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- W2600485963 abstract "This paper studies a recently proposed continuous-time distributed self-appraisal model with time-varying interactions among a network of $n$ individuals which are characterized by a sequence of time-varying relative interaction matrices. The model describes the evolution of the social-confidence levels of the individuals via a reflected appraisal mechanism in real time. We first show by example that when the relative interaction matrices are stochastic (not doubly stochastic), the social-confidence levels of the individuals may not converge to a steady state. We then show that when the relative interaction matrices are doubly stochastic, the $n$ individuals' self-confidence levels will all converge to $1/n$, which indicates a democratic state, exponentially fast under appropriate assumptions, and provide an explicit expression of the convergence rate." @default.
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- W2600485963 date "2017-12-01" @default.
- W2600485963 modified "2023-09-26" @default.
- W2600485963 title "On convergence rate of a continuous-time distributed self-appraisal model with time-varying relative interaction matrices" @default.
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- W2600485963 doi "https://doi.org/10.1109/cdc.2017.8264257" @default.
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