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In the paper, the exponential synchronisation for delayed Clifford-valued coupled switched neural networks via static event-triggering rule is studied. Firstly, the drive-response systems for delayed Clifford-valued coupled neural network models are established. So as to avoid the non-commutativity issue of Clifford number multiplication, the original n-dimensional Clifford-valued models are decomposed into $ 2 ^mn $ 2 m n -dimensional real-valued models. On this basis, the error dynamics system is constructed, and then some new sufficient conditions are presented of the exponential synchronisation for the considered neural network models by using Lyapunov–Krasovskii (L-K) functional approach and the technique of linear matrix inequality. Finally, the effectiveness of the results are verified by numerical simulations. [ABSTRACT FROM AUTHOR]

This paper is devoted to the investigation of the delay-dependent filtering problem for a class of continuous-time singular Markov jump systems with Wiener process and generally uncertain transition rates (GUTRs). In the GUTR stochastic singular model under consideration, based on an auxiliary vector function, by employing an integral inequality and some appropriate free-weighting matrices, the delay-dependent sufficient conditions are derived, which ensure that the filtering error system is stochastically admissible. And then, a singular filter is designed such that the filtering error system is not only regular, impulse-free and stochastically stable, but also satisfies a prescribed performance for all time-varying delays no larger than a given upper bound. Furthermore, the solvability conditions of the filtering problem are deduced in terms of a new type of candidate Lyapunov-Krasovskii function and a set of matrix inequalities. Finally, simulation examples are performed to validate the proposed method in this paper. [ABSTRACT FROM AUTHOR]

The mean-square admissibility problem of stochastic T–S fuzzy singular systems via an extended quadratic Lyapunov function is investigated in this paper. Comparing with the existing quadratic Lyapunov function method, the extended quadratic Lyapunov function method can relax stabilization conditions. Firstly, the sufficient condition is given for the mean-square admissibility of stochastic T–S fuzzy singular systems based on an extended quadratic Lyapunov function approach. Secondly, two sufficient conditions for mean-square admissibility of closed-loop systems via the parallel distributed compensation (PDC) fuzzy controller and non-parallel distributed compensation (non-PDC) fuzzy controller are proposed. Furthermore, through the extended quadratic Lyapunov function method and non-PDC fuzzy controller, the less conservative mean-square admissibility conditions on solving fuzzy controllers are derived in terms of linear matrix inequalities (LMIs). Finally, some simulation examples are given to show the effectiveness and merits of the proposed fuzzy controller design methodology. [ABSTRACT FROM AUTHOR]

The stability and exact observability problems of discrete stochastic singular systems based on generalised Lyapunov equations are investigated in this study. First, some new conditions for the existence and uniqueness of the solutions to discrete stochastic singular systems are given, and then, a new type generalised Lyapunov equation is proposed. Based on these results, a sufficient condition for stochastic stability of the systems is derived via the solution of the proposed generalised Lyapunov equation. Moreover, the relationship between the solution of the generalised Lyapunov equation and structure properties of discrete stochastic singular systems is discussed as well. Especially, the relationship between the solution of the generalised Lyapunov equation and the stochastic stability of discrete stochastic singular systems with non‐causal behaviour is studied for the first time. Second, another new type generalised Lyapunov equation for exactly observable discrete stochastic singular systems is proposed. Meanwhile, the relationships among the stochastic stability of the systems, exact observability and the solution of the proposed generalised Lyapunov equation are investigated. Finally, simulation examples are worked out to validate the effectiveness of the obtained theoretical results. [ABSTRACT FROM AUTHOR]

• Multiple search equations with different search abilities are adopted or designed. • Multiple strategies with complementary advantages are fused. • Evolution ratio is proposed as an indicator to reflect the adaptability of search equation. • An adaptive mechanism is proposed to adjust the selection of search equation. Although artificial bee colony (ABC) algorithm is more and more popular in solving complex problems, slow convergence rate limits its wide application. ABC with small population can use the limited function evaluation times more efficiently since it can avoid unnecessary searches. However, ABC with small population cannot ensure population diversity, and when the algorithm is weak or unstable, it may fall into local optimum easily. So based on the latest research, we are motivated to propose a stabler and more efficient algorithm design to improve the search ability of ABC with small population by the fusion of multiple search strategies, which used together for the employed bees and the onlooker bees. Firstly we select and design multiple strategies with different search abilities of exploration and exploitation. Secondly, we propose an evolution ratio, which is an indicator to fully reflect the adaptability of the search strategy. Thirdly, we design different fusion methods according to the characteristics of the strategies, in which the search strategy with high exploration is maintained at a certain frequency throughout the whole search process of the employed bees, and the selections of the other two search strategies are adjusted according to evolution ratio adaptively in the employed bee phase and the onlooker bee phase. In the end, a novel algorithm called MFABC is proposed, which can realize efficiently multi-strategy cooperative search according to the requirements of different problems and different search stages. Experimental results on a set of benchmark functions have shown the accuracy, stability, efficiency and convergence rate of MFABC. [ABSTRACT FROM AUTHOR]