• 제목/요약/키워드: Barycentric Interpolation

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Barycentric Approximator for Reinforcement Learning Control

  • Whang Cho
    • International Journal of Precision Engineering and Manufacturing
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    • 제3권1호
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    • pp.33-42
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    • 2002
  • Recently, various experiments to apply reinforcement learning method to the self-learning intelligent control of continuous dynamic system have been reported in the machine learning related research community. The reports have produced mixed results of some successes and some failures, and show that the success of reinforcement learning method in application to the intelligent control of continuous control systems depends on the ability to combine proper function approximation method with temporal difference methods such as Q-learning and value iteration. One of the difficulties in using function approximation method in connection with temporal difference method is the absence of guarantee for the convergence of the algorithm. This paper provides a proof of convergence of a particular function approximation method based on \"barycentric interpolator\" which is known to be computationally more efficient than multilinear interpolation .

보간 알고리즘 비교와 폴리곤 테크닉에 기초한 3차원 EEG 맵핑 (A 3-dimensional EEG topography based on the polygon technique)

  • 한이범;이용희;김선일
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 하계종합학술대회논문집
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    • pp.581-584
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    • 1998
  • To obtain 3-D topography of EEG records, we propose a new method based on the polygon mapping technique. The method has the low complexity to calculate the interpolation of the EEG records on the scalp and maintains the high resolution topography because the polygon technique performs the interpolation at the only vertexes of each polygon. We implemented the topographic system with 3D barycentric, 3D polynomial and spherical spline algorithms in a personal computer.

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PC에 기반한 3차원 TOPOGRAPHIC 매핑 시스템에 관한 연구 (A STUDY ON 3D BRAIN TOPOGRAPHY BASED ON PC)

  • 김강호;권중혁;이대희;이용희;김선일
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1997년도 춘계학술대회
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    • pp.362-365
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    • 1997
  • To visualize electrical activities in the cerebral cortex, we develop the 3D topographic mapping system based on PC. For this work, we utilize OpenGL tool and an optimized interpolation method known as 3D barycentric algotithm, which has a little computational complexity. OpenGL processes the 3D coordinates, and 3D barycentric algotithm interpolates to get overall EEGs with EEGs measured from finite electrodes on 3D. To prove validity of this algorithm on the PC-based system, we developped Windows-based 3D topographic mapping program using the Barycentric algorithm. The result showed that the performance of this system is comparable to that of workstation in terms of speed and precision. Also, the result of clinical test was the same as that of a EEG technician's analysis.

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Spectral Reflectivity Recovery from Tristimulus Values Using 3D Extrapolation with 3D Interpolation

  • Kim, Bog G.;Werner, John S.;Siminovitch, Michael;Papamichael, Kostantinos;Han, Jeongwon;Park, Soobeen
    • Journal of the Optical Society of Korea
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    • 제18권5호
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    • pp.507-516
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    • 2014
  • We present a hybrid method for spectral reflectivity recovery, using 3D extrapolation as a supplemental method for 3D interpolation. The proposed 3D extrapolation is an extended version of 3D interpolation based on the barycentric algorithm. It is faster and more accurate than the conventional spectral-recovery techniques of principal-component analysis and nonnegative matrix transformation. Four different extrapolation techniques (based on nearest neighbors, circumcenters, in-centers, and centroids) are formulated and applied to recover spectral reflectivity. Under the standard conditions of a D65 illuminant and 1964 $10^{\circ}$ observer, all reflectivity data from 1269 Munsell color chips are successfully reconstructed. The superiority of the proposed method is demonstrated using statistical data to compare coefficients of correlation and determination. The proposed hybrid method can be applied for fast and accurate spectral reflectivity recovery in image processing.