Network structure plays a significant role in determining the performance of network inference tasks. An interactive tool to study the dependence of network topology on estimation performance was developed. The tool allows end-users to easily create and modify network structures and observe the performance of pole estimation measured by Cramer-Rao bounds. The tool also automatically suggests the best measurement locations to maximize estimation performance, and thus finds its broad applications on the optimal design of data collection experiments. Finally, a series of theoretical results that explicitly connect subsets of network structures with inference performance are obtained.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc149617 |
| Date | 08 1900 |
| Creators | Veenadhar, Katragadda |
| Contributors | Wan, Yan, Fu, Shengli, Namuduri, Kamesh |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | Text |
| Rights | Public, Veenadhar, Katragadda, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
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