Short-time behaviour analysis of fractional-order model of generalized pantograph-type neural networks. Issue 3 (1st October 2016) - Kinh, C. T.; Hien, L. V.; Ke, T. D.
ABSTRACT: In this paper, the problem of short-time behaviour analysis including short-time stability and short-time boundedness is studied for a class of fractional-order generalized pantograph-type neural networks. By extending the comparison principle with Mittag–Leffler functions, explicit conditions are derived in terms of M-matrix inequalities to ensure that the system states are confined in a certain threshold over a pre-specified interval of time. Finally, two numerical examples with simulations are given to demonstrate the effectiveness of the obtained results.