Erratum to "Edge Selections in Bilinear Dynamic Networks"
Lemma 2 of "Edge Selections in Bilinear Dynamical Networks" (Oliveira et al., 2024) allows one to efficiently compute a lower bound for the optimal <inline-formula><tex-math notation="LaTeX">\mathcal {H}_{2}</tex-math></inline-formula>-norm of a bilinear d...
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| Published in: | IEEE transactions on automatic control Vol. 70; no. 1; pp. 705 - 706 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
IEEE
01.01.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 0018-9286, 1558-2523 |
| Online Access: | Get full text |
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| Abstract | Lemma 2 of "Edge Selections in Bilinear Dynamical Networks" (Oliveira et al., 2024) allows one to efficiently compute a lower bound for the optimal <inline-formula><tex-math notation="LaTeX">\mathcal {H}_{2}</tex-math></inline-formula>-norm of a bilinear dynamical network following optimal edge selection, by showing convexity of a relaxed version of the problem. However, the proof presented is wrong in general, leaving the statement unproven. In this note, we discuss a case in which the presented result is guaranteed to hold and update our experimental results in light of this fact. Despite this problem with an auxiliary result in the article, notice that the main result in Theorem 1 remains correct, proving supermodularity of the <inline-formula><tex-math notation="LaTeX">\mathcal {H}_{2}</tex-math></inline-formula>-norm under edge addition. |
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| AbstractList | Lemma 2 of “Edge Selections in Bilinear Dynamical Networks” (Oliveira et al., 2024) allows one to efficiently compute a lower bound for the optimal [Formula Omitted]-norm of a bilinear dynamical network following optimal edge selection, by showing convexity of a relaxed version of the problem. However, the proof presented is wrong in general, leaving the statement unproven. In this note, we discuss a case in which the presented result is guaranteed to hold and update our experimental results in light of this fact. Despite this problem with an auxiliary result in the article, notice that the main result in Theorem 1 remains correct, proving supermodularity of the [Formula Omitted]-norm under edge addition. Lemma 2 of "Edge Selections in Bilinear Dynamical Networks" (Oliveira et al., 2024) allows one to efficiently compute a lower bound for the optimal <inline-formula><tex-math notation="LaTeX">\mathcal {H}_{2}</tex-math></inline-formula>-norm of a bilinear dynamical network following optimal edge selection, by showing convexity of a relaxed version of the problem. However, the proof presented is wrong in general, leaving the statement unproven. In this note, we discuss a case in which the presented result is guaranteed to hold and update our experimental results in light of this fact. Despite this problem with an auxiliary result in the article, notice that the main result in Theorem 1 remains correct, proving supermodularity of the <inline-formula><tex-math notation="LaTeX">\mathcal {H}_{2}</tex-math></inline-formula>-norm under edge addition. |
| Author | Siami, Milad Sontag, Eduardo D. de Oliveira, Arthur Castello B. |
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| Snippet | Lemma 2 of "Edge Selections in Bilinear Dynamical Networks" (Oliveira et al., 2024) allows one to efficiently compute a lower bound for the optimal... Lemma 2 of “Edge Selections in Bilinear Dynamical Networks” (Oliveira et al., 2024) allows one to efficiently compute a lower bound for the optimal [Formula... |
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| SubjectTerms | Greedy algorithms Networked control systems Nonlinear systems Optimization Robustness |
| Title | Erratum to "Edge Selections in Bilinear Dynamic Networks" |
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