An identifying function approach for determining parameter structure of statistical learning machines
文献类型：期刊论文
| 作者 | Ran, Zhi-Yong1; Hu, Bao-Gang2,3
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2015-08-25 |
| 卷号 | 162页码:209-217 |
| 关键词 | Identifying function Structural identifiability Statistical learning machine Kullback-Leibler divergence Parameter redundancy Reparameterization |
| 英文摘要 | This paper presents an identifying function (IF) approach for determining parameter structure of statistical learning machines (SLMs). This involves studying three related aspects: structural identifiability (SI), parameter redundancy (PR) and reparameterization. Firstly, by employing the Rank Theorem in Riemann geometry, we derive an efficient identifiability criterion by calculating the rank of the derivative matrix (DM) of IF. Secondly, we extend the previous concept of IF to local IF (LIF) for examining local parameter structure of SLMs, and prove that the Kullback-Leibler divergence (KLD) is such a proper LIF, thus relating the LIF approach to several existing criteria. Lastly, an analytical approach for solving minimal reparameterization in parameter-redundant models is established. The dimensionality of the minimal reparameterization can be used to characterize the intrinsic parameter dimensionality of model. We compare the IF approach with existing criteria and discuss its pros/cons from theoretical and application viewpoints. Several model examples from the literature are presented to study their parameter structure. (C) 2015 Elsevier B.V. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | NEURAL-NETWORK MODEL ; INFORMATION CRITERION ; IDENTIFIABILITY ; IDENTIFICATION |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000356125200021 |
| 公开日期 | 2015-09-22 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/7936]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
| 作者单位 | 1.Chongqing Univ Posts & Telecommun, Sch Comp Sci & Technol, Chongqing 400065, Peoples R China 2.Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Automat, LIAMA, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ran, Zhi-Yong,Hu, Bao-Gang. An identifying function approach for determining parameter structure of statistical learning machines[J]. NEUROCOMPUTING,2015,162:209-217. |
| APA | Ran, Zhi-Yong,&Hu, Bao-Gang.(2015).An identifying function approach for determining parameter structure of statistical learning machines.NEUROCOMPUTING,162,209-217. |
| MLA | Ran, Zhi-Yong,et al."An identifying function approach for determining parameter structure of statistical learning machines".NEUROCOMPUTING 162(2015):209-217. |
入库方式： OAI收割
来源：自动化研究所
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