Geodesic
Anti-periodic solutions for recurrent neural networks without assuming global Lipschitz conditions
Electronic Journal of Differential Equations, Tome 2010 (2010).

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Summary: In this paper we study recurrent neural networks with time-varying delays and continuously distributed delays. Without assuming global Lipschitz conditions on the activation functions, we establish the existence and local exponential stability of anti-periodic solutions.
Classification : 34C25, 34D40
Keywords: recurrent neural networks, anti-periodic, exponential stability, delay 
@article{EJDE_2010__2010__a22,
     author = {Zhang, Hong and Wu, Yuanheng},
     title = {Anti-periodic solutions for recurrent neural networks without assuming global {Lipschitz} conditions},
     journal = {Electronic Journal of Differential Equations},
     publisher = {mathdoc},
     volume = {2010},
     year = {2010},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/EJDE_2010__2010__a22/}
}
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Zhang, Hong; Wu, Yuanheng. Anti-periodic solutions for recurrent neural networks without assuming global Lipschitz conditions. Electronic Journal of Differential Equations, Tome 2010 (2010). http://geodesic.mathdoc.fr/item/EJDE_2010__2010__a22/