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共 3334 条记录，以下是2911-2920 订阅

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Denosing and smoothing for oil well data base on discrete stationary wavelet transform

Denosing and smoothing for oil well data base on discrete st...

引用

5th international conference on Wavelet Analysis and pattern recognition

作者： Zhang, Xiao-Wei Xu, Yan-Xin Xing, Jia Beijing Gen Technol Dev Co Ltd Beijing 100871 Peoples R China Harbin Univ Sci & Technol Appl Sci Coll Harbin 150080 Peoples R China Harbin Norm Univ Dept Math Harbin 150500 Peoples R China Tianjin Univ Technol & Educ Dept Math & Phys Tianjin 300222 Peoples R China

ISBN: (纸本)9781424410651

In oil well data analysis, for the existence of noises and the effort of singularity points, indention distribution is appears and normal analysis work is affected. For the redundant characters of discrete stationary wavelet transform, mid-way threshold method is applied to remove noises disturbance and smooth the whole procedure data. that is 10 smooth data by using de-noising method Further more, adjusted modulus can be elected h? different slates and requirement of engineering technology for measuring data is satisfied.

关键词： oil well discrete stationary wavelet transform mid-way threshold

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Error protection method for embedded wavelet codec

Error protection method for embedded wavelet codec

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5th international conference on Wavelet Analysis and pattern recognition

作者： Ding, Xue-Wen Yang, Zhao-Xuan Wang, Zeng-Min Zheng, Hong-Xing Tianjin Univ Sch Elect Informat Engn Tianjin 300072 Peoples R China Tianjin Univ Technol & Educ Sch Elect Informat Engn Tianjin 300222 Peoples R China

ISBN: (纸本)9781424410651

this paper presents an error protection method for embedded wavelet codec by combining data hiding with error concealment. For the lowest frequency coefficients, a prolection scheine based data hiding is peifol-ined. the lowest frequency coefficients, which are taken as the hidden data, are extracted from the compressed bilstream, and embedded back into the same bitstream. the restored hidden data is used to conceal errors. the coefficients that cannot be recovered in other high frequency coefficients reconstruction are predicted through linear interpolation based oil inter-subband correlation. Experimental results show that the proposed method achieves good and stable error performance with minimal additional redundancy.

关键词： sPIHT coding error protection data hiding error concealment

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A new method for constructing clustering ensembles

A new method for constructing clustering ensembles

引用

5th international conference on Wavelet Analysis and pattern recognition

作者： Luo, Hui-Lan Xie, Xiao-Bing Li, Kang-Shun Jiangxi Univ Sci & Technol Sch Informat Engn Ganzhou 341000 Peoples R China

ISBN: (纸本)9781424410651

there are some general procedures to generate the clusterings in clustering ensembles. One can apply different algorithms to create different clusterings of the data. Some clustering algorithms like k-means require initialization Of parameters. Different initializations can lead to different clustering results. the parameters of a clustering algorithm, such as the number of clusters, can be altered to create different data clusterings. Different versions of the data can also be used as the input to the clustering algorithm, leading to different partitions. In this paper, we propose a new scheme for constructing multiple independent clusterings using additional artificially generated data. then, we compare our new method with seven general clustering ensemble constructing methods. the experiments show that our approach can achieve higher or comparable performance than the other methods.

关键词： clustering ensemble artificial data resampling

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A kind of trading off algorithm of object classification based on intelligent data fusion

A kind of trading off algorithm of object classification bas...

引用

5th international conference on Wavelet Analysis and pattern recognition

作者： Pan, Xiu-Qin Lu, Yong Zhao, Yue Cao, Yong-Cun Sun, Yuan Cent Univ Sch Math & Comp Sci Beijing 100081 Peoples R China

ISBN: (纸本)9781424410651

A kind of trading off algorithm off target classification combined with double mode intelligent fusion is presented, Applying neuron-fuzzy technique to the synthesis of the complementary information between radar and infrared, through combining neuron-fuzzy, technique with D-S evidence fusion theory, the ability, of target classification could be improved At the same time, according to the effective defection range of sensors, reasonably select the target features that can ensure the accurate target classification so that the computation load of the algorithm can be largely decreased compared to the infrared single model fusion. Simulalion results illustrate that the trading off algorithm is effective.

关键词： fusion classification fuzzy neural network

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Study of myocardial infraction feature extraction using subjective introduction based method

Study of myocardial infraction feature extraction using subj...

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5th international conference on Wavelet Analysis and pattern recognition

作者： Ge, Ding-Fei Sun, Li-Hui Zhejiang Univ Sci & Technol Sch Informat & Elect Engn Hangzhou 310012 Peoples R China

ISBN: (纸本)9781424410651

Most of the existing studies on myocardial infraction (MI) feature extraction are based on certain important components. the subjective significance based method was introduced into the feature extraction from an entire ECG segment for the classification in the paper. the method was employed to discriminate the assumed prior class from the other classes and separate each of the classes at the same time. the data in the analysis including healthy control (HC), myocardial infraction in early stage and acute myocardial infraction (AMI) was collected from PTB diagnostic ECG database which is the latest public database for various research purposes. the results show that the proposed method can obtain the effective features from the ECGs with 12-leads for the classification purpose.

关键词： myocardial infraction features classification subjective significance hyperdimensional data

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Advances in Neural Networks - ISNN 2007 2007

引用

丛书名： Lecture Notes in Computer Science

2007年

作者： Derong Liu Shumin Fei Zeng-Guang Hou Huaguang Zhang Changyin Sun

ISBN: (数字)9783540723950

ISBN: (纸本)9783540723943

the three volume set LNCS 4491/4492/4493 constitutes the refereed proceedings of the 4th international Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007. the 262 revised long papers and 192 revised short papers presented were carefully reviewed and selected from a total of 1.975 submissions. the papers are organized in topical sections on neural fuzzy control, neural networks for control applications, adaptive dynamic programming and reinforcement learning, neural networks for nonlinear systems modeling, robotics, stability analysis of neural networks, learning and approximation, data mining and feature extraction, chaos and synchronization, neural fuzzy systems, training and learning algorithms for neural networks, neural network structures, neural networks for pattern recognition, SOMs, ICA/PCA, biomedical applications, feedforward neural networks, recurrent neural networks, neural networks for optimization, support vector machines, fault diagnosis/detection, communications and signal processing, image/video processing, and applications of neural networks.

关键词： Neural networks (Computer science) Congresses. Neural computers Congresses.

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A feature extraction method suitable for multi-channel sensor data

A feature extraction method suitable for multi-channel senso...

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5th international conference on Wavelet Analysis and pattern recognition

作者： Sun, Li-Hui Zhejiang Univ Sci & Technol Sch Informat & Elect Engn Hangzhou 310012 Peoples R China

ISBN: (纸本)9781424410651

In order to obtain more significant information, the increasing hyper-dimensional data is acquired from multi-channel sensors, but the amount of data becomes very large. the quality of the data must be reduced for the data processing and transmission. the central problem is how, to extract the significant features from these data for these purposes. Optimal discrimination plane (ODP) technique based on Fisher's criterion method was developed to reduce the data in the paper. the patterns were projected onto the two orthogonal vectors that built up the ODP, and two-dimensional feature vectors were attained and utilized as features to represent the patterns. Electrocardiogram signals were applied to the analysis as an example in this study A quadratic discriminant function (QDF) based classifier and a threshold vector based classifier were employed to measure the performance of the extracted feature, respectively. the results show the proposed ODP is an effective and feasible technique to extract the features from the hyper-dimensional time series data.

关键词： multi-channel sensor data feature extraction classification

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Segmentation of nuclei in confocal image stacks using performance based thresholding

Segmentation of nuclei in confocal image stacks using perfor...

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4th IEEE international Symposium on Biomedical Imaging

作者： Beaver, William Kosman, David Tedeschi, Gary Bier, Ethan McGinnis, William Freund, Yoav Univ Calif San Diego Dept Comp Sci & Engn La Jolla CA 92093 USA Univ Calif San Diego Dept Cell & Dev Biol La Jolla CA 92093 USA

ISBN: (纸本)9781424406715

Combinatorial Transcriptional Fluorescent In Situ Hybridization (CT-FISH) is a confocal fluorescence imaging technique enabling the detection of multiple active transcription units in individual interphase diploid nuclei. As improved combinatorial labeling methods allow simultaneous measurement of gene activities to expand from five genes in a single embryo or tissue section to upward of twenty genes, transforming image stacks into usable data becomes an increasingly labor intensive task. In this paper we describe our progress towards a method for the computational analysis of confocal images from Drosophila melanogastar that involves the segmentation of the cell nuclei and of nascent transcription sites of specific genes. Using image processing and machine learning algorithms, we allow experimentalists to reiteratively tune and improve the analysis system to reflect biological reality.

关键词： image processing image segmentation machine vision pattern recognition

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learning graph matching

Learning graph matching

引用

11th IEEE international conference on Computer Vision

作者： Caetano, Tiberio S. Cheng, Li Le, Quoc V. Smola, Alex J. NICTA Stat Machine Learning Program Canberra ACT 0200 Australia

ISBN: (纸本)9781424416301

As a fundamental problem in pattern recognition, graph matching has found a variety of applications in the field of computer vision. In graph matching, patterns are modeled as graphs and pattern recognition amounts to finding a correspondence between the nodes of different graphs. there are many ways in which the problem has been formulated, but most can be cast in general as a quadratic assignment problem, where a linear term in the objective function encodes node compatibility functions and a quadratic term encodes edge compatibility functions. the main research focus in this theme is about designing efficient algorithms for solving approximately the quadratic assignment problem, since it is NP-hard. In this paper, we turn our attention to the complementary problem: how to estimate compatibility functions such that the solution of the resulting graph matching problem best matches the expected solution that a human would manually provide. We present a method for learning graph matching: the training examples are pairs of graphs and the "labels" are matchings between pairs of graphs. We present experimental results with real image data which give evidence that learning can improve the performance of standard graph matching algorithms. In particular, it turns out that linear assignment with such a learning scheme may improve over state-of-the-art quadratic assignment relaxations. this finding suggests that for a range of problems where quadratic assignment was thought to be essential for securing good results, linear assignment, which is far more efficient, could be just sufficient if learning is performed. this enables speed-ups of graph matching by up to 4 orders of magnitude while retaining state-of-the-art accuracy.

关键词： Computer vision

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Approximate inferring of goal-oriented Credal network

Approximate inferring of goal-oriented Credal network

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5th international conference on Wavelet Analysis and pattern recognition

作者： Li, Yu-Ling Wu, Qi-Zong Henan Univ Inst Data & Knowledge Engn Kaifeng 475001 Henan Peoples R China Beijing Inst Technol Sch Management & Econom Beijing 100081 Peoples R China

ISBN: (纸本)9781424410651

Approximate inferring approach of Credal network based on Ant Colony Algorithms is put forward Considering g network inferring of goal-oriented in Bayesian network for the variable decision-maker is interested in liven some evidence, the paper gives arithmetic for acquiring equivalent Credal network structure of goal-oriented Selecting of these vertexes in Credal network is considered as a multistage decision-making. Based on this, Ant Colony Algorithms is applied for Credal network approximate inferring to reuse the vertexes of high probability of each variable in order to improve of efficiency of inferring arithmetic and avoid some unnecessary computation. Finally, it shows the validity of the approach by simple analysis for a complex Credal network model.

关键词： Bayesian network Credal network goal-oriented Ant Colony Algorithms approximate inferring

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