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Principal component based classification for text-independent speaker identification

Principal component based classification for text-independen...

引用

international conference on soft computing, computing with Words and Perceptions in System Analysis, Decision and Control, ICSCCW

作者： Cemal Hanilçi Figen Ertaş Department of Electronic Engineering Uludag University Bursa Turkey

Classification based on Principal Component analysis has recently appeared in the literature in application to text-independent speaker identification. However, results have been reported for only clean speech data. In this paper, we evaluate the performance of principal component classifier for text-independent speaker identification on telephone speech. We then improve its identification performance using a Vector Quantization classifier in combination, through fusion of classifier scores. An identification rate of 78.27% has been obtained on the NTIMIT database, which is well above the best identification rate ever reported in the literature obtained by using only one type of feature set.

关键词： Classification algorithms Feature extraction Hidden Markov models Principal component analysis Vector quantization Speech analysis Spatial databases Telephony pattern recognition Clustering algorithms

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Dynamic power management based call pattern recognition for Telecommunication Equipments

Dynamic power management based call pattern recognition for ...

引用

NCM 2009 - 5th international Joint conference on Int. Conf. on Networked computing, Int. Conf. on Advanced Information Management and Service, and Int. Conf. on Digital Content, Multimedia Technology and its Applications

作者： Heo, Cheol-Kyun Shin, Dong-Ryeol Department of Mobile Communications Engineering Sungkyunkwan University Suwon Korea Republic of School of Information and Communication Engineering Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9780769537696

Lately around the world the Information and Communications Technology (ICT) industry has taken interest in reducing the power consumption of ICT equipment. Communications service providers are especially interested in the so-called Green-IT technology, hoping to reduce the power consumed by the large numbers of telecommunications equipment they operate in order to provide their services. Although a lot of research has been conducted into reducing power consumption, the developed methodologies are not effective to adapt them to telecommunication equipments. In this dissertation I will propose a method to actually reduce power consumption by implementing a Call pattern Reorganization-Dynamic Power Management (CPR-DPM)-based call pattern policy, which follows subscriber connection patterns over time, in telecommunications equipment (specifically equipment located in the Central Office) of IP Multimedia Subsystem (IMS)-based telecommunications networks. © 2009 IEEE.

关键词： Telecommunication equipment

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Granular computing and Rough Sets to Generate Fuzzy Rules

Granular Computing and Rough Sets to Generate Fuzzy Rules

引用

6th international conference on Image Analysis and recognition

作者： Guliato, Denise de Sousa Santos, Jean Carlo Univ Fed Uberlandia Fac Computacao Av Jodo Naves de Avila2121Bloco B BR-38400902 Uberlandia MG Brazil Med Assistida Computac Cient INCT MACC Uberlandia MG Brazil

ISBN: (纸本)9783642026102

In the recent years, rough set theory has been applied in diverse areas of research, however its application to classification problems is still a challenger. In this paper we present a new method to automatically generate fuzzy rules using an extension of rough sets. We use genetic algorithm to determine the granules of the knowledge to obtain the rough sets. The resulting classifier system based on the set of fuzzy rules was tested with the public databases: Iris, Wine, and Wdbc datasets, presenting accuracy rates of 100%, 100%, and 99%, respectively.

关键词： Rough set Fuzzy rule Fuzzy Classifier Fuzzy Membership Function Approximation Operators pattern Recogntion

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Multi-view Ear recognition Based on Moving Least Square Pose Interpolation

Multi-view Ear Recognition Based on Moving Least Square Pose...

引用

5th international conference on Intelligent computing

作者： Liu, Heng Zhang, David Zhang, Zhiyuan SW Univ Sci & Technol Sch Informat Engn Mianyang 621010 Peoples R China Shanghai Jiao Tong Univ Inst Image Processing & Pattern Recognit Shanghai 200240 Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong Peoples R China Harbin Inst Technol Shenzhen Grd Sch Bio Comp Res Ctr Harbin Peoples R China

ISBN: (纸本)9783642040191

Based on moving least square, a multi-view car pose interpolation and corresponding recognition approach is proposed. This work firstly analyzes the shape characteristics of actual trace caused by ear pose varying in feature space. Then according to training samples pose projection, we manage to recover the complete multi-view car pose manifold by using moving least square pose interpolation. The constructed multi-view ear pose manifolds can be easily utilized to recognize ear images captured under different views based on finding the minimal projection distance to the manifolds. The experimental results and some comparisons show the new method is superior to manifold learning method and B-Spline based recognition method.

关键词： Interpolation

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An Evolutionary Approach for Sample-Based Clustering on Microarray Data

引用

10th international Work-conference on Artificial Neural Networks (IWANN 2009)

作者： Glez-Pena, Daniel Diaz, Fernando Mendez, Jose R. Corchado, Juan M. Fdez-Riverola, Florentino Univ Vigo ESEI Escuela Super Ingn Informat Edificio PolitecnCampus Univ As Lagoas S-N Orense 32004 Spain Univ Valladolid Escuela Univ Informat Dept Informat E-40005 Segovia Spain Univ Salamanca Dept Informat Automat Salamanca Spain

ISBN: (纸本)9783642024801

Sample-based clustering is one of the most common methods for discovering disease subtypes as well as unknown taxonomies. By revealing hidden structures in microarray data, cluster analysis can potentially lead to more tailored therapies for patients as well as better diagnostic procedures. In this work, we present a novel method for automatically discovering clusters of samples which are coherent from a genetic point of view. Each possible cluster is characterized by a fuzzy pattern which maintains a fuzzy discretization of relevant gene expression values. Noise genes are identified and removed from the fuzzy pattern based on their probability of appearance. Possible clusters are randomly constructed and iteratively refined by following a probabilistic search and an optimization schema. Experimental results over publicly available microarray data show the effectiveness of the proposed method.

关键词： simulated annealing sample-based clustering discriminant fuzzy pattern microarray data

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A Novel Approach for Mining Association Rules on Sports Data using Principal Component Analysis: For Cricket match perspective

A Novel Approach for Mining Association Rules on Sports Data...

引用

IEEE international Advance computing conference

作者： UmaMaheswari, P. Rajaram, M. Anna Univ Sona Coll Technol Salem 636005 Tamil Nadu India Anna Univ Thanthai Periyar Inst Technol Vellore Tamil Nadu India

ISBN: (纸本)9781424429271

Sports coaches today have an access to a wide variety of information sources that describe the performance of their players. Cricket match data is highly available and rapidly growing in size which far exceeds the human abilities to analyze. Our major intention is to model an automated framework to identify specifics and correlations among play patterns, so as to haul out knowledge which can further be represented in the form of useful information in relevance to modify or improve coaching strategies and methodologies to confine performance enrichment at team level as well as individual. With this information, a coach can assess the effectiveness of certain coaching decisions and formulate game strategy for subsequent games. Since real time cricket data is too complex, Object-relational model is used to employ more sophisticated structure to store such data. Frequent pattern evaluation is imperative for sports be fond of cricket match data which facilitates recognition of main factors accounting for variances in data. While using simple apriori for interrelationship analysis, it is less time efficient because the raw data set which is too large and complex. On integrating association mining with Principal Component Analysis, the efficiency of mining algorithm is improved provided that Principal Component Analysis generates frequent patterns through statistical analysis and summarization not by repeated searching like other frequent patterns generation techniques. As the size and dimension of annotation database is large, Principal Component Analysis proceeds as a compression mechanism. Then the frequent patterns are analyzed for their interrelationship in order to generate interesting and confident rules of association.

关键词： Principal Component Analysis based association mining PCA enhanced apriori data mining sport data analysis Frequent pattern mining on ORDBM PCA on generalized data Dimensionality reduction on ORDBM

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Weighted Central Moment for pattern recognition: Derivation, Analysis of Invarianceness, and Simulation Using Letter Characters

Weighted Central Moment for Pattern Recognition: Derivation,...

引用

Asia international conference on Modeling & Simulation

作者： Rela Puteri Pamungkas Siti Mariyam Shamsuddin Soft Computing Research Group Faculty of Computer Science &Information System Universiti Teknologi Malaysia Skudai Johor Malaysia

ISBN: (纸本)9781424441549

Geometric moment invariant (GMI) is well known approach in pattern recognition. One of the weaknesses of GMI is in its invarianceness, where data or points concentrated near to the center-of-mass are neglected because of the existence of data or points that are far away from the center-of-mass. To solve this problem, Balslev *** has modified GMI method by adding a weighting function into GMIpsilas formula; thus we called it as Weighted Central Moment (WCM). WCM can increase noise tolerance for rotation/translation independent pattern recognition. In this paper, we present simulation results for characters with adjustable parameter alpha equal to 2/Rg. The experiments reveal that WCM yields intra-class results for identifying picture with different orientations. It also illustrates better inter-class distances in recognizing letter ldquogrdquo and ldquoqrdquo compared to GMI method.

关键词： pattern recognition pattern analysis Analytical models Solid modeling Computational modeling Computer simulation Asia Information analysis Computer science Information systems

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Proceedings of international conference on Methods and Models in Computer Science, ICM2CS09

Proceedings of International Conference on Methods and Model...

引用

international conference on Methods and Models in Computer Science, ICM2CS09

ISBN: (纸本)9789380043579

The proceedings contain 62 papers. The topics discussed include: intelligent detection of LSB stego anomalies in images using soft computing paradigms;human recognition using fusion of IRIS and ear data;an efficient approach for color image retrieval using Haar wavelet;swarm intelligence stability based on stochastic diffusion search;delta compression effect on smart card fingerprint verification system;an object-oriented conceptual level design for web data model;performance analysis of block matching criterion in video data on embedded processor using VHDL;medical image thresholding scheme using Atanassov intuitionistic fuzzy set;on locking conditions in m-sequence generators for the use in digital watermarking;performance simulation of Tahoe, Reno, New Reno and SACK over terrestrial and geostationary satellite links;and cryptanalysis of password authentication schemes: current status and key issues.

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Data preprocessing in SVM-based keywords extraction from scientific documents

Data preprocessing in SVM-based keywords extraction from sci...

引用

2009 4th international conference on Innovative computing, Information and Control, ICICIC 2009

作者： Wu, Chunguo Marchese, Maurizio Wang, Yufei Krapivin, Mikalai Wang, Chaoyong Li, Xitong Liang, Yanchun College of Computer Science and Technology Jilin University Changchun 130012 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100080 China Italy Department of Fundamental Sciences Jilin Teacher's Institute of Engineering and Technology Changchun 130021 China

ISBN: (纸本)9780769538730

Scientific documents are unstructured data consisting of natural language and hard for scientists to read and manage. Keywords are very helpful for scientists to search the related documents and know about their contents in a prompt way. In this paper we investigate a kind of data preprocessing technique used in SVM-based keyword extraction from scientific documents. Four definitions of regular scientific documents are proposed, and the analysis on the experimental results is performed based on the proposed definitions. The experimental results confirm the intuition that abstract is important for keywords extraction. © 2009 IEEE.

关键词： Support vector machines

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Fault tolerant interval fusion for moving vehicle classification in wireless sensor networks

Fault tolerant interval fusion for moving vehicle classifica...

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Institution of Engineering and Technology international Communication conference on Wireless Mobile and computing

作者： Liu, C.T. Huo, H. Fang, T. Li, D.R. Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781849191388

Faults of sensor data will always present in sensor networks because of unreliable communication links, measurement interference and harsh environment. Developing fusion algorithms that can tolerate faults is necessary for reliable sensor network applications. In this paper, we study the fault tolerant fusion for moving vehicle classification based on Marzullo's interval fusion algorithm. The unreliable sensor data are represented using interval estimations. To reduce communication cost, quantized interval representation is adopted. Simulation results demonstrate the validity of the interval fusion algorithm. By using quantized representation, the communication cost is reduced.

关键词： Wireless sensor networks

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