Displaying similar documents to “Finite-time topological identification of complex network with time delay and stochastic disturbance”

Passivity analysis of uncertain stochastic neural network with leakage and distributed delays under impulsive perturbations

Senthil Raj, Raja Ramachandran, Samidurai Rajendiran, Jinde Cao, Xiaodi Li (2018)

Kybernetika

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In this paper, the problem of passivity analysis for a class of uncertain stochastic neural networks with mixed delays and impulsive control is investigated. The mixed delays include constant delay in the leakage term, discrete and distributed delays. The discrete delays are assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By using Lyapunov stability theory, stochastic analysis, linear...

Finite-time outer synchronization between two complex dynamical networks with time delay and noise perturbation

Zhi-cai Ma, Yong-zheng Sun, Hong-jun Shi (2016)

Kybernetika

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In this paper, the finite-time stochastic outer synchronization and generalized outer synchronization between two complex dynamic networks with time delay and noise perturbation are studied. Based on the finite-time stability theory, sufficient conditions for the finite-time outer synchronization are obtained. Numerical examples are examined to illustrate the effectiveness of the analytical results. The effect of time delay and noise perturbation on the convergence time are also numerically...

Stabilization of partially linear composite stochastic systems via stochastic Luenberger observers

Patrick Florchinger (2022)

Kybernetika

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The present paper addresses the problem of the stabilization (in the sense of exponential stability in mean square) of partially linear composite stochastic systems by means of a stochastic observer. We propose sufficient conditions for the existence of a linear feedback law depending on an estimation given by a stochastic Luenberger observer which stabilizes the system at its equilibrium state. The novelty in our approach is that all the state variables but the output can be corrupted...

Stochastic performance measurement in two-stage network processes: A data envelopment analysis approach

Alireza Amirteimoori, Saber Mehdizadeh, Sohrab Kordrostami (2022)

Kybernetika

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In classic data envelopment analysis models, two-stage network structures are studied in cases in which the input/output data set are deterministic. In many real applications, however, we face uncertainty. This paper proposes a two-stage network DEA model when the input/output data are stochastic. A stochastic two-stage network DEA model is formulated based on the chance-constrained programming. Linearization techniques and the assumption of single underlying factor of the data are used...