Presentation | 2005-01-21 A Synchronized Learning Algorithm for Lattice Predictor Based Nonlinear Adaptive Filter Hiroaki KASHIMOTO, Kenji NAKAYAMA, Akihiro HIRANO, |
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Abstract(in English) | The adaptive Volterra filters (AVF) can represent general nonlinearity. However, its convergence speed is very slow. In order to solve this problem, techniques of whitening the input signal have been proposed. Among them, the lattice prediction error filter is useful. The lattice predictor based AVF (Lattice-AVF) has some problem. Updating the reflection coefficients and the filter coefficients is asynchronous, causing poor convergence properties. In order to solve this problem, the synchronized learning algorithm has been proposed for the linear adaptive filters. In this paper, a new synchronized learning algorithm is proposed for the nonlinear part of the Lattice-AVF. Its usefulness is confirmed though simulation using nonstationary colored signals. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Adaptive filters / Nonlinear / Volterra filters / Lattice predictor |
Paper # | SIP2004-110 |
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Committee | SIP |
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Conference Date | 2005/1/14(1days) |
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Registration To | Signal Processing (SIP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A Synchronized Learning Algorithm for Lattice Predictor Based Nonlinear Adaptive Filter |
Sub Title (in English) | |
Keyword(1) | Adaptive filters |
Keyword(2) | Nonlinear |
Keyword(3) | Volterra filters |
Keyword(4) | Lattice predictor |
1st Author's Name | Hiroaki KASHIMOTO |
1st Author's Affiliation | Division of Electronics and Computer Science Graduate School of Natural Science and Technology, Kanazawa Univ.() |
2nd Author's Name | Kenji NAKAYAMA |
2nd Author's Affiliation | Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology, Kanazawa Univ. |
3rd Author's Name | Akihiro HIRANO |
3rd Author's Affiliation | Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology, Kanazawa Univ. |
Date | 2005-01-21 |
Paper # | SIP2004-110 |
Volume (vol) | vol.104 |
Number (no) | 559 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |