In this paper,a class of discontinuous Cohen-Grossberg neural networks with timevarying delays is considered.Firstly,under the extended Filippov differential inclusions framework,the problem of periodic solutions of t...In this paper,a class of discontinuous Cohen-Grossberg neural networks with timevarying delays is considered.Firstly,under the extended Filippov differential inclusions framework,the problem of periodic solutions of the considered neural networks with more relaxed conditions imposed on the amplification functions is analyzed by using set-valued mapping and Kakutani's fixed point theorem,which has rarely been used to study such problem.Secondly,the fixed-time synchronization of the error system of the considered neural networks is also investigated by designing a novel control strategy,which can improve not only the previous ones with sign function greatly,but also can reduce the chattering phenomenon.Finally,two numerical examples are presented to further illustrate the validity of the obtained results.展开更多
In this paper, a class of discontinuous neutral-type neural networks (NTNNs) with proportional delays is considered. The targets of the paper are to study the problem of periodic solutions and fixed-time (FXT) stabili...In this paper, a class of discontinuous neutral-type neural networks (NTNNs) with proportional delays is considered. The targets of the paper are to study the problem of periodic solutions and fixed-time (FXT) stabilization of the addressed neural networks. In order to complete the targets, based on set-valued map, differential inclusions theory, coincidence theorem and Hölder inequality technique, some new proportional delay-dependent criteria shown by the inequalities are derived. Based on the fact of the existence of solution, further by applying the FXT stability lemmas and equivalent transformation, the zero solution of closed-loop system achieves FXT stabilization and the corresponding settling-times are estimated. Some previous related works on NTNNs are extended. Finally, one typical example is provided to show the effectiveness of the established results.展开更多
基金Supported by the National Natural Science Foundation of China(62576008)University Annual Scientific Research Plan of Anhui Province(2022AH030023)。
文摘In this paper,a class of discontinuous Cohen-Grossberg neural networks with timevarying delays is considered.Firstly,under the extended Filippov differential inclusions framework,the problem of periodic solutions of the considered neural networks with more relaxed conditions imposed on the amplification functions is analyzed by using set-valued mapping and Kakutani's fixed point theorem,which has rarely been used to study such problem.Secondly,the fixed-time synchronization of the error system of the considered neural networks is also investigated by designing a novel control strategy,which can improve not only the previous ones with sign function greatly,but also can reduce the chattering phenomenon.Finally,two numerical examples are presented to further illustrate the validity of the obtained results.
基金supported by Social Science Fund of Hunan province(Grant No.22JD074)the Research Foundation of Education Bureau of Hunan province(Grant No.22B0912).
文摘In this paper, a class of discontinuous neutral-type neural networks (NTNNs) with proportional delays is considered. The targets of the paper are to study the problem of periodic solutions and fixed-time (FXT) stabilization of the addressed neural networks. In order to complete the targets, based on set-valued map, differential inclusions theory, coincidence theorem and Hölder inequality technique, some new proportional delay-dependent criteria shown by the inequalities are derived. Based on the fact of the existence of solution, further by applying the FXT stability lemmas and equivalent transformation, the zero solution of closed-loop system achieves FXT stabilization and the corresponding settling-times are estimated. Some previous related works on NTNNs are extended. Finally, one typical example is provided to show the effectiveness of the established results.
