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IJCNN
2007
IEEE
15 years 3 months ago
System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks
— A single biological neuron is able to perform complex computations that are highly nonlinear in nature, adaptive, and superior to the perceptron model. A neuron is essentially ...
Manish Saggar, Tekin Meriçli, Sari Andoni, ...
69
Voted
CDC
2009
IEEE
133views Control Systems» more  CDC 2009»
15 years 2 months ago
A symbolic model approach to the digital control of nonlinear time-delay systems
— In this paper we propose an approach to control design of nonlinear time–delay systems, which is based on the construction of symbolic models, where each symbolic state and e...
Giordano Pola, Pierdomenico Pepe, Maria Domenica D...
AUTOMATICA
2008
154views more  AUTOMATICA 2008»
14 years 9 months ago
Approximately bisimilar symbolic models for nonlinear control systems
Control systems are usually modeled by differential equations describing how physical phenomena can be influenced by certain control parameters or inputs. Although these models ar...
Giordano Pola, Antoine Girard, Paulo Tabuada
CDC
2009
IEEE
148views Control Systems» more  CDC 2009»
15 years 2 months ago
State estimation of the three-tank system using a multiple model
— This paper addresses the exact transformation of nonlinear systems into a multiple model form with unmeasurable premise variables. The multiple model structure serves to treat ...
Anca Maria Nagy, Benoît Marx, Gilles Mourot,...
TSP
2008
134views more  TSP 2008»
14 years 9 months ago
Computational Algorithms for Wavelet Identification of Nonlinearities in Hammerstein Systems With Random Inputs
Abstract-- Simple and efficient computational algorithms for nonparametric wavelet-based identification of nonlinearities in Hammerstein systems driven by random signals are propos...
Przemyslaw Sliwinski, Zygmunt Hasiewicz