• Title/Summary/Keyword: fitting algorithm

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Ideal Phase map Extraction Method and Filtering of Electronic Speckle Pattern Interferometry (전자 스페클 간섭법에서의 이상적인 위상도 추출과 필터링 방법)

  • 강영준;이주성;박낙규;권용기
    • Journal of the Korean Society for Precision Engineering
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    • v.19 no.12
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    • pp.20-26
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    • 2002
  • Deformation phase can be obtained by using Least-Square fitting. In extraction of phase values, Least-Square Fitting is superior to usual method such as 2, 3, 4-Bucket Algorithm. That can extract almost noise-free phase and retain 2 $\pi$ discontinuities. But more fringes in phase map, 2 $\pi$ discontinuities are destroyed when that are filtered and reconstruction of deformation is not reliable. So, we adapted Least-Square fitting using an isotropic window in dense fringe. Using Sine/cosine filter give us perfect 2 $\pi$ discontinuities information. We showed the process and result of extraction of phase map and filtering in this paper.

Algorithm to Improve Mass Spectral Resolution of Gas Chromatography Mass Spectrometer (가스크로마토그래피 질량분석기의 질량 스펙트럼 해상도 개선 알고리즘)

  • Choi, Hun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.9
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    • pp.1232-1238
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    • 2018
  • This paper proposes methods for improving mass spectral resolution for a gas chromatograph mass spectrometer. The slope signs of the 1st and 2nd fitting functions for the ion signal block of each mass index are obtained, and the unnecessary element signals in the ion signal block are removed. The spectrum can be obtained by obtaining the second-order fitting function of the reconstructed ion signal block using only the effective ion signals. In addition, the resolution of the mass spectrum can be improved by correcting the error caused by the shift of the spectral peak position. To verify the performance of the proposed methods, computer simulations were performed using the actual ion signals obtained from the GC-MS system under development. Simulation results show that the proposed method is valid.

A Novel Battery State of Health Estimation Method Based on Outlier Detection Algorithm

  • Piao, Chang-hao;Hu, Zi-hao;Su, Ling;Zhao, Jian-fei
    • Journal of Electrical Engineering and Technology
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    • v.11 no.6
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    • pp.1802-1811
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    • 2016
  • A novel battery SOH estimation algorithm based on outlier detection has been presented. The Battery state of health (SOH) is one of the most important parameters that describes the usability state of the power battery system. Firstly, a battery system model with lifetime fading characteristic was established, and the battery characteristic parameters were acquired from the lifetime fading process. Then, the outlier detection method based on angular distribution was used to identify the outliers among the battery behaviors. Lastly, the functional relationship between battery SOH and the outlier distribution was obtained by polynomial fitting method. The experimental results show that the algorithm can identify the outliers accurately, and the absolute error between the SOH estimation value and true value is less than 3%.

A Comparison of Classification Techniques in Hyperspectral Image (하이퍼스펙트럴 영상의 분류 기법 비교)

  • 가칠오;김대성;변영기;김용일
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.11a
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    • pp.251-256
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    • 2004
  • The image classification is one of the most important studies in the remote sensing. In general, the MLC(Maximum Likelihood Classification) classification that in consideration of distribution of training information is the most effective way but it produces a bad result when we apply it to actual hyperspectral image with the same classification technique. The purpose of this research is to reveal that which one is the most effective and suitable way of the classification algorithms iii the hyperspectral image classification. To confirm this matter, we apply the MLC classification algorithm which has distribution information and SAM(Spectral Angle Mapper), SFF(Spectral Feature Fitting) algorithm which use average information of the training class to both multispectral image and hyperspectral image. I conclude this result through quantitative and visual analysis using confusion matrix could confirm that SAM and SFF algorithm using of spectral pattern in vector domain is more effective way in the hyperspectral image classification than MLC which considered distribution.

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A Current Compensation Algorithm for a CT Saturation (CT 포화 복원 알고리즘)

  • Yi, Xiao-Li;Kang, Sang-Hee;Lee, Dong-Gyu;Kang, Yong-Cheol
    • Proceedings of the KIEE Conference
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    • 2003.11a
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    • pp.88-90
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    • 2003
  • In this paper, an algorithm to compensate the distorted signals due to CT(Current Transformer) saturation is suggested. Firstly, WT(Wavelet Transform) is used to detect a start point and an end point of saturation. Filter banks which can be easily realized in real-time applications are employed in detecting CT saturation. Secondly, least-square curve fitting method is used to restore the distorted section of the secondary current. Fault simulations are performed on a power system model using EMTP(Electromagnetic Transient Program). A series of test results indicate that WT has superior detection accuracy and the proposed algorithm which shows very stable features under various levels of remanent flux is also satisfactory.

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Adaptive Marquardt Algorithm based on Mobile environment (모바일 환경에 적합한 적응형 마쿼트 알고리즘 제시)

  • Lee, Jongsu;Hwang, Eunhan;Song, Sangseob
    • Smart Media Journal
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    • v.3 no.2
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    • pp.9-13
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    • 2014
  • The Levenberg-Marquardt (LM) algorithm is the most widely used fitting algorithm. It outperforms simple gradient descent and other conjugate gradient methods in a wide variety of problems. Based on the work of paper[1], we propose a modified Levenberg-Marquardt algorithm for better performance of mobile system. The LM parameter at the $k_{th}$ iteration is chosen ${\mu}=A{\bullet}{\parallel}f(x){\parallel}{\bullet}I$ where f is the residual function, and J is the Jacobi of f. In this paper, we show this method is more efficient than traditional method under the situation that the system iteration is limited.

Shock-Fitting in Kinematic Wave Modeling (운동파 이론의 충격파 처리기법)

  • Park, Mun-Hyeong;Choe, Seong-Uk;Heo, Jun-Haeng;Jo, Won-Cheol
    • Journal of Korea Water Resources Association
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    • v.32 no.2
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    • pp.185-195
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    • 1999
  • The finite difference method and the method of characteristics are frequently used for the numerical analysis of kinematic wave model. Truncation errors cause the peak discharge dissipated in the solution from the finite difference method. The peak discharge is conserved in the solution from the finite difference method. The peak discharge is conserved in the solution from the method of characteristics, however, the shock may deteriorates the numerical solution. In this paper, distinctive features of each scheme are investigated for the numerical analysis of kinematic wave model, and applicability of shock fitting algorithm such as Propagating Shock Fitting and Approximated Shock Fitting methods are studied. Propagating Shock Fitting method appears to treat shock properly, however, it failed to fit the shock appropriately when applied to a sudden inflow change in a long river. Approximate Shock Sitting method, which uses finer elements, is found to be more proper shock-fitting than the Propagating Shock Fitting method. Comparisons are made between two solution from the kinematic wave theory with shock fitting and full dynamic wave theory, and the results are discussed.

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Identification of Damping Matrix for a Steel Bar by the Genetic Algorithm (유전알고리즘에 의한 강봉의 감쇠행렬 산출법)

  • Park, Sok-Chu;Park, Young-Bum;Park, Kyoung-Il;Je, Hye-Kwang;Yi, Geum-Joo
    • Journal of Advanced Marine Engineering and Technology
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    • v.35 no.2
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    • pp.271-277
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    • 2011
  • An identification method of the structural damping matrix for a steel bar by the genetic algorithm is proposed. Supposing the damping matrix were in proportion to the stiffness matrix, the proportional factors can be identified from the curve fitting of the experimental frequency response function(FRF) by the genetic algorithm. Applying the identified damping matrix to FEM of a beam model, the values of the objective function could be reduced to about 1/60 in comparison with conventional FEM model without damping. The damping matrices of some sub-structures which have large damping partly could be identified by the algorithm, and they could be used as some parts of the FEM model for a whole structure.

The Segmented Polynomial Curve Fitting for Improving Non-linear Gamma Curve Algorithm (비선형 감마 곡선 알고리즘 개선을 위한 구간 분할 다항식 곡선 접합)

  • Jang, Kyoung-Hoon;Jo, Ho-Sang;Jang, Won-Woo;Kang, Bong-Soon
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.3
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    • pp.163-168
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    • 2011
  • In this paper, we proposed non-linear gamma curve algorithm for gamma correction. The previous non-linear gamma curve algorithm is generated by the least square polynomial using the Gauss-Jordan inverse matrix. However, the previous algorithm has some weak points. When calculating coefficients using inverse matrix of higher degree, occurred truncation errors. Also, only if input sample points are existed regular interval on 10-bit scale, the least square polynomial is accurately works. To compensate weak-points, we calculated accurate coefficients of polynomial using eigenvalue and orthogonal value of mat11x from singular value decomposition (SVD) and QR decomposition of vandemond matrix. Also, we used input data part segmentation, then we performed polynomial curve fitting and merged curve fitting results. When compared the previous method and proposed method using the mean square error (MSE) and the standard deviation (STD), the proposed segmented polynomial curve fitting is highly accuracy that MSE under the least significant bit (LSB) error range is approximately $10^{-9}$ and STD is about $10^{-5}$.

Segmentation of tooth using Adaptive Optimal Thresholding and B-spline Fitting in CT image slices (적응 최적 임계화와 B-spline 적합을 사용한 CT영상열내 치아 분할)

  • Heo, Hoon;Chae, Ok-Sam
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.4
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    • pp.51-61
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    • 2004
  • In the dental field, the 3D tooth model in which each tooth can be manipulated individually is an essential component for the simulation of orthodontic surgery and treatment. To reconstruct such a tooth model from CT slices, we need to define the accurate boundary of each tooth from CT slices. However, the global threshold method, which is commonly used in most existing 3D reconstruction systems, is not effective for the tooth segmentation in the CT image. In tooth CT slices, some teeth touch with other teeth and some are located inside of alveolar bone whose intensity is similar to that of teeth. In this paper, we propose an image segmentation algorithm based on B-spline curve fitting to produce smooth tooth regions from such CT slices. The proposed algorithm prevents the malfitting problem of the B-spline algorithm by providing accurate initial tooth boundary for the fitting process. This paper proposes an optimal threshold scheme using the intensity and shape information passed by previous slice for the initial boundary generation and an efficient B-spline fitting method based on genetic algorithm. The test result shows that the proposed method detects contour of the individual tooth successfully and can produce a smooth and accurate 3D tooth model for the simulation of orthodontic surgery and treatment.