As the theory of the fractional order differential equation becomes mature gradually, the fractional order neural networks become a new hotspot.The robust stability of a class of fractional order Hopfield neural netwo...As the theory of the fractional order differential equation becomes mature gradually, the fractional order neural networks become a new hotspot.The robust stability of a class of fractional order Hopfield neural network with the Caputo derivative is investigated in this paper. The sufficient conditions to guarantee the robust stability of the fractional order Hopfield neural networks are derived by making use of the property of the Mittag-Leffler function, comparison theorem for the fractional order system, and method of the Laplace integral transform. Furthermore, a numerical simulation example is given to illustrate the correctness and effectiveness of our results.展开更多
Acid extraction methods have been used in the last half century to selectively extract the CO_(2)produced from different carbonate minerals in mixed samples.However,these methods are often time-consuming and labor int...Acid extraction methods have been used in the last half century to selectively extract the CO_(2)produced from different carbonate minerals in mixed samples.However,these methods are often time-consuming and labor intensive.Their application to clumped isotope(Δ47)analysis has not been demonstrated.We propose here an acid extraction method with phosphoric acid for bulk stable and clumped isotope analysis that treats mixtures of calcite and dolomite the same regardless of the proportional composition.CO_(2)evolved from calcite is extracted by allowing a reaction with phosphoric acid to proceed for 10 min at 50℃.We then extract CO_(2)evolved from dolomite by rapid ramping the acid temperature from 50 to 90℃and allowing the reaction to complete.The experimental results show that our method yields accurate calcite and dolomiteΔ_(47)values from mixed samples under different proportional compositions.Our method also displays equal or higher accuracy for calciteδ^(13)C and dolomiteδ^(13)C andδ^(18)O values from mixtures when compared to previous studies.Our approach exhibits higher sample throughput than previous methods,is adequate for clumped isotopic analysis and simplifies the reaction progression from over 24 h to less than 2 h,while maintaining relatively high isotopic obtaining accuracy.It yet poorly resolves calciteδ18O values,as found with previous methods.展开更多
基金supported by the Natural Science Foundation of Shandong Province under Grant No.ZR2014AM006
文摘As the theory of the fractional order differential equation becomes mature gradually, the fractional order neural networks become a new hotspot.The robust stability of a class of fractional order Hopfield neural network with the Caputo derivative is investigated in this paper. The sufficient conditions to guarantee the robust stability of the fractional order Hopfield neural networks are derived by making use of the property of the Mittag-Leffler function, comparison theorem for the fractional order system, and method of the Laplace integral transform. Furthermore, a numerical simulation example is given to illustrate the correctness and effectiveness of our results.
基金funded by the fellowship of the China Postdoctoral Science Foundation(No.2020M682134)the National Natural Science Foundation of China(Nos.41872149,42076220)the Shandong Postdoctoral Innovation Research Project。
文摘Acid extraction methods have been used in the last half century to selectively extract the CO_(2)produced from different carbonate minerals in mixed samples.However,these methods are often time-consuming and labor intensive.Their application to clumped isotope(Δ47)analysis has not been demonstrated.We propose here an acid extraction method with phosphoric acid for bulk stable and clumped isotope analysis that treats mixtures of calcite and dolomite the same regardless of the proportional composition.CO_(2)evolved from calcite is extracted by allowing a reaction with phosphoric acid to proceed for 10 min at 50℃.We then extract CO_(2)evolved from dolomite by rapid ramping the acid temperature from 50 to 90℃and allowing the reaction to complete.The experimental results show that our method yields accurate calcite and dolomiteΔ_(47)values from mixed samples under different proportional compositions.Our method also displays equal or higher accuracy for calciteδ^(13)C and dolomiteδ^(13)C andδ^(18)O values from mixtures when compared to previous studies.Our approach exhibits higher sample throughput than previous methods,is adequate for clumped isotopic analysis and simplifies the reaction progression from over 24 h to less than 2 h,while maintaining relatively high isotopic obtaining accuracy.It yet poorly resolves calciteδ18O values,as found with previous methods.
