Presentation | 2010-06-15 Inference of Multiple Absorbtion Bands for Reflectance Spectra Using Exchange Monte Carlo Method Kenji NAGATA, Seiji SUGITA, Masato OKADA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | It is essential to establish the method to deconvolute spectral data into some bands in order to analyze the chemical properties of matter. For the establishment, we have two fundamental problems. One is the determination of the number of bands without heuristics. The other is to avoid the solution of parameters to trap the local minima due to the hierarchy and the nonlinearity of the model. In this paper, we propose the new method of spectral deconvolution based on Bayesian learning with the exchange Monte Carlo method, and experimentally show its effectiveness by applying the synthetic data, and the reflectance spectral data of Olivine. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Spectroanalysis / Spectral Deconvolution / Exchange Monte Carlo Method / Bayesian Learning |
Paper # | IBISML2010-18 |
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Committee | IBISML |
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Conference Date | 2010/6/7(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Inference of Multiple Absorbtion Bands for Reflectance Spectra Using Exchange Monte Carlo Method |
Sub Title (in English) | |
Keyword(1) | Spectroanalysis |
Keyword(2) | Spectral Deconvolution |
Keyword(3) | Exchange Monte Carlo Method |
Keyword(4) | Bayesian Learning |
1st Author's Name | Kenji NAGATA |
1st Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo() |
2nd Author's Name | Seiji SUGITA |
2nd Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo |
3rd Author's Name | Masato OKADA |
3rd Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo:RIKEN Brain Science Institute |
Date | 2010-06-15 |
Paper # | IBISML2010-18 |
Volume (vol) | vol.110 |
Number (no) | 76 |
Page | pp.pp.- |
#Pages | 6 |
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