Performance evaluation of analog circuit using improved LSSVR subject to data information uncertainty
This paper demystifies the proposed analog circuit performance evaluation methods based on improved LSSVR (ILSSVR) by examining the arithmetic speed and the evaluation reliability online. The ILSSVR performance evaluation scheme has the robustness for the signal information uncertainty, which may be...
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| Published in | Neurocomputing (Amsterdam) Vol. 151; pp. 461 - 470 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
03.03.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0925-2312 1872-8286 |
| DOI | 10.1016/j.neucom.2014.09.020 |
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| Abstract | This paper demystifies the proposed analog circuit performance evaluation methods based on improved LSSVR (ILSSVR) by examining the arithmetic speed and the evaluation reliability online. The ILSSVR performance evaluation scheme has the robustness for the signal information uncertainty, which may be deduced by nonlinear feature, time varying feature and contain faults value about industrial field data information. More specially, the self-update via incremental and reduced interaction is employed to detect the interests both on history data information and the updated data information, and the features extraction nonlinear independent component analysis (NICA) is proposed, then the number of the feature data is controlled and desired time consumed is guaranteed. In addition, the multi-kernel and weighted idea have also been employed to interfuse quite flexibility to the bandwidths of kernel online. The proposed analog circuit performance evaluation scheme ILSSVR is evaluated for two filter circuit: leapfrog filter circuit and self-adapting filter circuit. And the effectiveness is illustrated through a numerical example. |
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| AbstractList | This paper demystifies the proposed analog circuit performance evaluation methods based on improved LSSVR (ILSSVR) by examining the arithmetic speed and the evaluation reliability online. The ILSSVR performance evaluation scheme has the robustness for the signal information uncertainty, which may be deduced by nonlinear feature, time varying feature and contain faults value about industrial field data information. More specially, the self-update via incremental and reduced interaction is employed to detect the interests both on history data information and the updated data information, and the features extraction nonlinear independent component analysis (NICA) is proposed, then the number of the feature data is controlled and desired time consumed is guaranteed. In addition, the multi-kernel and weighted idea have also been employed to interfuse quite flexibility to the bandwidths of kernel online. The proposed analog circuit performance evaluation scheme ILSSVR is evaluated for two filter circuit: leapfrog filter circuit and self-adapting filter circuit. And the effectiveness is illustrated through a numerical example. |
| Author | Zhang, Zhiqiang Zhang, Aihua Wang, Yongchao |
| Author_xml | – sequence: 1 givenname: Aihua surname: Zhang fullname: Zhang, Aihua email: Aihuazhangbhu@gmail.com – sequence: 2 givenname: Yongchao surname: Wang fullname: Wang, Yongchao email: 985287986@qq.com – sequence: 3 givenname: Zhiqiang surname: Zhang fullname: Zhang, Zhiqiang email: Jsxinxi_zzq@163.com |
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| Keywords | Multi-kernel ILSSVR Features extraction Incremental and reduced interaction Analog circuit performance evaluation |
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| Snippet | This paper demystifies the proposed analog circuit performance evaluation methods based on improved LSSVR (ILSSVR) by examining the arithmetic speed and the... |
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| SubjectTerms | Analog circuit performance evaluation Features extraction ILSSVR Incremental and reduced interaction Multi-kernel |
| Title | Performance evaluation of analog circuit using improved LSSVR subject to data information uncertainty |
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