[1] Alikhanov A A. A priori estimates for solutions of boundary value problems for fractional-order equations. Differ Equat, 2010, 46(5):660-666 [2] Asadisaghandi J, Tahmasebi P. Comparative evaluation of back-propagation neural network learning algorithms and empirical correlations for prediction of oil PVT properties in Iran oil fields. J Pet Sci Eng, 2011, 78(2):464-475 [3] Baker C T H, Tang A. Generalized Halanay inequalities for Volterra functional differential equations and discretized versions. Invited plenary talk, in:Volterra Centennial Meeting, UTA Arlington, June, 1996 [4] Boroomand A, Menhaj M B. Fractional-order Hopfield neural networks//Koppen M, Kasabov N, Coghill G, eds. Advances in Neuro-Information Processing. Berlin:Springer, 2008:883-890 [5] Caponetto R, Fortuna L, Porto D. Bifurcation and chaos in noninteger order cellular neural networks. Int J Bifurc Chaosm, 1998, 8:1527-1539 [6] Chen L, Chai Y, Wu R, Ma T, Zhai H. Dynamic analysis of a class of fractional-order neural networks with delay. Neurocomputing, 2013, 111:190-194 [7] Concezzi M, Spigler R. Some analytical and numerical properties of the Mittag-Leffler functions. Fract Calc Anal Appl, 2015, 18(10):64-94 [8] Ding X, Cao J, Zhao X, Alsaadi F E. Finite-time stability of fractional-order complex-valued neural networks with time delays. Neural Process Lett, 2017, 46:561-580 [9] Ding X, Cao J, Zhao X, Alsaadi F E. Mittag-Leffler synchronization of delayed fractional-order bidirectional associative memory neural networks with discontinuous activations:state feedback control and impulsive control schemes. Proc Royal Soc A:Math, Phys Eng Sci, 2017, 473(2204):DOI:10.1098/rspa.2017.0322 [10] Gorenflo R, Kilbas A A, Mainardi F, Rogosin S Y. Mittag-Leffler Functions, Related Topics and Applications. Springer Monographs in Mathematics. New York:Dordrecht, London Springer Heidelberg, 2014 [11] Halanay A. Differential Equations. New York:Academic Press, 1996 [12] Hien L V, Phat V, Trinh H. New generalized Halanay inequalities with applications to stability of nonlinear non-autonomous time-delay systems. Nonlinear Dyn, 2015, 82:563-575 [13] Hopfield J J. Neural networks and physical systems with emergent collective computational abilities. Proc Natl Acad Sci, 1982, 79:2554-2558 [14] Jiang M, Shen Y, Liao X. On the global exponential stability for functional differential equations. Communications in Nonlinear Science and Numerical Simulation, 2005, 10:705-713 [15] Jong-Se L, Jungwhan K. Reservoir Porosity and Permeability Estimation from Well Logs using Fuzzy Logic and Neural Networks. SPE Asia Pacific Oil and Gas Conference and Exhibition. Perth, Australia, 2004 [16] Kaslik E, Sivasundaram S. Dynamics of fractional-order neural networks. Proceedings of International Joint Conference on Neural Networks, 2011:611-618 [17] Kaydani H, Mohebbi A, Baghaie A. Neural fuzzy system development for the prediction of permeability from wireline data based on fuzzy clustering. Pet Sci Eng, 2012, 30(19):2036-2045 [18] Li Y, Chen Y Q, Podlubny I. Mittag Leffler stability of fractional order nonlinear dynamic systems. Automatica, 2009, 45:1965-1969 [19] Li Y, Chen Y Q, Podlubny I. Stability of fractional-order nonlinear dynamic systems:Lyapunov direct method and generalized Mittag Leffler stability. Comput Math Appl, 2010, 59:1810-1821 [20] Lim J -S. Reservoir properties determination using fuzzy logic and neural networks from well data in offshore Korea. J Pet Sci Engi, 2005, 49(3/4):182-192 [21] Lippmann R P, Shahian D M. Coronary artery bypass risk prediction using neural networks. Ann Thorac Surg, 1997, 63:1635-1643 [22] Liu B, Lu W, Chen T. Generalized Halanay inequalities and their applications to neural networks with unbounded time-varying delays. IEEE Trans Neural Netw, 2011, 22(9):1508-1513 [23] Lou X, Ye Q, Cui B. Exponential stability of genetic regulatory networks with random delays. Neurocomputing, 2010, 73:759-69 [24] Luan X, Shi P, Liu F. Robust adaptive control for greenhouse climate using neural networks. International Journal of Robust and Nonlinear Control, 2011, 21(7):815-826 [25] Mainardi F. On some properties of the Mittag-Leffler function Eα(-tα), completely monotone for t>0 with 0 < α < 1. Discrete Continuous Dynamical Systems-Series B, 2014, 10(7):2267-2278 [26] Mathai A M. Mittag-Leffler Functions and Fractional Calculus, Chapter 3, Recent Developments and Recent Applications in Statistics and Astrophysics, Proceedings of the third SERC School on Special Functions and Functions of Matrix Argument, held 14 March-15 April, 2005 at the Centre for Mathematical Sciences, Pala, India Compiled by A M Mathai Publication No 32. Centre for Mathematical Sciences, Pala Campus, Kerala State, India, 2005, p.91 [27] Michalski M W. Derivatives of Noninteger Order and their Applications[D]. Polska Akademia Nauk, 1993 [28] Mohamed S, Gopalsamy K. Continuous and discrete Halanay-type inequalities. Bull Austral Math Soc, 2000, 61:371-385 [29] Niamsup P. Stability of time-varying switched systems with time-varying delay. Nonlinear Analysis:Hybrid Systems, 2009, 3:631-639 [30] Peng X, Wu H, Song K, Shi J. Global synchronization in finite time for fractional-order neural networks with discontinuous activations and time delays. Neural Netw, 2017, 94:46-54 [31] Podlubny I. Fractional Differential Equations, Vol 198. Academic Press, 1998 [32] Ramgulam A, Ertekin T, Flemings P B. Utilization of Artificial Neural Networks in the Optimization of History Matching. SPE Latin American and Caribbean Petroleum Engineering Conference, SPE 107468. Buenos Aires, Argentina, 2007:15-18 April [33] Ren F, Cao F, Cao J. Mittag-Leffler stability and generalized Mittag-Leffler stability of fractional-order gene regulatory networks. Neurocomputing, 2015, 160:185-190 [34] Rogers S J, Fang J H, Karr C L, Stanley D A. Determination of lithology from well logs using a neural network. Am Assoc Pet Geol Bull, 1992, 76:731-739 [35] Shahkarami A, Mohaghegh S D, Gholami V, Haghighat S A. Artificial Intelligence (AI) Assisted History Matching, SPE-169507-MS. 2014 [36] Silva P C, Maschio C, Schiozer D J. Use of neuro-simulation techniques as proxies to reservoir simulator:application in production history matching. J Pet Sci Eng, 2007, 57:273-280 [37] Song C, Cao J. Dynamics in fractional-order neural networks. Neurocomputing, 2014, 142:494-498 [38] Song K, Wu H, Wang L. Lur'e-Postnikov Lyapunov functional technique to global Mittag-Leffler stability of fractional-order neural networks with piecewise constant argument. Neurocomputing, 2018, 302(9):23-32 [39] Tatar N-e. The decay rate for a fractional differential equation. J Math Anal Appl, 2004, 295:303-314 [40] Tian H. The exponential asymptotic stability of singularly perturbed delay differential equations with a bounded lag. J Math Anal Appl, 2002, 270:143-149 [41] Wang H, Yu Y, Wen G. Stability analysis of fractional-order Hopfield neural networks with time delays. Neural Netw, 2014, 55:98-109 [42] Wen L, Yu Y, Wang W. Generalized Halanay inequalities for dissipativity of Volterra functional differential equations. J Math Anal Appl, 2008, 347:169-178 [43] Wu H, Wang L, Niu P, Wang Y. Global projective synchronization in finite time of nonidentical fractionalorder neural networks based on sliding mode control strategy. Neurocomputing, 2017, 235:264-273 [44] Wu H, Zhang X, Xue S, Wang L, Wang Y. LMI conditions to global Mittag-Leffler stability of fractional-order neural networks with impulses. Neurocomputing, 2016, 193:148-154 [45] Zeng Z, Wang J, Liao X. Global asymptotic stability and global exponential stability of neural networks with unbounded time-varying delays. IEEE Trans Circuits Syst, 2005, 52:168-173 [46] Zhang J, Jin X. Global stability analysis in delayed Hopfield neural network models. Neural Networks, 2000, 13:745-753 [47] Zhang S, Yu Y, Wang H. Mittag-Leffler stability of fractional-order Hopfield neural networks. Nonlinear Anal Hybrid Syst, 2015, 16:104-121 |