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• W2491056743 abstract "Recently Lagrangian relaxation has been used to generate convex approximations of the challenging simulation error minimization problem arising in system identification. In this paper, we present a specialized algorithm to optimize the convex bounds generated by Lagrangian relaxation, applicable to linear state-space models. The algorithm demonstrates superior scalability over general-purpose semidefinite programming solvers. In addition, we show empirically that Lagrangian relaxation is more resilient to a biasing effect commonly observed in other identification methods that guarantee model stability." @default.
• W2491056743 created "2016-08-23" @default.
• W2491056743 creator A5014393565 @default.
• W2491056743 creator A5026600708 @default.
• W2491056743 date "2016-07-01" @default.
• W2491056743 modified "2023-09-27" @default.
• W2491056743 title "Specialized algorithm for identification of stable linear systems using Lagrangian relaxation" @default.
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• W2491056743 doi "https://doi.org/10.1109/acc.2016.7525034" @default.
• W2491056743 hasPublicationYear "2016" @default.
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