Results 11 to 20 of about 4,682,633 (203)

Iterative procedures for identification of nonlinear interconnected systems [PDF]

open access: yes, 2007
This work addresses the identification problem of a discrete-time nonlinear system composed by linear and nonlinear subsystems. Systems in this class will be represented by Linear Fractional Transformations.
Date, P, Pepona, E
core   +6 more sources

Convergence of sequential and asynchronous nonlinear paracontractions [PDF]

open access: yes, 1992
Elsner L, Koltracht I, Neumann M. Convergence of sequential and asynchronous nonlinear paracontractions. Numerische Mathematik. 1992;62(1):305-319.We establish the convergence of sequential and asynchronous iteration schemes for nonlinear paracontracting
Elsner, Ludwig   +2 more
core   +1 more source

Study on a class of Schrödinger elliptic system involving a nonlinear operator [PDF]

open access: yes, 2020
This paper considers a class of Schrödinger elliptic system involving a nonlinear operator. Firstly, under the simple condition on and \u27, we prove the existence of the entire positive bounded radial solutions.
Zhang, Lihong   +3 more
core   +1 more source

Symbolic Computation of Polynomial Conserved Densities, Generalized Symmetries, and Recursion Operators for Nonlinear Differential-Difference Equations [PDF]

open access: yes, 2004
Algorithms for the symbolic computation of polynomial conserved densities, fluxes, generalized symmetries, and recursion operators for systems of nonlinear differential-difference equations are presented. In the algorithms we use discrete versions of the
Jan A. S   +15 more
core   +1 more source

Nonlinear input-normal realizations based on the differential eigenstructure of hankel operators [PDF]

open access: yes, 2005
This paper investigates the differential eigenstructure of Hankel operators for nonlinear systems. First, it is proven that the variational system and the Hamiltonian extension with extended input and output spaces can be interpreted as the Gâteaux ...
Fujimoto, K.,   +3 more
core   +2 more sources

On the convergence of iterative voting: how restrictive should restricted dynamics be? [PDF]

open access: yes, 2015
We study convergence properties of iterative voting procedures. Such procedures are defined by a voting rule and a (restricted) iterative process, where at each step one agent can modify his vote towards a better outcome for himself.
Polukarov, Maria   +6 more
core   +2 more sources

Balanced Realization and Model Order Reduction for Nonlinear Systems Based on Singular Value Analysis [PDF]

open access: yes, 2004
This paper discusses balanced realization and model order reduction for both continuous-time and discrete-time general nonlinear systems based on singular value analysis of the corresponding Hankel operators.
Fujimoto, Kenji   +6 more
core   +2 more sources

Necessary optimality conditions for Lagrange problems involving ordinary control systems described by fractional Laplace operators [PDF]

open access: yes, 2020
In this paper, optimal control problems containing ordinary nonlinear control systems described by fractional Dirichlet and Dirichlet–Neumann Laplace operators and a nonlinear integral performance index are studied. Using smooth-convex maximum principle,
Kamocki, Rafał
core   +1 more source

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane   +3 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +3 more
wiley   +1 more source

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