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A novel approach based on recurrent neural networks applied to nonlinear systems optimization
(Elsevier B.V., 2007-01-01)
This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the ...
A novel approach based on recurrent neural networks applied to nonlinear systems optimization
(Elsevier B.V., 2007-01-01)
This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the ...
Transformer Operation at Deep Saturation: Model and Parameter Determination
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCPISCATAWAY, 2012)
This paper proposes a model that adequately describes the operation of the transformer at deep saturation, suitable for power-electronics applications, and a method for determining its parameters. Simulation and experimental ...
Volterra-type models for nonlinear systems identification
(Elsevier Science Inc, 2014-05)
In this work, multi-input multi-output (MIMO) nonlinear process identification is dealt with. In particular, two Volterra-type models are discussed in the context of system identification. These models are: Memory Polynomial ...
Nonlinear dynamics of rotating box FGM beams using nonlinear normal modes
(Elsevier, 2013-01)
In this work an analysis is performed on the nonlinear planar vibrations of a functionally graded beam subjected to a combined thermal and harmonic transverse load in the presence of internal resonance. Adopting the direct ...
A note on influence diagnostics in nonlinear mixed-effects elliptical models
(ELSEVIER SCIENCE BV, 2011)
This paper provides general matrix formulas for computing the score function, the (expected and observed) Fisher information and the A matrices (required for the assessment of local influence) for a quite general model ...
Experimental Modelling of DC Motor for Position Control Systems Involving Nonlinear Phenomena
(Communications in Computer and Information Science, 2020)
On the application of discrete-time Volterra series for the damage detection problem in initially nonlinear systems
(2017-01-01)
Nonlinearities in the dynamical behavior of mechanical systems can degrade the performance of damage detection features based on a linearity assumption. In this article, a discrete Volterra model is used to monitor the ...
Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series
(European Assoc Structural Dynamics, 2014-01-01)
The consideration of nonlinearities in mechanical structures is a question of high importance because several common features as joints, large displacements and backlash may give rise to these kinds of phenomena. However, ...