Decoding neuronal firing and modelling neural networks

1994 ◽  
Vol 27 (3) ◽  
pp. 291-331 ◽  
Author(s):  
L. F. Abbott

Biological neural networks are large systems of complex elements interacting through a complex array of connexions. Individual neurons express a large number of active conductances (Connors et al. 1982; Adams & Gavin, 1986; Llinás, 1988; McCormick, 1990; Hille, 1992) and exhibit a wide variety of dynamic behaviours on time scales ranging from milliseconds to many minutes (Llinás, 1988; Harris-Warrick & Marder, 1991; Churchland & Sejnowski, 1992; Turrigiano et al. 1994).

2009 ◽  
Vol 19 (06) ◽  
pp. 449-456 ◽  
Author(s):  
YONGKUN LI ◽  
TIANWEI ZHANG

In this paper, we investigate the existence and uniqueness of equilibrium point for fuzzy interval delayed neural networks with impulses on time scales. And we give the criteria of the global exponential stability of the unique equilibrium point for the neural networks under consideration using Lyapunov method. Finally, we present an example to illustrate that our results are effective.


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