Average-Approximation SIP Algorithms Used to Improve Accuracy of RC Model Order Reduction
- Resource Type
- Conference
- Authors
- Peng, Zhiliang; Wang, Yichen; Yuan, Zhengwu; Wu, Zhanpeng; Dai, Yong; Bai, Geng; Miao, Xiangshui; Wang, Xingsheng
- Source
- 2023 International Symposium of Electronics Design Automation (ISEDA) Electronics Design Automation (ISEDA), 2023 International Symposium of. :71-75 May, 2023
- Subject
- Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
General Topics for Engineers
Photonics and Electrooptics
Design automation
Fitting
Approximation algorithms
Average approximation
Model Order Reduction (MOR)
Sparse Implicit Projection (SIP)
- Language
This paper presents the Average-Approximation Sparse Implicit Projection (AASIP) algorithm, which enhances the accuracy of the lossless correction factor in Sparse Implicit Projection (SIP) by employing the mean fitting correction. AASIP improves the approximate accuracy of RC-netlist reduction compared to conventional SIP, while also addressing the challenges of high-order moment matching in SIP. The correctness and feasibility of the proposed algorithm are demonstrated through netlist examples.