Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
167 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Reciprocal and Positive Real Balanced Truncations for Model Order Reduction of Descriptor Systems (1811.04630v1)

Published 12 Nov 2018 in cs.NA

Abstract: Model order reduction algorithms for large-scale descriptor systems are proposed using balanced truncation, in which symmetry or block skew symmetry (reciprocity) and the positive realness of the original transfer matrix are preserved. Two approaches based on standard and generalized algebraic Riccati equations are proposed. To accelerate the algorithms, a fast Riccati solver, RADI (alternating directions implicit [ADI]-type iteration for Riccati equations), is also introduced. As a result, the proposed methods are general and efficient as a model order reduction algorithm for descriptor systems associated with electrical circuit networks.

Summary

We haven't generated a summary for this paper yet.