WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/9997445,
	  title     = {Improved Exponential Stability Analysis for Delayed Recurrent Neural Networks},
	  author    = {Miaomiao Yang and  Shouming Zhong},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper studies the problem of exponential stability analysis for recurrent neural networks with time-varying delay.By establishing a suitable augmented LyapunovCKrasovskii function and a novel sufficient condition is obtained to guarantee the exponential stability of the considered system.In order to get a less conservative results of the condition,zero equalities and reciprocally convex approach are employed. The several exponential stability criterion proposed in this paper is simpler and effective. A numerical example is provided to demonstrate the feasibility and effectiveness of our results.
},
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {8},
	  number    = {1},
	  year      = {2014},
	  pages     = {153 - 159},
	  ee        = {https://publications.waset.org/pdf/9997445},
	  url   	= {https://publications.waset.org/vol/85},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 85, 2014},
	}