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  NL q Theory: unifications in the theory of neural networks, systems and control (1995) [2 citations — 2 self]

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by Johan Suykens, Bart De Moor, Joos Vandewalle
European Symposium on Artificial Neural Networks (ESANN '95), Brussels Belgium
ftp://ftp.esat.kuleuven.ac.be/pub/SISTA/suykens/reports/nlqesann95.ps.Z
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Abstract:

The aim of this paper is to present some results on NLq theory, a new theory that originated from the study of stability criteria for neural state space control systems. NLq s represent a large class of nonlinear dynamical systems in state space form and contain a number of q layers of an alternating sequence of linear and nonlinear operators that satisfy a sector condition. NLq s have many special cases in neural networks, systems and control. Among the examples are e.g. the Hopfield network, Generalized Cellular Neural Networks, Locally Recurrent Globally Feedforward neural

Citations

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13 Nonlinear system identification using neural state space models, applicable to robust control design – Suykens, Moor, et al. - 1995
12 Stability analysis of generalized cellular neural networks – Guzelis, Chua - 1993
6 Stability criteria for neural control systems – Suykens, Moor, et al. - 1995
5 Asymptotic stability of discrete time systems with saturation nonlinearities with applications to digital filters – Liu, Michel - 1992
2 NLq theory and its extension to theory – Suykens, Moor, et al. - 1994
2 Generalized Cellular Neural Networks represented in the NLq framework – Suykens, Vandewalle - 1994
1 Neural state space model framework for identification and control with global asymptotic stability criteria – Suykens, Moor, et al.
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