2021
DOI: 10.1007/s11071-021-06208-6
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Input-to-state stability of impulsive reaction–diffusion neural networks with infinite distributed delays

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Cited by 134 publications
(27 citation statements)
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“…In view of the nonlinearity of the navigation dynamics, several solutions have been developed on the Lie group of SE 2 (3), including invariant extended Kalman filter (IEKF) [1], a Riccati observer [26], and a nonlinear stochastic observer [27]. Stochastic filters have been useful in several applications, for instance distributed delays [28] and simultaneous localization and mapping [29]. The main shortcomings of these solutions are 1) the disregard for the IMU measurement noise and 2) the lack of transient and steady-state performance measures.…”
Section: Geometric Stochastic Filter With Guaranteed Performance For Autonomous Navigation Based On Imu and Feature Sensor Fusionmentioning
confidence: 99%
“…In view of the nonlinearity of the navigation dynamics, several solutions have been developed on the Lie group of SE 2 (3), including invariant extended Kalman filter (IEKF) [1], a Riccati observer [26], and a nonlinear stochastic observer [27]. Stochastic filters have been useful in several applications, for instance distributed delays [28] and simultaneous localization and mapping [29]. The main shortcomings of these solutions are 1) the disregard for the IMU measurement noise and 2) the lack of transient and steady-state performance measures.…”
Section: Geometric Stochastic Filter With Guaranteed Performance For Autonomous Navigation Based On Imu and Feature Sensor Fusionmentioning
confidence: 99%
“…For more results on the corresponding fundamental and qualitative dynamical behaviors of impulsive reaction-diffusion systems, we refer to [ 36 , 54 , 55 , 56 , 57 ]. The consideration of impulsive conditions allows us to take into account short-term effects on susceptible cells, infected cells, and free viruses.…”
Section: Model Description and Preliminariesmentioning
confidence: 99%
“…Wei et al considered the model of impulsive reaction-diffusion neural networks with infinite distributed delays and the local and global existence-uniqueness and input-to-state stability were performed in this analysis. 13 The effectiveness of the reaction–diffusion was demonstrated in numerical simulations. Zhu et al designed an adaptive optimal controller based on online iterative algorithm for a class of nonlinear Markov jump systems.…”
Section: Introductionmentioning
confidence: 99%