Presentation | 2006-03-21 Stationary Signal Estimation Using a Tensor Product that Minimizes Absolute Error Akitoshi ITAI, Hiroshi YASUKAWA, Ichi TAKUMI, Masayasu HATA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper proposes a new stationary signal estimation method using a tensor product expansion whose error function is an absolute error. When the two-variable function including nonstationary and stationary time series is applied to the conventional tensor product expansion, the product of single variable function (estimated component) is calculated by minimizing the mean square error between the input vector and the estimated component. It is difficult to extract the stationary signal from the estimated component. In this paper, we shows that the stationary signal can be estimated by using a tensor product expansion applying an absolute error for error function. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | stationary signal / tensor pruduct expansion / signal estimation / multivariate analysis |
Paper # | NLP2005-156 |
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Committee | NLP |
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Conference Date | 2006/3/14(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
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) | Stationary Signal Estimation Using a Tensor Product that Minimizes Absolute Error |
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Keyword(1) | stationary signal |
Keyword(2) | tensor pruduct expansion |
Keyword(3) | signal estimation |
Keyword(4) | multivariate analysis |
1st Author's Name | Akitoshi ITAI |
1st Author's Affiliation | Aichi prefectural University() |
2nd Author's Name | Hiroshi YASUKAWA |
2nd Author's Affiliation | Aichi prefectural University |
3rd Author's Name | Ichi TAKUMI |
3rd Author's Affiliation | Nagoya Institute of Technology |
4th Author's Name | Masayasu HATA |
4th Author's Affiliation | Collage of Engineering, Chubu University |
Date | 2006-03-21 |
Paper # | NLP2005-156 |
Volume (vol) | vol.105 |
Number (no) | 676 |
Page | pp.pp.- |
#Pages | 6 |
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