• Title/Summary/Keyword: Least Squares Algorithm

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OFDM Channel Estimation with Jammed Pilot Excision Method under Narrow-Band Jamming (협대역 재밍환경에서 재밍된 파일럿 제거 방법을 이용한 OFDM시스템의 채널추정에 관한 연구)

  • Han, Myeong-Su;Yu, Tak-Ki;Kim, Ji-Hyung;Kwak, Kyung-Chul;Han, Seung-Youp;Hong, Dae-Sik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.2C
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    • pp.166-173
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    • 2007
  • In Orthogonal Frequency Division Multiplexing (OFDM) systems, Narrow-Band Jamming (NBJ) over pilot tones used for channel estimation degrades the system performance. In this paper, we propose a new jammed pilot detection and elimination algorithm to overcome this problem. Moreover, the average Mean-Squared Error (MSE) on one OFDM symbol both under jammed and removed pilot subcarrier is analyzed. And then, the Symbol Error Rate (SER) performance of the channel estimation scheme using the proposed algorithm is evaluated by simulation. We can confirm that the channel estimator with the proposed algorithm improves the channel estimation performance at a high jamming power.

Fast Remote Detection Algorithms for Chemical Gases Using Pre-Detection with a Passive FTIR Spectrometer (수동형 FTIR 분광계에서 초동 탐지 기법을 이용한 고속 원거리 화학 가스 탐지 알고리즘)

  • Yu, Hyeonggeun;Park, Dongjo;Nam, Hyunwoo;Park, Byeonghwang
    • Journal of the Korea Institute of Military Science and Technology
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    • v.21 no.6
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    • pp.744-751
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    • 2018
  • In this paper, we propose a fast detection and identification algorithm of chemical gases with a passive FTIR spectrometer. We use a pre-detection algorithm that can reduce the spatial region effectively for gas detection and the candidates of the target. It is possible to remove background spectra effectively from measured spectra with the least-squares method. The CC(Correlation Coefficients) and the SNR(Signal-to-Noise Ratio) methods are used for the detection of target gases. The proposed pre-detection algorithm allows the total process of chemical gas detection to be performed with lower complexity compared with the conventional algorithms. This paper can help developing real-time chemical detection instruments and various applications of FTIR spectrometers.

Comparison among Gamma(${\gamma}$) Line Systems for Non-Linear Gamma Curve (비선형 감마 커브를 위한 감마 라인 시스템의 비교)

  • Jang, Won-Woo;Lee, Sung-Mok;Ha, Joo-Young;Kim, Joo-Hyun;Kim, Sang-Choon;Kang, Bong-Soon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.2
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    • pp.265-272
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    • 2007
  • This proposed gamma (${\gamma}$) correction system is developed to reduce the difference between non-linear gamma curve produced by a typical formula and result produced by the proposed algorithm. In order to reduce the difference, the proposed system is using the Least Squares Polynomial which is calculating the best fitting polynomial through a set of points which is sampled. Each system is consisting of continuous several kinds of equations and having their own overlap sections to get more precise. Based on the algorithm verified by MATLAB, the proposed systems are implemented by using Verilog-HDL. This paper will compare the previous algorithm of gamma system such as Existing system with Seed Table with the latest that such as Proposed system. The former and the latter system have 1, 2 clock latency; each 1 result per clock. Because each of the error range (LSB) is $1{\sim}+1,\;0{\sim}+36$, we can how that Proposed system is improved. Under the condition of SAMSUNG STD90 0.35 worst case, each gate count is 2,063, 2,564 gates and each maximum data arrival time is 29.05[ns], 17.52[ns], respectively.

ARMA System identification Using GTLS method and Recursive GTLS Algorithm (GTLS의 ARMA시트템식별에의 적용 및 적응 GTLS 알고리듬에 관한 연구)

  • Kim, Jae-In;Kim, Jin-Young;Rhee, Tae-Won
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.3
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    • pp.37-48
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    • 1995
  • This paper presents an sstimation of ARMA coefficients of noisy ARMA system using generalized total least square (GTLS) method. GTLS problem for ARMA system is defined as minimizing the errors between the noisy output vectors and estimated noisy-free output. The GTLS problem is solved in closed form by eigen-problem and the perturbation analysis of GTLS is presented. Also its recursive solution (recursive GTLS) is proposed using the power method and the covariance formula of the projected output error vector into the input vector space. The simulation results show that GTLS ARMA coefficients estimator is an unbiased estimator and that recursive GTLS achieves fast convergence.

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Estimation of VOCs Affecting a Used Car Air Conditioning Smell via PLSR (부분최소자승법을 이용한 중고차 에어컨냄새 원인물질 추정)

  • You, Hanmin;Lee, Taehee;Sung, Kiwoo
    • Transactions of the Korean Society of Automotive Engineers
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    • v.21 no.6
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    • pp.175-182
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    • 2013
  • Lately, customers think highly of the emotional satisfaction and as a result, issues on odor are matters of concern. The cases are odor of interior material and air-conditioner of vehicles. In particualar, with respect to the odor of air-conditioner, customers strongly claimed defects with provocative comments : "It smells like something rotten," "It smells like a foot odor," "It stinks like a rag." Generally, it is known that mold of evaporator core in the air-conditioning system decays and this produce VOCs which causes the odor to occur. In this study, partial least squares regression model is applied to predict the strength of the odor and select of important VOCs which affect car air conditioning smell. The PLS method is basically a particular multilinear regression algorithm which can handle correlated inputs and limited data. The number of latent variable is determined by the point which is stabilized mean absolute deviations of VOCs data. Also multiple linear regression is carried out to confirm the validity of PLS method.

A Study on the Comparision of One-Dimensional Scattering Extraction Algorithms for Radar Target Identification (레이더 표적 구분을 위한 1차원 산란점 추출 기법 알고리즘들의 성능에 관한 비교 연구)

  • Jung, Ho-Ryung;Seo, Dong-Kyu;Kim, Kyung-Tae;Kim, Hyo-Tae
    • Proceedings of the Korea Electromagnetic Engineering Society Conference
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    • 2003.11a
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    • pp.193-197
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    • 2003
  • Radar target identification can be achieved by using various radar signatures, such as one-dimensional(1-D) range profile, 2-D radar images, and 1-D or 2-D scattering centers on a target. In this letter, five 1-D scattering center extraction methods are discussed - TLS(Total Least Square)-Prony, Fast Root-MUSIC (Multiple Signal Classification), Matrix-Pencil, GEESE(GEneralized Eigenvalues utilizing Signal-subspace Eigenvalues), TLS-ESPRIT(Total Least Squares - Estimation of Signal Parameters via Rotational Invariance Technique), These methods are compared in the context of estimation accuracy as well as a computational efficiency using a noisy data. Finally these methods are applied to the target classification experiment with the measured data in the POSTECH compact range facility.

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MORE RELATIONS BETWEEN λ-LABELING AND HAMILTONIAN PATHS WITH EMPHASIS ON LINE GRAPH OF BIPARTITE MULTIGRAPHS

  • Zaker, Manouchehr
    • Bulletin of the Korean Mathematical Society
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    • v.59 no.1
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    • pp.119-139
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    • 2022
  • This paper deals with the λ-labeling and L(2, 1)-coloring of simple graphs. A λ-labeling of a graph G is any labeling of the vertices of G with different labels such that any two adjacent vertices receive labels which differ at least two. Also an L(2, 1)-coloring of G is any labeling of the vertices of G such that any two adjacent vertices receive labels which differ at least two and any two vertices with distance two receive distinct labels. Assume that a partial λ-labeling f is given in a graph G. A general question is whether f can be extended to a λ-labeling of G. We show that the extension is feasible if and only if a Hamiltonian path consistent with some distance constraints exists in the complement of G. Then we consider line graph of bipartite multigraphs and determine the minimum number of labels in L(2, 1)-coloring and λ-labeling of these graphs. In fact we obtain easily computable formulas for the path covering number and the maximum path of the complement of these graphs. We obtain a polynomial time algorithm which generates all Hamiltonian paths in the related graphs. A special case is the Cartesian product graph Kn☐Kn and the generation of λ-squares.

Estimation of Rotational Center and Angle for Image Stabilization (영상 안정화를 위한 회전중심 및 각도 추정기법)

  • Seok, Ho-Dong;Yoo, Jun;Kim, Do-Jong
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.7
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    • pp.611-617
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    • 2004
  • This paper presents a simple method of rotational motion estimation and correction for roll axis stabilization of an image. The scheme first computes the rotation center by taking least squares of selected local velocity vectors, and the rotational angle is found from special subset of motion vectors. Roll motion correction is then performed by the nearest neighbor interpolation technique. To show the effectiveness of our approach, the synthetic and real images are evaluated, resulting in better performance than the previous ones.

Tracking Control of Robotic Manipulators based on the All-Coefficient Adaptive Control Method

  • Lei Yong-Jun;Wu Hong-Xin
    • International Journal of Control, Automation, and Systems
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    • v.4 no.2
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    • pp.139-145
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    • 2006
  • A multi-variable Golden-Section adaptive controller is proposed for the tracking control of robotic manipulators with unknown dynamics. With a small sample time, the unknown dynamics of the robotic manipulator are denoted equivalently by a characteristic model of a 2-order multivariable time-varying difference equation. The coefficients of the characteristic model change slowly with time and some of their valuable characteristic relationships emerge. Based on the characteristic model, an adaptive algorithm with a simple form for the control of robotic manipulators is presented, which combines the multi-variable Golden-Section adaptive control law with the weighted least squares estimation method. Moreover, a compensation neural network law is incorporated into the designed controller to reduce the influence of the coefficients estimation error on the control performance. The results of the simulations indicate that the developed control scheme is effective in robotic manipulator control.

Adaptive Neuro-Fuzzy Inference Systems for Indoor Propagation Prediction

  • Phaiboon, S.;Phokharatkul, P.;Somkurnpanich, S.
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1865-1869
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    • 2004
  • A new model for the propagation prediction for mobile communication network inside building is presented in this paper. The model is based on the determination of the dominant paths between the transmitter and the receiver. The field strength is predicted with adaptive neuro - fuzzy inference systems (ANFIS), trained with measurements. The advantage of the ANFIS with hybrid least squares and gradient descent algorithms is fast convergence compared with original neural network. The K-means algorithm for selection of training patterns is also used. Comparison of our predicted results to measurements indicate that improvements in accuracy over conventional empirical model are achieved.

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