• Title/Summary/Keyword: Information matrix

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Design of FIR/IIR Lattice Filters using the Circulant Matrix Factorization (Circulant Matrix Factorization을 이용한 FIR/IIR Lattice 필터의 설계)

  • Kim Sang-Tae;Lim Yong-Kon
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.41 no.1
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    • pp.35-44
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    • 2004
  • We Propose the methods to design the finite impulse response (FIR) and the infinite impulse response (IIR) lattice filters using Schur algorithm through the spectral factorization of the covariance matrix by circulant matrix factorization (CMF). Circulant matrix factorization is also very powerful tool used for spectral factorization of the covariance polynomial in matrix domain to obtain the minimum phase polynomial without the polynomial root finding problem. Schur algorithm is the method for a fast Cholesky factorization of Toeplitz matrix, which easily determines the lattice filter parameters. Examples for the case of the FIR filter and for the case of the In filter are included, and performance of our method check by comparing of our method and another methods (polynomial root finding and cepstral deconvolution).

Generic Text Summarization Using Non-negative Matrix Factorization (비음수 행렬 인수분해를 이용한 일반적 문서 요약)

  • Park Sun;Lee Ju-Hong;Ahn Chan-Min;Park Tae-Su;Kim Ja-Woo;Kim Deok-Hwan
    • Annual Conference of KIPS
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    • 2006.05a
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    • pp.469-472
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    • 2006
  • 본 논문은 비음수 행렬 인수분해(NMF, non-negative matrix factorization)를 이용하여 문장을 추출하여 문서를 요약하는 새로운 방법을 제안하였다. 제안된 방법은 문장추출에 사용되는 의미 특징(semantic feature)이 비 음수 값을 갖기 때문에 잠재의미분석에 비해 문서의 내용을 정확하게 요약한다. 또한, 적은 계산비용을 통하여 쉽게 요약 문장을 추출할 수 있는 장점을 갖는다.

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A Novel Compressed Sensing Technique for Traffic Matrix Estimation of Software Defined Cloud Networks

  • Qazi, Sameer;Atif, Syed Muhammad;Kadri, Muhammad Bilal
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.10
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    • pp.4678-4702
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    • 2018
  • Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

Selection of the Optimal Location of Traffic Counting Points for the OD Travel Demand Estimation (기종점 수요추정을 위한 교통량 관측지점의 적정위치 선정)

  • 이승재;이헌주
    • Journal of Korean Society of Transportation
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    • v.21 no.1
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    • pp.53-63
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    • 2003
  • The Origin-Destination(OD) matrix is very important in describing transport movements in a region. The OD matrix can be estimated using traffic counts on links in the transport network and other available information. This information on the travel is often contained in a target OD matrix and traffic counts in links. To estimate an OD matrix from traffic counts, they are the major input data which obviously affects the accuracy of the OD matrix estimated, Generally, the quality of an estimated OD matrix depends much on the reliability of the input data, and the number and locations of traffic counting points in the network. Any Process regarding the traffic counts such as the amount and their location has to be carefully studied. The objective of this study is to select of the optimal location of traffic counting points for the OD matrix estimation. The model was tested in nationwide network. The network consists of 224 zones, 3,125 nodes and 6,725 links except to inner city road links. The OD matrix applied for selection of traffic counting points was estimated to 3-constrained entropy maximizing model. The results of this study follow that : the selected alternative to the best optimal counting points of six alternatives is the alternative using common links of OD matrix and vehicle-km and traffic density(13.0% of 6,725 links), however the worst alternative is alternative of all available traffic counting points(44.9% of 6,725 links) in the network. Finally, it should be concluded that the accuracy of reproduced OD matrix using traffic counts related much to the number of traffic counting points and locations.

Changing Image Resolution In A Block Transform Domain (임의의 직교 블록 변환 영역에서의 영상 크기 변환 방법)

  • Lee, Nam-Koo;Oh, Hyung-Suk;Kim, Won-Ha
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.1
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    • pp.49-55
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    • 2009
  • This paper develops a methodology for resizing the resolution of an image in an arbitrary block transform domain. To accomplish this, we represent the procedures resizing images in an orthogonal transform domain in the form of matrix multiplications from which the matrix scaling the image resolutions is produce. The experiments showed that the proposed method produces the reliable performances without increasing the computational complexity, compared to conventional methods when applied to various transforms.

The Toeplitz Circulant Jacket Matrices (The Toeplitz Circulant Jacket 행렬)

  • Park, Ju Yong;Kim, Jeong Su;Szollosi, Ferenc;Lee, Moon Ho
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.7
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    • pp.19-26
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    • 2013
  • In this paper we prove that all Jacket matrices are circulant and up to equivalence. This result leads to new constructions of Toeplitz Jacket(TJ) matrices. We present the construction schemes of Toeplitz Jacket matrices and the examples of $4{\times}4$ and $8{\times}8$ Toeplitz Jacket matrices. As a corollary we show that a Toeplitz real Hadamard matrix is either circulant or negacyclic.

A Logical Framework of Comparison Shopping Effectiveness and Comparison Challenge Methodology

  • Lee, Jae-Won
    • Proceedings of the CALSEC Conference
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    • 2005.03a
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    • pp.130-134
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    • 2005
  • This research describes the comparison broker's role and its effectiveness measurement using a developed logical framework of comparison shopping service. And verifies that seller-led comparison challenge method provide comparison information of products to buyers more efficiently. In electronic commerce, buyer's satisfaction of purchase (S) can be defined as an interactive function between seller's competitiveness vector (P) of products that supplied to the market, and buyer's informed level vector (B) of products that is known from a lot of sources. Then the buyer's informed level can be changed through the information analysis among products by transformation process using comparison matrix (C). So the role of comparison shopping is to construct a comparison matrix and to serve it to the buyers, and to change the buyer's informed level. The changed informed level influences a buyer's satisfaction, that improved satisfaction of purchase is defined as the effectiveness of comparison shopping. As a perfect provision and usage of comparison matrix is impossible cause of cognitive limit, the most efficient method for improving the comparison effectiveness is the comparison challenge that detects the comparison elements of the largest buyer's information efficiency, and then to be compared between elementary products selectively. This research verifies the substantial superiority of comparison challenge through television market data experiments.

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Face Recognition using Non-negative Matrix Factorization and Learning Vector Quantization (비음수 행렬 분해와 학습 벡터 양자화를 이용한 얼굴 인식)

  • Jin, Donghan;Kang, Hyunchul
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.3
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    • pp.55-62
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    • 2017
  • Non-negative matrix factorization (NMF) is one of the typical parts-based representation in which images are expressed as a linear combination of basis vectors that show the lcoal features or objects in the images. In this paper, we represent face images using various NMF methods and recognize their face identities based on extracted features using a learning vector quantization. We analyzed the various NMF methods by comparing extracted basis vectors. Also we confirmed the availability of NMF to the face recognition by verification of recognition rate of the various NMF methods.

The Present and Future of the Food Market in Northeast Asia: Confectionery Markets

  • Jeong, Han-Na-Ra;Moon, Junghoon
    • Agribusiness and Information Management
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    • v.4 no.1
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    • pp.41-47
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    • 2012
  • The Asian food market has been growing recently, due to the role played by major Asian countries, which include Korea, China, and Japan. This study is purposed to investigate the potential of the food market in these Northeast Asian countries and to suggest future direction for global food companies. For in-depth analysis, this study is limited in scope to the confectionery market and analyzes that market within two frameworks: first, the 'Market Attractiveness Matrix' which transforms the 'BCG Matrix' to fit into the food market in order to analyze the flow in the Asian confectionery market; and second, analysis of the potential growth of the market using a Category Development Index (CDI), which aids in understanding the growth potential of a market. The European food market has recently reached its capacity and is now experiencing a low growth rate (Data Monitor, 2011). It is time for food companies to find a new 'blue ocean' to avoid fierce competition in the mature markets of Europe. Therefore, this analysis of the confectionery market, using the Market Attractiveness Matrix and CDI will suggest opportune directions for global food companies.

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Mosaics Image Generation based on Mellin Transform (멜린 변환을 이용한 모자이크 이미지 생성)

  • 이지현;양황규
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.8
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    • pp.1785-1791
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    • 2003
  • This paper presents the mosaic method that the video sequence with shift and rotation information after Mellin Transform. The results are used to compute the projection matrix for each image registration. So before registration, we process camera calibration in order to reduce the image warp by camera and then compute the global projection matrix for image registration for reducing errors from rut image to last image. This paper describes the mosaic method that compute duplication and movement information quickly and robust noise using projection matrix on Mellin Transform.