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Some effective control schemes are designed under which the whole network is globally asymptotically synchronized to an arbitrary objective trajectory.
In this setup, a robust state-feedback controller is designed, under which the system output tracks a given signal arbitrarily well, and all signals in the closed-loop system remain bounded.
The static output feedback controllers and a so-called conic switching law are designed under which the output of the closed-loop switched system can track the step signal asymptotically without violating the transient performance constraints.
Based on the certainty equivalence principle and neighborhood history information, the decentralized adaptive control is designed, under which, the boundedness of identification error is guaranteed with the help of the Lyapunov theory.
For the case where the communication graph is undirected and connected, based on the local state information of neighboring agents, a fully distributed continuous adaptive consensus protocol is designed, under which the consensus error is uniformly ultimately bounded and exponentially converges to a small adjustable bounded set.
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While there are many promising algorithms available, there is still a lack of theoretical understanding on how some of them are designed and under which conditions they perform.
This study addressed ATM-related issues, expressed on the set of items submitted to ranking, in which policy interventions can be designed and under which research can be developed.
There is the "Racial Preference Licensing Act," for example, a new Federal law of Ms. Crenshaw's design under which white business owners could obtain a license that would free them to discriminate openly, rather than covertly as they do at present, against black employees and customers.
Because of cost constraints, these studies typically employ a two-stage design, under which a large panel of markers is examined in a subsample of subjects, and the most-promising markers are then examined in all subjects.
When it comes to the analysis of the trial data, for various reasons the precise data structure that is obtained may differ from the design under which t des ∗ was calculated.
This procedure reflected the study design under which Group A was expected to make significant changes between visit 1 and visit 2, then preserve or increase those changes at visit 3, while Group B was expected to make modest changes between visit 1 and visit 2, but greater changes between visit 2 and visit 3.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com