• Title/Summary/Keyword: Recursive Method

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Glasses Removal from Facial Image using Recursive Error Compensation (반복적 오차 보정을 이용한 얼굴 영상에서 의 안경 제거)

  • Park, Jeong-Seon;Oh, You-Hwa;Lee, Seong-Whan
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10b
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    • pp.688-690
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    • 2004
  • In this paper, we propose a new method of removing glasses from human frontal facial images. We first detect the regions occluded by the glasses, and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame, nor of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion, and we believe that this method can also be used to enhance the performance of face recognition systems.

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A Study on the Parameters Estimation of Electro-Hydraulic Servo Systems Using RMSM (RLSM 방법을 이용한 전기 유압 서보 시스템의 파라미터 추정에 관한 연구)

  • Kim, Byeong-Woo;Hur, Jin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.8
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    • pp.1510-1514
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    • 2011
  • In this paper, linear discrete model of the electro-hydraulic servo system are made for parameters estimation. The parameters of electro-hydraulic servo system are estimated using the recursive least square method. Persistent excitation conditions are studied in order to estimate parameters of electro-hydraulic servo system to real values and parameters estimation affections are studied due to the forgetting factors variation. As the results, An parameter estimation method has been synthesized for minimizing the error between reference and error.

An Innovative Application Method of Monthly Load Forecasting for Smart IEDs

  • Choi, Myeon-Song;Xiang, Ling;Lee, Seung-Jae;Kim, Tae-Wan
    • Journal of Electrical Engineering and Technology
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    • v.8 no.5
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    • pp.984-990
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    • 2013
  • This paper develops a new Intelligent Electronic Device (IED), and then presents an application method of a monthly load forecasting algorithm on the smart IEDs. A Multiple Linear Regression (MLR) model implemented with Recursive Least Square (RLS) estimation is established in the algorithm. Case Study proves the accuracy and reliability of this algorithm and demonstrates the practical meanings through designed screens. The application method shows the general way to make use of IED's smart characteristics and thereby reveals a broad prospect of smart function realization in application.

Blind Signal Processing for Wireless Sensor Networks

  • Kim, Namyong;Byun, Hyung-Gi
    • Journal of Sensor Science and Technology
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    • v.23 no.3
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    • pp.158-164
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    • 2014
  • In indoor sensor networks equalization algorithms based on the minimization of Euclidean distance (MED) for the distributions of constant modulus error (CME) have yielded superior performance in compensating for signal distortions induced from optical fiber links, wireless-links and for impulsive noise problems. One main drawback of MED-CME algorithms is a heavy computational burden hindering its implementation. In this paper, a recursive gradient estimation for weight updates of the MED-CME algorithm is proposed for reducing the operations $O(N^2)$ of the conventional MED-CME to O(N) at each iteration time for N data-block size. From the simulation results of the proposed recursive method producing exactly the same results as the conventional method, the proposed estimation method can be considered to be a reliable candidate for implementation of efficient receivers in indoor sensor networks.

Curve Fitting with Recursive Ball Curve (Ball 곡선을 이용한 Fitting 알고리즘)

  • Lee, A-Ri;Choe, Yeong-Geun
    • The KIPS Transactions:PartA
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    • v.8A no.1
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    • pp.42-47
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    • 2001
  • In this paper, we present a curve fitting algorithm using a ball curve. Our algorithm is recursive method for fitting, which is not a traditional ball function but a continuous ball function. This algorithm consists of two steps. The first step, it is classified the composite corner points to joint points until selected from the given data set. The second step is the curve fitting. The basis function for curve fitting is use to ball function. Also, the weighted least square method, to insert knot, is an efficient method for piecewise ball curve and ball curve segments will be smoothly connected at all composit points. The proposed algorithm will be applied to represent image representation, like fonts, digital image and GIS.

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New approach method of finite difference formulas for control algorithm (제어 알고리즘 구현을 위한 새로운 미분값 유도 방법)

  • Kim, Tae-Yeop
    • Journal of IKEEE
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    • v.23 no.3
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    • pp.817-825
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    • 2019
  • Difference equation is useful for control algorithm in the microprocessor. To approximate a derivative values from sampled data, it is used the methods of forward, backward and central differences. The key of computing discrete derivative values is the finite difference coefficient. The focus of this paper is a new approach method of finite difference formula. And we apply the proposed method to the recursive least squares(RLS) algorithm.

Heat source control intelligent system for heat treatment process

  • Lee, JeongHoon;Cho, InHee
    • International journal of advanced smart convergence
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    • v.11 no.4
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    • pp.28-40
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    • 2022
  • Although precise temperature control in the heat treatment process is a key factor in process reliability, there are many cases where there is no separate heat source control optimization system in the field. To solve this problem, the program monitors the temperature data according to the heat source change through sensor communication in a recursive method based on multiple variables that affect the process, and the target heat source value and the actual heat treatment heat source to match the internal air temperature and material temperature. A control optimization system was constructed. Through this study, the error rate between the target temperature and the atmosphere (material surface) temperature of around 10.7% with the existing heat source control method was improved to an improved result of around 0.1% using a process optimization algorithm and system.

Memory-Efficiently Modified JEC (FD)2TD Method for Debye Medium (Debye 매질에 대한 메모리 효율적인 JEC (FD)2TD 수치 해석 기법)

  • Kim Hyun;Hong Ik-Pyo;Yook Jong-Gwan
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.16 no.5 s.96
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    • pp.447-454
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    • 2005
  • JEC method for Debye medium is required more memory resources and long calculation time than already well-known method such as RC method. It has been observed that JEC method would be converted to a memory effcient method by a change of discrete convolution integral range. The modified JEC method proposed here requires memory and calculation time similar to RC method, while it has a same or a smaller dispersion error than conventional methods, RC and JEC.

Reconstruction of High-Resolution Facial Image Based on Recursive Error Back-Projection of Top-Down Machine Learning (하향식 기계학습의 반복적 오차 역투영에 기반한 고해상도 얼굴 영상의 복원)

  • Park, Jeong-Seon;Lee, Seong-Whan
    • Journal of KIISE:Software and Applications
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    • v.34 no.3
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    • pp.266-274
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    • 2007
  • This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on top-down machine learning and recursive error back-projection. A face is represented by a linear combination of prototypes of shape and that of texture. With the shape and texture information of each pixel in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those that of texture by solving least square minimizations. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes. In addition, a recursive error back-projection procedure is applied to improve the reconstruction accuracy of high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution images captured at a distance.

New Motor Parameter Estimation Method of Surface-mounted Permanent Magnet Motors (표면 부착형 영구자석 전동기의 새로운 상수 추정 방법)

  • Lee, Dong-Myung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.4
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    • pp.517-522
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    • 2019
  • This paper proposes a new motor parameter estimation method. Because the proposed method is based on difference equations, it does not affect the error in the voltage magnitude so called dead-time effect. Information on the motor constant may be needed to improve the motor control performance. For example, a control technique called DTC (Direct Torque Control) requires a motor constant when calculating the torque and flux magnitude. As another example, in the case of predictive control, information on the motor parameters is required to generate voltage references. Because the constant of the motor fluctuates according to the driving environment, it is essential to estimate the correct motor constant because the control performance is degraded when incorrect motor information is used. In the proposed scheme, the motor constant estimated based on the voltage difference equation is obtained using the RLS (Recursive Least Square) technique. The RLS algorithm is applied to obtain the value through an iterative calculation so that the estimation performance is robust to noise. The simulation results carried out with surface mounted permanent magnet motors confirmed the validity of the proposed method.