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 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.
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Keyword(in English) stationary signal / tensor pruduct expansion / signal estimation / multivariate analysis
Paper # NLP2005-156
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Committee NLP
Conference Date 2006/3/14(1days)
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Registration To Nonlinear Problems (NLP)
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
Sub Title (in English)
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
Date of Issue