• 제목/요약/키워드: least square technique

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An Identification of Dynamic Characteristics by Spectral Analysis Technique of Linear Autoregressive Model Using Lattice Filter (Lattice Filter 이용한 선형 AR 모델의 스펙트럼 분석기법에 의한 동특성 해석)

  • Lee, Tae-Yeon;Shin, Jun;Oh, Jae-Eung
    • Journal of the Korean Society of Safety
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    • v.7 no.2
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    • pp.71-79
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    • 1992
  • This paper presents a least-square algorithms of lattice structures and their use for adaptive prediction of time series generated from the dynamic system. As the view point of adaptive prediction, a new method of Identification of dynamic characteristics by means of estimating the parameters of linear auto regressive model is proposed. The fast convergence of adaptive lattice algorithms is seen to be due to the orthogonalization and decoupling properties of the lattice. The superiority of the least-square lattice is verified by computer simulation, then predictor coefficients are computed from the linear sequential time data. For the application to the dynamic characteristic analysis of unknown system, the transfer function of ideal system represented in frquency domain and the estimated one obtained by predicted coefficients are compared. Using the proposed method, the damping ratio and the natural frequency of a dynamic structure subjected to random excitations can be estimated. It is expected that this method will be widely applicable to other technical dynamic problem in which estimation of damping ratio and fundamental vibration modes are required.

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A Transfer Function Synthesis for Model Approximation with Resonance Peak Value (첨두공진점을 갖는 모델 근사화를 위한 전달함수 합성법)

  • Kim, Jong-Gun;Kim, Ju-Sik;Kim, Hong-Kyu
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.22 no.1
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    • pp.118-123
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    • 2008
  • This paper proposes a frequency transfer function synthesis for approximating a high-order model with resonance to a low-order model in the frequency domain. The presented model approximation method is based on minimizing the error function weighted by the numerator polynomial of approximated models, which is used of the RLS(Recursive Least Square) technique to estimate the coefficient vector of approximated models. The proposed method provides better fitting in a low frequency and peak resonance. And an example is given to illustrate feasibilities of the suggested schemes.

A Study on the Baseband Data Recovery and its Realization via the 2-Dimensional Transformantion of Estimation Parameters (추정 파라미터의 2차원 변환을 통한 기저대역 데이터 복원 및 그의 실현에 관한 연구)

  • 허동규;김기근;유흥균
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.15 no.12
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    • pp.1044-1052
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    • 1990
  • We have investigated the digital bit synchronization problem in baseband communication receiver systems using the Gauss-Markov estimation technique which is equivalent to the weighted least square method. The realized bit synchronizer, including the data detector, processes the input signal two dimensionally into the transition phase and data level under the white Gaussian noise environment. We have confrmed the realiation of the bit synchronizer via computer simulation. In addition, we have compared and evaluated the estimation error performance of the proposed method with that of the conventional DTTL method and of the minimum likelihood method.

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Adaptive Milling Process Modeling and Nerual Networks Applied to Tool Wear Monitoring (밀링공정의 적응모델링과 공구마모 검출을 위한 신경회로망의 적용)

  • Ko, Tae-Jo;Cho, Dong-Woo
    • Journal of the Korean Society for Precision Engineering
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    • v.11 no.1
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    • pp.138-149
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    • 1994
  • This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

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Volatile Compounds for Discrimination between Beef, Pork, and Their Admixture Using Solid-Phase-Microextraction-Gas Chromatography-Mass Spectrometry (SPME-GC-MS) and Chemometrics Analysis

  • Zubayed Ahamed;Jin-Kyu Seo;Jeong-Uk Eom;Han-Sul Yang
    • Food Science of Animal Resources
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    • v.44 no.4
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    • pp.934-950
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    • 2024
  • This study addresses the prevalent issue of meat species authentication and adulteration through a chemometrics-based approach, crucial for upholding public health and ensuring a fair marketplace. Volatile compounds were extracted and analyzed using headspace-solid-phase-microextraction-gas chromatography-mass spectrometry. Adulterated meat samples were effectively identified through principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). Through variable importance in projection scores and a Random Forest test, 11 key compounds, including nonanal, octanal, hexadecanal, benzaldehyde, 1-octanol, hexanoic acid, heptanoic acid, octanoic acid, and 2-acetylpyrrole for beef, and hexanal and 1-octen-3-ol for pork, were robustly identified as biomarkers. These compounds exhibited a discernible trend in adulterated samples based on adulteration ratios, evident in a heatmap. Notably, lipid degradation compounds strongly influenced meat discrimination. PCA and PLS-DA yielded significant sample separation, with the first two components capturing 80% and 72.1% of total variance, respectively. This technique could be a reliable method for detecting meat adulteration in cooked meat.

A Study for the 3-Dimensional Measurement System using Laser Slit-Ray (레이저 슬릿광을 이용한 3차원 계측 장치에 관한 연구)

  • 김선일;정재문;양윤모
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.2
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    • pp.27-39
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    • 1992
  • 3 Dimensional measurement system using camera and laser slit-ray is studied. Precise calibration technique in this system is suggested. Calibration is accomplished with calibration die, calibration block and robot. For obtaining calibration parameters, the equations are solved using least square error method from a great many calibration points to reduce measuring error. Continuous measurement is possible for the object which is larger than one frame of camera. The efficiency and usability are proved by applying to the tire profile measuring system which measures tire profile using robot and this system.

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The Parameters Extraction in Poly TFT Using Optimization Technique (최적화 기법에 의한 다결정 TFT(Thin Film Transistor)의 매개 변수 추출)

  • 김홍배;손상희;박용헌
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.40 no.6
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    • pp.582-589
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    • 1991
  • We used Cd Se as the semiconductor to analyze the Poly-TFT. Cd Se TFT is fabricated by the vacuum evaporation method and the characteristics curves of the current-voltage are obtained using the results of measurement of Cd Se TFT devices. Employing least square method and Rosenbrock algorithm, we can extract the device parameters(grain boundary mobility, trap density). The current-voltage relations calculated by extracted parameters are in good agreement with experimental results.

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NUMERICAL STUDY FOR THE PARAMETER ESTIMATION OF THE MOISTURE TRANSFER COEFFICIENT : 2D CASE

  • Lee, Yong-Hun;Park, Yeon-Hee
    • Journal of applied mathematics & informatics
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    • v.29 no.5_6
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    • pp.1257-1268
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    • 2011
  • The thermal behavior of wood exposed to the outdoors is influenced by solar absorptivity and longwave emissivity. However, it is difficult to measure that properties directly. Hence we estimate the values of the parameter by using the least-square optimization technique. Finally we report the results for the computation of the values of the parameters.

One-dimensional Kalman filter for estimating target position (목표물 위치추정을 위한 1차원 Kalman filter)

  • 진강규;하주식
    • Journal of Advanced Marine Engineering and Technology
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    • v.10 no.3
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    • pp.119-125
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    • 1986
  • By using the least square input estimator and a likelihood ratio technique, an one-dimensional tracking problem is presented. A Kalman tracking filter based on constant-velocity model is used to track a target and the filtered estimate is updated with an input estimate when a maneuver is detected. The simulation results show that there are significant improvements using the scheme presented here.

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DEVELOPMENT OF TERRAIN CONTOUR MATCHING ALGORITHM FOR THE AIDED INERTIAL NAVIGATION USING RADIAL BASIS FUNCTIONS

  • Gong, Hyeon-Cheol
    • Journal of Astronomy and Space Sciences
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    • v.15 no.1
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    • pp.229-234
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    • 1998
  • We study on a terrain contour matching algorithm using Radial Basis Functions(RBFs) for aided inertial navigation system for position fixing aircraft, cruise missiles or re-entry vehicles. The parameter optimization technique is used for updating the parameters describing the characteristics of an area with modified Gaussian least square differential correction algorithm and the step size limitation filter according to the amount of updates. We have applied the algorithm for matching a sampled area with a target area supposed that the area data are available from Radar Terrain Sensor(RTS) and Reference Altitude Sensor(RAS)

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