English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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

Reciprocal and Positive Real Balanced Truncations for Model Order Reduction of Descriptor Systems