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4D Graphical representation research of DNA sequences

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International Journal of Biomathematics 2015年第1期8卷 47-58页

作者： Chengjie Tan Shanshan Li Ping Zhu School of Science Jiangnan University Wuxi Jiangsu 214122 P. R. China

Graphical representation of DNA sequences is a key component in studying biological problems. In order to gain new insights in DNA sequences, this paper combined the digitized methods of single-base, base pairs and coding in triplet bases with the times of base appearing, and then a novel 4D graphical representation method of DNA sequences was put forward. It was a one-to-one correspondence of the arbitrary DNA sequence and 4D graphical representation, that avoided causing non-unique 4D graphical representation and overlapping lines. The method could reflect the biological information features of DNA sequence more comprehensively and effectively without any losses. Based on the 4D graphical representation, we used the geometric center of 4D graphical representation as eigenvalue of DNA sequences analyses, which kept the original features of the data, and then established the euclidean distances and included angles between vectors＇ ter- minal point for similarity analyses of the first extron of the beta-globulin gene among 11 species. Finally, we established the graph of systematic hierarchical cluster analysis of 11 species to observe more easily the relationship between species. A positive outcome was reached, and the results were in accord with biological taxonomy, which also supported the rationality and effectiveness of the novel 4D graphical representation.

关键词： euclidean distance graphical representation geometric center similarity analysis.

SERIALLY CONCATENATED CONTINUOUS PHASE MODULATION WITH REDUCED ITERATIVE DEMODULATION AND DETECTION

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Journal of Electronics(China) 2007年第1期24卷 16-22页

作者： Sun Jinhua Li Jiandong Jin Lijun State Key Lab. of Integrated Service Networks Xidian University Xi＇an 710071 China

A reduced state Soft Input Soft Output (SISO) a posteriori probability algorithm for Seri-ally Concatenated Continuous Phase Modulation (SCCPM) is proposed in this paper. Based on the Reduced State Sequence Detection (RSSD),it has more general form compared with other reduced state SISO algorithms. The proposed algorithm can greatly reduce the state number,thus leads to the computation complexity reduction. It also minimizes the degradation in euclidean distance with decision feedback in the reduced state trellis. Analysis and simulation results show that the perform-ance degradation is little with proper reduction scheme.

关键词： Concatenated codes Continuous Phase Modulation (CPM) Soft Input Soft Output (SISO) euclidean distance

Novel Mapping Design Criterion for BICM-ID with Square QAM Constellations

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Journal of Beijing Institute of Technology 2003年第4期12卷 385-389页

作者：刘林南费泽松赵胜辉匡镜明 Department of Electronic Engineering

Mapping design criteria of bit-interleaved coded modulation with iterative decoding (BICM-ID) with square 16QAM are analyzed. Three of the existing criteria are analyzed and compared with each other. Through the comparison, two main characters of the mapping design criteria are found. They are the harmonic mean of the minimum squared euclidean distance and the average of Hamming distances with the nearest euclidean distance. Based on these two characters, a novel mapping design criterion is proposed and a label mapping named mixed mapping is searched according to it. Simulation results show that mixed mapping performs better than the other mappings in BICM-ID system.

关键词： bit-interleaved coded modulation with iterative decoding (BICM-ID) 16 quadrature amplitude modulation (16QAM) design criteria Hamming distance euclidean distance

Multi-modal Image Matching Method Based on Optimized Wavelet Transform Modular Maximum and DAISY Descriptor

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Multi-modal Image Matching Method Based on Optimized Wavelet...

2011 3rd International Conference on Signal Processing Systems(ICSPS 2011)

作者： Zhenbing Zhao Sasa Wang Ping Yu Qin Wang School of Electrical and Electronic Engineering North China Electric Power University

ISBN: (纸本)9781457701726

The existing matching methods of multi-modal image have poor performance, so this paper proposes a kind of matching method of multi-modal image based on optimized wavelet transform modular maximum and DAISY descriptor. The method is divided into three steps: firstly, the optimized wavelet transform modular maximum is used to extract feature points;secondly, a fast local DAISY descriptor is introduced to describe feature points;finally, the euclidean distance(ED) and the RANdom SAmple Consensus (RANSAC) are used in coarse and fine matching for the descriptor. Experiment results show that the method has a higher matching precision than the traditional method.

关键词： Multi-modal image Feature points extraction Wavelet transform modular maximum DAISY euclidean distance RANSAC

Chinese Character Recognition Based on Energy Value of the Dual Peripheral Coordinates

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Chinese Character Recognition Based on Energy Value of the D...

2015年中国智能自动化学术会议

作者： Li Yuan Tian Wang Zhiyan Li Wei Liu School of Automation and Electrical Engineering University of Science and Technology Beijing

Feature extraction is the most important part in the process of Chinese character recognition(CCR). When there are such factors as deformity, tilt, uneven illumination existing on the text images, conventional recognition methods such as cellular feature or the linear density characteristics show a degrade on recognition performance. In this paper, we propose a new feature extraction method for CCR based on the energy value of the dual peripheral coordinates. During registration,training samples of the Chinese characters are transformed into binary images. Then the character feature vector is extracted by calculating the square of the coordinates of the peripheral points. During recognition, test samples of Chinese characters are isolated from text images by the steps of image correction, layout analysis, and image segmentation, then the feature vector of dual energy value of the peripheral coordinates is extracted. Character recognition is achieved by searching the minimum euclidean distance between the testing samples features and the registered training samples features. Experimental results on scanned images and photo images show the effectiveness and accuracy of the feature of dual peripheral coordinate energy value approached in this paper.

关键词： Chinese character recognition Character feature extraction euclidean distance

Air Target Intention Recognition Based on Further Clustering and Sample Expansion

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Air Target Intention Recognition Based on Further Clustering...

第37届中国控制会议

作者： Zheng Zhang Yang Qu Hongkun,Liu Army Armored Forces Academy of PLA Bengbu campus

The Air Target Intention Recognition（ATIR） is an unavoidable problem during the air defense process and the small sample size is one problem in neural network learning. Concerning the first problem, the further clustering algorithm, which is established based on euclidean distance, provides a new method of clustering which can make full use of the intrinsic information of sample;Concerning the second problem, the sample expansion algorithm is put forward to increase the number of sample and promote the prediction accuracy. Then, by using Neural Network,an instance of ATIR is studied. The result shows that the combination of further clustering algorithm and the sample expansion method algorithm is effective.

关键词： euclidean distance Sample Expansion Neural Network Air Target Intention Recognition

A New MCDM Method in Transmission Network Planning Based on Gray Correlation Degree and TOPSIS

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A New MCDM Method in Transmission Network Planning Based on ...

第二十七届中国控制会议

作者： Fan Liguo,Li Yanhong School of Business Administration,North China Electric Power University,Baoding 071003,P.R.China

Aiming at solving multi-criteria decision（MCDM） problems in transmission network planning,a new decision-making method based on gray correlation degree and TOPSIS is *** the basis of introducing the concept of gray correlation degree into traditional TOPSIS,it combines the euclidean distance with gray correlation degree and establishes a new kind of relative similarity degree to decide the quality of *** method could overcome error originated from biased thinking due to subjective and objective factors in decision-making problem when using single method and boosts up reliability of evaluation result in transmission network planning.

关键词： Multi-criteria decision making TOPSIS Gray correlation degree euclidean distance Relative similarity degree Transmission network planning

Supervised Identification Algorithm on Detection of Foreign Fibers in Raw Cotton

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Supervised Identification Algorithm on Detection of Foreign ...

第24届中国控制与决策会议

作者： Ling Ouyang 1 , Hongtao Peng 2 , Dongyun Wang 3 ,Yongping Dan 4 , Fanghua Liu 5 1, 2, 3, 4, 5. School of Electrical and Information, Zhongyuan University of Technology, Zhengzhou 450007

Foreign fibers accounted for a small proportion in cotton, but there is serious impact on the quality of textile. Foreign fibers are removed by hand, which is low efficiency. Generally, the methods of fixed threshold are used to identify foreign fibers in cotton, but high speed flow of cotton is easy to result in fluctuations on light, the color of captured images will be changed accordingly, then misidentification possibility will be increased. But the suitable amount of sample libraries are used in the identification algorithm of supervised classification, which eliminate this defect to meet the requirements of accuracy and real-time. In this paper, according to the character of image gray of foreign fibers in cotton, and mathematical model is established. Further, important image features are enhanced by image processing, foreign fibers’ characters are drawn. At last, euclidean distance and k-nearest neighbor classification are adopted in identification algorithm, and finally foreign fibers are identified.

关键词： foreign fibers identification euclidean distance k-nearest neighbor classification algorithm

A New Approach of Gross Errors Detection for Soft Sensing Data Based on Cluster Analysis

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A New Approach of Gross Errors Detection for Soft Sensing Da...

第二十九届中国控制会议

作者： TIAN Hui-Xin 1,MENG Bo 1,LI Kun 2 1.School of Electrical Engineering&Automation,Tianjin Polytechnic University,Tianjin 300160,P.R.China2.School of Management,Tianjin Polytechnic University,Tianjin 300160,P.R.China

Modeling data plays a very important role in the process of establishing an accurate soft sensing *** errors detection for modeling data could ensure the good quality of modeling data,and then ensure the good performance of soft sensor *** this paper,a new gross errors detection method based on cluster analysis is *** the traditional methods,the new method does not rely on the mechanism *** the new method is suitable to the characters of soft sensor better.A new cluster algorithm is presented to detect the gross errors of modeling data based on the special characters of soft *** new clustering algorithm detects the gross errors by analyzing the euclidean distance between the data points and the center of data *** experiments demonstrate that the new detection approach based on new clustering method could detect the gross error effectively.

关键词： Gross Errors Detection Soft Sensor Cluster Analysis Mountain Method euclidean distance