| Presentation | 2012-03-08 Adaptive proximal forward-backward splitting applied to Huber loss function for sparse system identification under impulsive noise Takayuki YAMAMOTO, Masao YAMAGISHI, Isao YAMADA, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, we propose a robust sparsity-aware adaptive filtering algorithm under impulsive noise environment, by using the Huber loss function in the frame of adaptive proximal forward-backward splitting(APFBS). The APFBS attempts to suppress a time-varying cost function which is the sum of a smooth function and a nonsmooth function. As the smooth function, we employ the weighted sum of the Huber loss functions of the output residuals. As the nonsmooth function, we employ the weighted l_1 norm. The use of the Huber loss function robustifies the estimation under impulsive noise and the use of the weighted l_1 norm effectively exploits the sparsity of the system to be estimated. The resulting algorithm has low-computational complexity with order 0(N), where N is the tap length. Numerical examples in sparse system identification demonstrate that the proposed algorithm outperforms conventional algorithms by achieving robustness against impulsive noise. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Adaptive proximal forward-backward splitting / Huber loss function / Sparse system identification / Adaptive filtering / Robust adaptive filtering algorithm / Parallel projection algorithm |
| Paper # | CAS2011-110,SIP2011-130,CS2011-102 |
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| Conference Information | |
| Committee | CAS |
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| Conference Date | 2012/3/1(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Circuits and Systems (CAS) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Adaptive proximal forward-backward splitting applied to Huber loss function for sparse system identification under impulsive noise |
| Sub Title (in English) | |
| Keyword(1) | Adaptive proximal forward-backward splitting |
| Keyword(2) | Huber loss function |
| Keyword(3) | Sparse system identification |
| Keyword(4) | Adaptive filtering |
| Keyword(5) | Robust adaptive filtering algorithm |
| Keyword(6) | Parallel projection algorithm |
| 1st Author's Name | Takayuki YAMAMOTO |
| 1st Author's Affiliation | Department of Communications and Integrated Systems, Tokyo Institute of Technology() |
| 2nd Author's Name | Masao YAMAGISHI |
| 2nd Author's Affiliation | Department of Communications and Integrated Systems, Tokyo Institute of Technology |
| 3rd Author's Name | Isao YAMADA |
| 3rd Author's Affiliation | Department of Communications and Integrated Systems, Tokyo Institute of Technology |
| Date | 2012-03-08 |
| Paper # | CAS2011-110,SIP2011-130,CS2011-102 |
| Volume (vol) | vol.111 |
| Number (no) | 465 |
| Page | pp.pp.- |
| #Pages | 5 |
| Date of Issue | |