This paper is concerned with fractional-order bidirectional associative memory(BAM) neural networks with time delays. Applying Laplace transform, the generalized Gronwall inequality and estimates of Mittag–Leffler fu...This paper is concerned with fractional-order bidirectional associative memory(BAM) neural networks with time delays. Applying Laplace transform, the generalized Gronwall inequality and estimates of Mittag–Leffler functions, some sufficient conditions which ensure the finite-time stability of fractional-order bidirectional associative memory neural networks with time delays are obtained. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results.展开更多
基金Supported by National Natural Science Foundation of China under Grant Nos.61673008,11261010,11101126Project of High–Level Innovative Talents of Guizhou Province([2016]5651)+2 种基金Natural Science and Technology Foundation of Guizhou Province(J[2015]2025 and J[2015]2026)125 Special Major Science and Technology of Department of Education of Guizhou Province([2012]011)Natural Science Foundation of the Education Department of Guizhou Province(KY[2015]482)
文摘This paper is concerned with fractional-order bidirectional associative memory(BAM) neural networks with time delays. Applying Laplace transform, the generalized Gronwall inequality and estimates of Mittag–Leffler functions, some sufficient conditions which ensure the finite-time stability of fractional-order bidirectional associative memory neural networks with time delays are obtained. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results.
