Art

J-GLOBAL ID：200902255885168914   Reference number：05A0587179

Decomposition of Surface Data into Fractal Signals Based on Mean Likelihood and Importance Sampling and Its Applications to Feature Extraction

平均尤度と重要度サンプリングを利用した曲面データのフラクタル信号への分解とその特徴抽出への適用

Author (2)： TOKINAGA Shozo (Kyushu Univ., Fukuoka-shi, JPN) ,  TAKAGI Noboru (Nagasaki Insutitute of Applied Sci., Nagasaki-shi, JPN)
Material： IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (Institute of Electronics, Information and Communication Engineers)  (IEICE Trans Fundam Electron Commun Comput Sci (Inst Electron Inf Commun Eng))
Volume： E88-A  Issue： 7  Page： 1946-1956  Publication year： Jul. 01, 2005 
JST Material Number： F0699C  ISSN： 0916-8508  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： signal processing ,...

   To see more with JDream III (charged).   {{ this.onShowAbsJLink("http://jdream3.com/lp/jglobal/index.html?docNo=05A0587179&from=J-GLOBAL&jstjournalNo=F0699C") }}

JST classification (1)： Signal theory  (ND02020G)

Reference (18)：

• KAY, S. M. Mean likelihood frequency estimation. IEEE Trans. Signal Process. 2000, 48, 7, 1937-1946
• SAHA, S. Maximum likelihood parameter estimation of superimposed chirps using Monte Carlo importance sampling. IEEE Trans. Signal Process. 2002, 50, 2, 224-230
• TAKAGI, N. Decomposition of time series by using the fractal signals based on the importance sampling and its applications to the prediction. IEICE Trans. Fundamentals (Japanese Edition). 2003, J86-A, 10, 1010-1020
• TOKINAGA, S. Feature extraction by using the decomposition of surface data into several fractal surfaces based on the importance sampling and its applications. IEICE Technical Report. 2003, DSP2003-191
• TOKINAGA, S. A fore-casting method for time series bearing fractal geometry and its application. IEICE Trans. Fundamentals (Japanese Edition). 1996, J79-A, 11, 1793-1800

Terms in the title (7)： 平均 ,  尤度 ,  重要度サンプリング ,  曲面 ,  フラクタル ,  分解 ,  特徴抽出