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Chaotic time series prediction with residual analysis method using hybrid Elman–NARX neural networks
Chaotic time series prediction with residual analysis method using hybrid Elman–NARX neural networks
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Chaotic time series prediction with residual analysis method using hybrid Elman–NARX neural networks

Ardalani-Farsa, Muhammad ; Zolfaghari, Saeed

Neurocomputing (Amsterdam), 2010-08, Vol.73 (13), p.2540-2553 [Periódico revisado por pares]

Elsevier B.V

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2
Sparse augmented Lagrangian algorithm for system identification
Sparse augmented Lagrangian algorithm for system identification
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Sparse augmented Lagrangian algorithm for system identification

Tang, Xiaoquan ; Zhang, Long ; Wang, Xiaolin

Neurocomputing (Amsterdam), 2019-02, Vol.330, p.403-411 [Periódico revisado por pares]

Elsevier B.V

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3
Long-term time series prediction with the NARX network: An empirical evaluation
Long-term time series prediction with the NARX network: An empirical evaluation
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Long-term time series prediction with the NARX network: An empirical evaluation

Menezes, José Maria P. ; Barreto, Guilherme A.

Neurocomputing (Amsterdam), 2008-10, Vol.71 (16), p.3335-3343 [Periódico revisado por pares]

Elsevier B.V

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4
Multi-objective evolutionary framework for non-linear system identification: A comprehensive investigation
Multi-objective evolutionary framework for non-linear system identification: A comprehensive investigation
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Multi-objective evolutionary framework for non-linear system identification: A comprehensive investigation

Hafiz, Faizal ; Swain, Akshya ; Mendes, Eduardo

Neurocomputing (Amsterdam), 2020-04, Vol.386, p.257-280 [Periódico revisado por pares]

Elsevier B.V

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5
Adaptive evolutionary neural control of perturbed nonlinear serial PAM robot
Adaptive evolutionary neural control of perturbed nonlinear serial PAM robot
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Adaptive evolutionary neural control of perturbed nonlinear serial PAM robot

Anh, Ho Pham Huy ; Son, Nguyen Ngoc ; Nam, Nguyen Thanh

Neurocomputing (Amsterdam), 2017-12, Vol.267, p.525-544 [Periódico revisado por pares]

Elsevier B.V

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6
Two-Dimensional (2D) particle swarms for structure selection of nonlinear systems
Two-Dimensional (2D) particle swarms for structure selection of nonlinear systems
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Two-Dimensional (2D) particle swarms for structure selection of nonlinear systems

Hafiz, Faizal ; Swain, Akshya ; Mendes, Eduardo M.A.M.

Neurocomputing (Amsterdam), 2019-11, Vol.367, p.114-129 [Periódico revisado por pares]

Elsevier B.V

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7
Neural activity inspired asymmetric basis function TV-NARX model for the identification of time-varying dynamic systems
Neural activity inspired asymmetric basis function TV-NARX model for the identification of time-varying dynamic systems
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Neural activity inspired asymmetric basis function TV-NARX model for the identification of time-varying dynamic systems

Guo, Yuzhu ; Wang, Lipeng ; Li, Yang ; Luo, Jingjing ; Wang, Kailiang ; Billings, S.A. ; Guo, Lingzhong

Neurocomputing (Amsterdam), 2019-09, Vol.357, p.188-202 [Periódico revisado por pares]

Elsevier B.V

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8
Orthogonal Floating Search Algorithms: From the perspective of nonlinear system identification
Orthogonal Floating Search Algorithms: From the perspective of nonlinear system identification
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Orthogonal Floating Search Algorithms: From the perspective of nonlinear system identification

Hafiz, Faizal ; Swain, Akshya ; Mendes, Eduardo M.A.M.

Neurocomputing (Amsterdam), 2019-07, Vol.350, p.221-236 [Periódico revisado por pares]

Elsevier B.V

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9
Online phoneme recognition using multi-layer perceptron networks combined with recurrent non-linear autoregressive neural networks with exogenous inputs
Online phoneme recognition using multi-layer perceptron networks combined with recurrent non-linear autoregressive neural networks with exogenous inputs
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Online phoneme recognition using multi-layer perceptron networks combined with recurrent non-linear autoregressive neural networks with exogenous inputs

Bonilla Cardona, Diana A. ; Nedjah, Nadia ; Mourelle, Luiza M.

Neurocomputing (Amsterdam), 2017-11, Vol.265, p.78-90 [Periódico revisado por pares]

Elsevier B.V

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10
Innovative NARX recurrent neural network model for ultra-thin shape memory alloy wire
Innovative NARX recurrent neural network model for ultra-thin shape memory alloy wire
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Innovative NARX recurrent neural network model for ultra-thin shape memory alloy wire

Wang, Han ; Song, Gangbing

Neurocomputing (Amsterdam), 2014-06, Vol.134, p.289-295 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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