• Title/Summary/Keyword: Total Least Squares

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Recursive Total Least Squares Method for Ultrasonic Doppler Frequency Estimation (순환적인 완전최소자승법을 이용한 도플러 주파수 추정 방법에 관한 연구)

  • Kim Yoon Chung;Lim jun-seok;Song Joon-il;Choi Nakjin;Sung Koeng-Mo
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.357-360
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    • 2002
  • 혈관에 흐르는 혈류 속도의 측정은 혈압 및 심박수와 관련된 혈류의 역학적 변화를 관찰하는 데 있어서 주로 사용되는 방법 중의 하나이다. 이 혈류 속도는 일반적으로 도플러 효과에 의하여 주파수가 변화하는 현상을 이용하여 추정하게 된다. 그런데 기존의 주파수 추정 방법들은 시불변 시스템을 가정하고 있지만 실제 혈관 속은 혈구가 일정하지 않은 속도를 갖는 시변 시스템이라 할 수 있기 때문에 이러한 시변 특성이 강한 경우 기존의 방법을 이용하게 되면 그 성능이 저하되는 경향을 보인다. 또 피시험자의 몸 상태에 따라서 서로 다른 주파수 변화 추이를 보이므로 하나의 고정 변수로써 최적화된 성능을 기대하기도 어렵다. 그러므로 본 논문에서는 시변 시스템에서 좋은 성능을 갖는 가변 망각 인자(variable forgetting factor, VFF)를 사용한 순환적인 완전 최소 자승법(recursive total least squares, RTLS) 기법을 이용한 주파수 추정 방법을 제안한다. RTLS란 TLS 기법을 순차적으로 계산하는 방법으로 시변 적응력을 향상시키는 방법이다. 또한 이 기법에 가변 망각 인자(VFF)를 적용시키는 것은 시변 시스템에서 외부적인 변화에 대하여 좀더 효율적으로 대응할 수 있기 위함이다. 기존의 방법과 성능 비교를 위하여 컴퓨터 시뮬레이션을 하였으며 그 결과 시변 시스템에서 본 논문에서 제안한 VFF를 이 용한 RTLS 기법이 보다 향상된 성능을 가지고 있음을 확인 할 수 있었다.

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Time delay estimation by iterative Wiener filter based recursive total least squares algorithm (반복형 위너 필터 방법에 기반한 재귀적 완전 최소 제곱 방법을 사용한 시간 지연 추정 알고리즘)

  • Lim, Jun-Seok
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.5
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    • pp.452-459
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    • 2021
  • Estimating the mutual time delay between two acoustic sensors is used in various fields such as tracking and estimating the location of a target in room acoustics and sonar. In the time delay estimation methods, there are a non-parametric method, such as Generalized Cross Correlation (GCC), and a parametric method based on system identification. In this paper, we propose a time delay estimation method based on the parametric method. In particular, we propose a method that considers the noise in each receiving acoustic sensor. Simulation confirms that the proposed algorithm is superior to the existing generalized cross-correlation and adaptive eigenvalue analysis methods in white noise and reverberation environments.

The Impact of Ownership Structure on Credit Risk of Commercial Banks: An Empirical Study in Vietnam

  • PHAM, Thi Bich Duyen;PHAM, Thi Kieu Khanh
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.7
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    • pp.195-201
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    • 2021
  • This study aims to assess the impact of ownership structure of commercial banks on bank credit risk in Vietnam. The authors used the unbalanced table data of 28 commercial banks in the period from 2004 to 2020 with 439 observations. The ratio of loan loss provisioning to loans (CR) is selected as a dependent variable representing credit risk at commercial banks. The regression methods used include: least squares method (OLS), fixed-effect model (FEM), random-effect model (REM) and general least squares method (GLS). The results reveal that, with interaction variable between the ratio of equity to total assets and foreign ownership, the national GDP annual growth rate is negatively associated with credit risk. With the ratio of equity to total assets, the interaction variable between equity and state ownership, and bank size have a significant positive impact on credit risk. In addition, inflation has negligible impact on the credit risk of commercial banks in Vietnam over the research period. The findings of this study suggest that, if foreign-owned banks increase equity capital, there will be a stronger impact on reducing credit risk than other banks. On the other hand, when state-owned commercial banks in Vietnam increase equity, they will have higher credit risk.

Model Evaluations Analysis of Nonpoint Source Pollution Reduction in a Green Infrastructure regarding Urban stormwater (도시 호우 유출에 관한 그린인프라의 비점오염원 저감 모델 평가 분석)

  • Jeon, Seol;Kim, Siyeon;Lee, Moonyoung;Um, Myoung-Jin;Jung, Kichul;Park, Daeryong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.393-393
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    • 2021
  • 도시화는 도시 호우 유출 발생으로 인한 수질 악화를 초래했고 문제를 해결하기 위해 본 연구에서는 보다 정확한 설계를 위해 그린인프라(Green Infrastructure, GI)의 구조적 특성과 수문학적인 특성을 이용해 어떤 인자들이 설계에 필요한지 상관관계를 통해 분석하였다. GI의 종류 중 저류지와 저류연못의 총부유사량(Total Suspended Solids, TSS)와 총인 (Total Phosphorous, TP)의 유입수, 유출수, 비점오염원 농도, 수문학적인 특성 그리고 GI의 구조적 특성을 Ordinary Least Squares regression(OLS)과 Multi Linear Regression(MLR) 방법을 적용하였다. GI의 구조적인 특성은 한 BMP마다 달라지지 않으나 호우사상의 데이터 개수에 의한 편향이 있을 수 있다. 이런 문제를 해결하기 위해 일정한 범위를 가지고 무작위로 데이터를 추출하는 방법과 이상치를 제외하는 방법을 사용하여 모델에 적용하였다. 이러한 OLS와 MLR 모델들의 정확도를 PBIAS(Percent Bias), NSE(Nash-Sutcliffe efficiency), RSR(RMSE-observations standard deviation ratio)을 통해 분석할 수 있다. 연구 결과 유입수의 비점오염원의 농도뿐만 아니라 수문학적 특성과 GI의 구조적 특성이 함께 들어갈 시 더 좋은 상관관계를 가지고 있음을 알 수 있다. 저류지가 저류연못보다 모델의 성능평가 면에서 좋은 값을 가지고 있지만 특성별 상관관계는 저류연못이 더 뚜렷한 결과를 보여준다.

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Mass Estimation of a Permanent Magnet Linear Synchronous Motor Applied at the Vertical Axis (수직축 선형 영구자석 동기전동기의 질량 추정)

  • Lee, Jin-Woo;Ji, Jun-Keun;Mok, Hyung-Soo
    • The Transactions of the Korean Institute of Power Electronics
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    • v.13 no.6
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    • pp.487-491
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    • 2008
  • Tuning of the speed controller in the linear servo applications needs the accurate information of a mover mass including a load mass. Therefore this paper proposes the mass estimation method of a permanent magnet linear synchronous motor(PMLSM) applied at the vertical axis by using the recursive Least-Squares estimation algorithm. First, this paper derives the deterministic autoregressive moving average(DARMA) model of the mechanical dynamic system used at the vertical axis. The application of the Least-Squares algorithm to the derived DARMA model gives the mass estimation method. Matlab/Simulink-based simulation and experimental results show that the total mover mass of a PMLSM applied at the vertical axis can be accurately estimated at both no-load and load conditions.

Forecast and Demand Analysis of Oyster as Kimchi's Ingredients (김장굴의 수요 분석 및 예측)

  • Nam, Jong-Oh;Nho, Seung-Guk
    • The Journal of Fisheries Business Administration
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    • v.42 no.2
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    • pp.69-83
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    • 2011
  • This paper estimates demand functions of oyster as Kimchi's ingredients of capital area, other areas excluding a capital area, and a whole area in Korea to forecast its demand quantities in 2011~2015. To estimate oyster demand function, this paper uses pooled data produced from Korean housewives over 30 years old in 2009 and 2010. Also, this paper adopts several econometrics methods such as Ordinary Least Squares and Feasible Generalized Least Squares. First of all, to choose appropriate variables of oyster demand functions by area, this paper carries out model's specification with joint significance test. Secondly, to remedy heteroscedasticity with pooled data, this paper attempts residual plotting between estimated squared residuals and estimated dependent variable and then, if it happens, undertakes White test to care the problem. Thirdly, to test multicollinearity between variables with pooled data, this paper checks correlations between variables by area. In this analysis, oyster demand functions of a capital area and a whole area need price of the oyster, price of the cabbage for Gimjang, and income as independent variables. The function on other areas excluding a capital area only needs price of the oyster and income as ones. In addition, the oyster demand function of a whole area needed White test to care a heteroscedasticity problem and demand functions of the other two regions did not have the problem. Thus, first model was estimated by FGLS and second two models were carried out by OLS. The results suggest that oyster demand quantities per a household as Kimchi's ingredients are going to slightly increase in a capital area and a whole area, but slightly decrease in other areas excluding a capital area in 2011~2015. Also, the results show that oyster demand quantities as kimchi's ingredients for total household targeting housewives over 30 years old are going to slightly increase in three areas in 2011~2015.

Decision function for optimal smoothing parameter of asymmetrically reweighted penalized least squares (Asymetrically reweighted penalized least squares에서 최적의 평활화 매개변수를 위한 결정함수)

  • Park, Aa-Ron;Park, Jun-Kyu;Ko, Dae-Young;Kim, Sun-Geum;Baek, Sung-June
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.3
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    • pp.500-506
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    • 2019
  • In this study, we present a decision function of optimal smoothing parameter for baseline correction using Asymmetrically reweighted penalized least squares (arPLS). Baseline correction is very important due to influence on performance of spectral analysis in application of spectroscopy. Baseline is often estimated by parameter selection using visual inspection on analyte spectrum. It is a highly subjective procedure and can be tedious work especially with a large number of data. For these reasons, an objective procedure is necessary to determine optimal parameter value for baseline correction. The proposed function is defined by modeling the median value of possible parameter range as the length and order of the background signal. The median value increases as the length of the signal increases and decreases as the degree of the signal increases. The simulated data produced a total of 112 signals combined for the 7 lengths of the signal, adding analytic signals and linear and quadratic, cubic and 4th order curve baseline respectively. According to the experimental results using simulated data with linear, quadratic, cubic and 4th order curved baseline, and real Raman spectra, we confirmed that the proposed function can be effectively applied to optimal parameter selection for baseline correction using arPLS.

A UDU decomposition based recursive total least square method (UDU 행렬분해법을 이용한 재귀적 TLS 알고리즘)

  • Lim Jun-seok;Choi Nakjin;Sung KoengMo
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.547-550
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    • 2004
  • 본 논문은 시스템 인식에서 RLS의 성능을 높이기 위한 한 방법으로 UDU 행렬 분해법을 바탕으로 한 recursive total least squares (RTLS) algorithm을 제안한다. 기존의 RTLS는 Power Method에 의거해서 recursive하게 만든 형태이어서 RLS와 거의 같은 구조이다. 그러나 본 논문에서는 일반적인 Power Method가 rank-1 update를 이용하기 때문에 ill-condition에 빠질 가능성이 높은 점을 감안하여, UDU 행렬 분해법을 사용한 RTLS방법을 제안하고, 그를 시스템 인식에 적용한다.

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Prediction of Chemical Compositions for On-line Quality Measurement of Red Pepper Powder Using Near Infrared Reflectance Spectroscopy (NIRS)

  • Lee, Sun-Mee;Kim, Su-Na;Park, Jae-Bok;Hwang, In-Kyeong
    • Food Science and Biotechnology
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    • v.14 no.2
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    • pp.280-285
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    • 2005
  • Applicability of near infrared reflectance spectroscopy (NIRS) was examined for quality control of red pepper powder in milling factories. Prediction of chemical composition was performed using modified partial least square (MPLS) techniques. Analysis of total 51 and 21 red pepper powder samples by conventional methods for calibration and validation, respectively, revealed standard error of prediction (SEP) and correlation coefficient ($R^2$) of moisture content, ASTA color value, capsaicinoid content, and total sugar content were 0.55 and 0.90, 8.58 and 0.96, 31.60 and 0.65, and 1.82 and 0.86, respectively; SEP and $R^2$ were low and high, respectively, except for capsaicinoid content. The results indicate, with slight improvement, on-line quality measurement of red pepper powder with NIRS could be applied in red pepper milling factories.

Quality Inspection of Dented Capsule using Curve Fitting-based Image Segmentation

  • Kwon, Ki-Hyeon;Lee, Hyung-Bong
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.12
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    • pp.125-130
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    • 2016
  • Automatic quality inspection by computer vision can be applied and give a solution to the pharmaceutical industry field. Pharmaceutical capsule can be easily affected by flaws like dents, cracks, holes, etc. In order to solve the quality inspection problem, it is required computationally efficient image processing technique like thresholding, boundary edge detection and segmentation and some automated systems are available but they are very expensive to use. In this paper, we have developed a dented capsule image processing technique using edge-based image segmentation, TLS(Total Least Squares) curve fitting technique and adopted low cost camera module for capsule image capturing. We have tested and evaluated the accuracy, training and testing time of the classification recognition algorithms like PCA(Principal Component Analysis), ICA(Independent Component Analysis) and SVM(Support Vector Machine) to show the performance. With the result, PCA, ICA has low accuracy, but SVM has good accuracy to use for classifying the dented capsule.