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模糊中心聚类的模式识别学习方法

曾黄麟,袁慧,刘小芳

《中国工程科学》 2004年第6卷第11期页码 33-37

摘要：

基于一个约束条件下的非线性规划问题的优化计算思想，把模糊中心聚类中计算输入矢量与中心的距离来实现聚类作为一种优化计算问题，证明了模糊中心聚类方法，取一个适当的属函数，其聚类中心vi为模糊聚类中心价值函数的极小值，推导出了基于模糊中心聚类的模式识别的无导师递推学习方法，提出了模糊中心聚类模式分类神经网络结构，该网络可以实现并行数据处理和模式分类的软划分和硬划分。

关键词：模糊中心聚类模式识别神经网络

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PD pattern recognition based on multi-fractal dimension in GIS

ZHANG Xiaoxing, YAO Yao, TANG Ju, ZHOU Qian, XU Zhongrong

《机械工程前沿（英文）》 2008年第3卷第3期页码 270-275 doi: 10.1007/s11465-008-0042-1

摘要： This paper designs four types of gas insulated substation (GIS) defect models based on partial discharge (PD) characteristics and its defections. The GIS gray intensity images are constructed based on the mass specimens gathered by the ultra-high frequency and high-speed sampling systems. The multi-fractal dimension is founded on the box-counting dimension and multi-fractal theories. The GIS gray intensity images distillation methods, based on multi-fractal characteristics, is put forward. The box-counting dimension, multi-fractal dimension, and discharge centrobaric characteristics of the PD images are also extracted. The characteristic variables are then classified by the radial basis function (RBF) network. Identified results show that the methods can effectively elevate the discrimination of the four types of defects in GIS.

关键词： substation high-speed discharge centrobaric network ultra-high frequency

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基于径向基函数神经网络的滚动轴承故障模式的识别

陆爽,张子达,李萌

《中国工程科学》 2004年第6卷第2期页码 56-60

摘要：

径向基函数（RBF）神经网络是一种3层前馈性神经网络，它具有较强的函数逼近能力和分类能力。鉴于径向基函数神经网络的优点，在对滚动轴承振动信号特征分析的基础上，提出了采用时序方法对其建立AR模型，利用AR模型参数建立径向基函数神经网络，并用该网络对滚动轴承的故障模式进行了识别。理论和试验证明了该方法的有效性，且具有较高的识别精度。

关键词：滚动轴承振动信号 AR模型 RBF神经网络模式识别

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模式识别技术在泥浆浓度反演中的应用

李德军,吕艳华,王润田

《中国工程科学》 2007年第9卷第5期页码 81-84

摘要：

泥浆在建筑工程中使用非常普遍，合理地控制泥浆的物理性能对于建筑工程施工及其质量控制非常重要，通过声学方法可以有效地监测泥浆的体积浓度等物理参数。在通过声衰减和声速等介质的声学参数反演泥浆浓度的过程中，数据拟合的好坏直接影响到反演的精确程度。通过模式识别技术，利用聚类算法，对数据进行分类、归类处理，能有效的地提高反演的准确度。

关键词：模式识别最近邻法聚类算法泥浆浓度

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统计不相关最佳鉴别矢量集的本质研究

吴小俊,杨静宇,王士同,刘同明,Josef Kittler

《中国工程科学》 2004年第6卷第2期页码 44-47

摘要：

对统计不相关最佳鉴别矢量集的本质进行研究，在基于总体散布矩阵特征分解的基础上，构造了一种白化变换，使得变换后的样本空间中的总体散布矩阵为单位矩阵，这样使得传统的最佳鉴别矢量集算法得到的均是具有统计不相关的最佳鉴别矢量集，从而揭示了统计不相关最佳鉴别变换的本质——白化变换加普通的线性鉴别变换。该方法的最大优点在于所获得的最优鉴别矢量同时具有正交性和统计不相关性。该方法对代数特征抽取具有普遍适用性。用ORL人脸数据库的数值实验，验证了该方法的有效性。

关键词：模式识别特征抽取鉴别分析广义最佳鉴别矢量集人脸识别

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区域水资源可持续利用评价理论模型与方法

陈守煜

《中国工程科学》 2001年第3卷第2期页码 33-38

摘要：

文章在论述区域水资源可持续利用与水资源承载能力关系的前提下，提出了区域水资源可持续利用评价的模糊模式识别理论、模型和方法。应用所建立的模型对汉中盆地水资源可持续利用的程度进行了评价，应用实例表明，理论模型严谨，方法简洁，评价结果合理可行。此方法也可用于区域社会经济可持续发展等的评价。

关键词：水资源可持续利用评价模式识别模糊性

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A minimized fluorescent chemosensor array utilizing carboxylate-attached polythiophenes on a chip for metal ions detection

Yui Sasaki, Xiaojun Lyu, Zhoujie Zhang, Tsuyoshi Minami

《化学科学与工程前沿（英文）》 2022年第16卷第1期页码 72-80 doi: 10.1007/s11705-021-2037-y

摘要： Chemosensor arrays have a great potential for on-site applications in real-world scenarios. However, to fabricate on chemosensor array a number of chemosensors are required to obtain various optical patterns for multi-analyte detection. Herein, we propose a minimized chemosensor array composed of only two types of carboxylate-functionalized polythiophene derivatives for the detection of eight types of metal ions. Upon recognition of the metal ions, the polythiophenes exhibited changes in their fluorescence intensity and various spectral shifts. Although both chemosensors have the same polymer backbone and recognition moiety, only the difference in the number of methylene groups contributed to the difference in the fluorescence response patterns. Consequently, the metal ions in aqueous media were successfully discriminated qualitatively and quantitatively by the chemosensor microarray on the glass chip. This study offers an approach for achieving a minimized chemosensor array just by changing the alkyl chain lengths without the necessity for many receptors and reporters.

关键词： metal ions polythiophene chemosensor array fluorescence pattern recognition

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过程神经网络的训练及其应用

何新贵,梁久祯,许少华

《中国工程科学》 2001年第3卷第4期页码 31-35

摘要：

研究过程神经网络的学习算法及其在过程模式识别中的应用。针对权值基展开的过程神经网络讨论了权值基的选取规则和对采样曲线的标准化处理问题，给出了含一个隐层的过程神经网络的误差反传播学习算法。以聚合化学反应和渗流实验两个具体实例验证了算法的有效性，也说明了过程神经网络的广泛应用前景。

关键词：过程神经网络学习算法模式识别化学反应渗流

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钱学森与思维科学

卢明森

《中国工程科学》 2002年第4卷第2期页码 8-15

摘要：

文章分析了钱学森倡导建立思维科学的背景和必要性，介绍了钱学森关于思维科学研究的对象、基本道路、思想来源的一系列论述，阐述了钱学森倡导建立的思维科学是现代科学技术体系中的11个大部门之一，它包含基础科学、技术科学与工程技术三个层次，分别介绍了各个层次近20年来所取得的初步成果。

关键词：认知科学思维科学抽象思维形象思维创造性思维模式识别

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第二届中国模式识别与计算机视觉学术会议（Chinese Conference on Pattern Recognition and Computer Vision）

会议日期： 2019年11月08日

会议地点：中国/陕西/西安

主办单位：中国图象图形学学会、中国计算机学会、中国自动化学会、中国人工智能学会

Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

《机械工程前沿（英文）》 2006年第1卷第3期页码 313-316 doi: 10.1007/s11465-006-0026-y

摘要： It is a very important task to automatically fix the number of die in the image recognition system of a fully automatic die bonder. A multiobjective image recognition algorithm based on clustering Genetic Algorithm (GA), is proposed in this paper. In the evolutionary process of GA, a clustering method is provided that utilizes information from the template and the fitness landscape of the current population. The whole population is grouped into different niches by the clustering method. Experimental results demonstrated that the number of target images could be determined by the algorithm automatically, and multiple targets could be recognized at a time. As a result, time consumed by one image recognition is shortened, the performance of the image recognition system is improved, and the atomization of the system is fulfilled.

关键词： clustering different recognition algorithm Algorithm multiobjective

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Advances in tissue state recognition in spinal surgery: a review

Hao Qu, Yu Zhao

《医学前沿（英文）》 2021年第15卷第4期页码 575-584 doi: 10.1007/s11684-020-0816-3

摘要： Spinal disease is an important cause of cervical discomfort, low back pain, radiating pain in the limbs, and neurogenic intermittent claudication, and its incidence is increasing annually. From the etiological viewpoint, these symptoms are directly caused by the compression of the spinal cord, nerve roots, and blood vessels and are most effectively treated with surgery. Spinal surgeries are primarily performed using two different techniques: spinal canal decompression and internal fixation. In the past, tactile sensation was the primary method used by surgeons to understand the state of the tissue within the operating area. However, this method has several disadvantages because of its subjectivity. Therefore, it has become the focus of spinal surgery research so as to strengthen the objectivity of tissue state recognition, improve the accuracy of safe area location, and avoid surgical injury to tissues. Aside from traditional imaging methods, surgical sensing techniques based on force, bioelectrical impedance, and other methods have been gradually developed and tested in the clinical setting. This article reviews the progress of different tissue state recognition methods in spinal surgery and summarizes their advantages and disadvantages.

关键词： spinal surgery tissue state recognition image force sensing bioelectrical impedance

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View-invariant human action recognition via robust locally adaptive multi-view learning

Jia-geng FENG,Jun XIAO

《信息与电子工程前沿（英文）》 2015年第16卷第11期页码 917-920 doi: 10.1631/FITEE.1500080

摘要： Human action recognition is currently one of the most active research areas in computer vision. It has been widely used in many applications, such as intelligent surveillance, perceptual interface, and content-based video retrieval. However, some extrinsic factors are barriers for the development of action recognition; e.g., human actions may be observed from arbitrary camera viewpoints in realistic scene. Thus, view-invariant analysis becomes important for action recognition algorithms, and a number of researchers have paid much attention to this issue. In this paper, we present a multi-view learning approach to recognize human actions from different views. As most existing multi-view learning algorithms often suffer from the problem of lacking data adaptiveness in the nearest neighborhood graph construction procedure, a robust locally adaptive multi-view learning algorithm based on learning multiple local L1-graphs is proposed. Moreover, an efficient iterative optimization method is proposed to solve the proposed objective function. Experiments on three public view-invariant action recognition datasets, i.e., ViHASi, IXMAS, and WVU, demonstrate data adaptiveness, effectiveness, and efficiency of our algorithm. More importantly, when the feature dimension is correctly selected (i.e.,>60), the proposed algorithm stably outperforms state-of-the-art counterparts and obtains about 6% improvement in recognition accuracy on the three datasets.

关键词： View-invariant Action recognition Multi-view learning L1-norm Local learning

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Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

《环境科学与工程前沿（英文）》 2021年第15卷第6期 doi: 10.1007/s11783-021-1430-6

摘要：

• UV-vis absorption analyzer was applied in drainage type online recognition.

关键词： Drainage online recognition UV-vis spectra Derivative spectrum Convolutional neural network

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Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

《信息与电子工程前沿（英文）》 2015年第16卷第12期页码 1046-1058 doi: 10.1631/FITEE.1500085

摘要： With the development of face recognition using sparse representation based classification (SRC), many relevant methods have been proposed and investigated. However, when the dictionary is large and the representation is sparse, only a small proportion of the elements contributes to the 1-minimization. Under this observation, several approaches have been developed to carry out an efficient element selection procedure before SRC. In this paper, we employ a metric learning approach which helps find the active elements correctly by taking into account the interclass/intraclass relationship and manifold structure of face images. After the metric has been learned, a neighborhood graph is constructed in the projected space. A fast marching algorithm is used to rapidly select the subset from the graph, and SRC is implemented for classification. Experimental results show that our method achieves promising performance and significant efficiency enhancement.

关键词： Face recognition Sparse representation Manifold structure Metric learning Subset selection