Neural Networks with Discontinuous/Impact Activations, 2014 Nonlinear Systems and Complexity Series, Vol. 9
Auteurs : Akhmet Marat, Yılmaz Enes
This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural because huge velocities and short distances are usually observed in devices modeling the networks. A discussion of the models, appropriate for the proposed applications, is also provided.
Introduction.- Differential Equations with Piecewise Constant Argument of Generalized Type.- Impulsive Differential Equations.- Periodic Motions and Equilibria of Neural Networks with Piecewise Constant Argument.- Equilibria of Neural Networks with Impact Activation and Piecewise Constant Argument.- Periodic Motions of Neural Networks with Impact Activation and Piecewise Constant Argument.- The Method of Lyapunov Functions: RNNs.- The Lyapunov-Razumikhin Method: CNNs.
Explores questions related to the biological underpinning for models of neural networks
Considers neural networks modeling using differential equations with impulsive and piecewise constant argument discontinuities
Provides all necessary mathematical basics for application to the theory of neural networks
Date de parution : 08-2016
Ouvrage de 168 p.
15.5x23.5 cm
Date de parution : 10-2013
Ouvrage de 168 p.
15.5x23.5 cm
Thèmes de Neural Networks with Discontinuous/Impact Activations :
Mots-clés :
Artificial Intelligence; Chaotic Neural Networks; Cohen-Grossberg Neural Networks; Computational Neural Networks; Impulsive Differential Equations; Lyapnov-Razumikhim Method; Neural Networks; Piecewise Constant Argument; Recurrent Neural Networks; State-dependent Moments of Time; complexity; ordinary differential equations