175-182页

作者：徐启华师军 Electronic Engineering Department Huaihai Institute of Technology Lianyungang 222005China College of Automatic Control Northwestern Polytechnical University Xi'an 710072China

Hierarchical Support Vector Machine （H-SVM） is faster in training and classification than other usual multi-class SVMs such as ＂1-V-R＂and ＂1-V-1＂. In this paper, a new multi-class fault diagnosis algorithm based on H-SVM is proposed and applied to aero-engine. Before SVM training, the training data are first clustered according to their class-center Euclid distances in some feature spaces. The samples which have close distances are divided into the same sub-classes for training, and this makes the H-SVM have reasonable hierarchical construction and good generalization performance. Instead of the common C-SVM, the v-SVM is selected as the binary classifier, in which the parameter v varies only from 0 to 1 and can be determined more easily. The simulation results show that the designed H-SVMs can fast diagnose the multi-class single faults and combination faults for the gas path components of an aero-engine. The fault classifiers have good diagnosis accuracy and can keep robust even when the measurement inputs are disturbed by noises.

关键词： support vector machine fault diagnosis multi-class classification

Relations of Budd-Chiari syndrome to prothrombin gene mutation

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Hepatobiliary & Pancreatic Diseases International 2004年第2期3卷 214-218页

作者： Guo-Ling Lin, Pei-qin xu, hua qi, Jian-hua Lian, Hong Zheng and Xiao-Wei Dang Zhengzhou, ChinaDepartment of General Surgery, First Affiliated Hospi- tal of Zhengzhou University the Faculty of Cytobiology and Medical Genetics, Medical School, Zhengzhou Univer- sity , Zhengzhou 450052, China Department of General Surgery First Affiliated Hospital of Zhengzhou University Zhengzhou 450052 China.

BACKGROUND: Budd-Chiari syndrome (BCS) is a type of disease characterized by portal hypertension and/or hy- pertension of the inferior vena cava (IVC) due to the ob- struction of the hepatic veins (HV) and/or intrahepatic IVC outlet. Being etiologically complicated and obscure, BCS can be acquired or idiopathic and several gene muta- tions may be contributable. This study was to explore whether prothrombin gene mutation (F G20210A) takes part in the pathogenesis of BCS and to investigate their cor- relativity. METHODS: In 38 proven BCS patients and 70 controls, polymerase chain reaction-restriction fragment length poly- morphism (PCR-RFLP) was used to find F G20210A mutation. To detect whether there are any mutations, four steps were taken: purification of genome DNA from whole blood, amplification of special fragment by polymerase chain reaction, digestion of the fragment via restriction en- donuclease, and analysis of results by polyacrylamide gel electrophoresis. RESULTS: F G20210A mutation was not detected in all patients and controls. CONCLUSIONS: No F G20210A mutation exists in Chi- nese patients with BCS, nor correlativity between the oc- currence of BCS and F G20210A mutation. The etiology of BCS in the Chinese needs further investigation.

关键词： hepatic vein thrombosis etiology F G20210A gene mutation

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支持向量机在交通流量实时预测中的应用

公路交通科技 2005年第12期22卷 131-134页

作者：徐启华杨瑞淮海工学院电子工程系江苏连云港222005

实时、准确的交通流量预测是正在发展的智能交通系统的关键问题之一,对于交通控制和交通流诱导都有着直接的影响。提出一种基于支持向量机的交通流量实时预测模型,通过采用序贯最小优化算法,能够实现对交通流量的有效预测。应用实例表明... 详细信息

实时、准确的交通流量预测是正在发展的智能交通系统的关键问题之一,对于交通控制和交通流诱导都有着直接的影响。提出一种基于支持向量机的交通流量实时预测模型,通过采用序贯最小优化算法,能够实现对交通流量的有效预测。应用实例表明,支持向量机具有良好的泛化性能,在输入信号混有10%噪声的情况下,支持向量机的鲁棒性更好,预测的平均误差为4.25%,预测结果优于BP神经网络和动态递归神经网络。

关键词：支持向量机交通流量实时预测模型泛化核函数