Presentation | 2002/8/28 Feature Extraction of Time Series by using the Multifractal Signals and its Applications Noboru TAKAGI, Shozo TOKINAGA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This report deals with feature extraction of time series based on the multifractal and its applications. We introduce the representation of multifractal by using the wavelet coefficients in contrast to the conventional definition in the time domain. The relation among the multifractal and the moments of wavelet coefficients for the time series is derived. The higher-order moments of wavelet coefficient are easy to calculate , and we can have precise information for each dilation index m. As an application, the basic prescribed waveforms such as the fractal time series and sinusoidal waves are recognized by the system, and also the system is applied to the feature extraction of the time series of stock trends. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Multifractal / Wavelet Coefficients / High-order Moments / Feature Extraction / Time Series Recognition |
Paper # | NLP2002-61 |
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Committee | NLP |
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Conference Date | 2002/8/28(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Nonlinear Problems (NLP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Feature Extraction of Time Series by using the Multifractal Signals and its Applications |
Sub Title (in English) | |
Keyword(1) | Multifractal |
Keyword(2) | Wavelet Coefficients |
Keyword(3) | High-order Moments |
Keyword(4) | Feature Extraction |
Keyword(5) | Time Series Recognition |
1st Author's Name | Noboru TAKAGI |
1st Author's Affiliation | Graduate School of Economics, Kyushu University() |
2nd Author's Name | Shozo TOKINAGA |
2nd Author's Affiliation | Graduate School od Economics, Kyushu University |
Date | 2002/8/28 |
Paper # | NLP2002-61 |
Volume (vol) | vol.102 |
Number (no) | 298 |
Page | pp.pp.- |
#Pages | 6 |
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