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Journal ArticleDOI

An iterative method for the identification of nonlinear systems using a Hammerstein model

Kumpati S. Narendra, +1 more
- 01 Jul 1966 - 
- Vol. 11, Iss: 3, pp 546-550
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TLDR
In this article, an iterative method is proposed for the identification of nonlinear systems from samples of inputs and outputs in the presence of noise, which consists of a no-memory gain (of an assumed polynomial form) followed by a linear discrete system.
Abstract
An iterative method is proposed for the identification of nonlinear systems from samples of inputs and outputs in the presence of noise. The model used for the identification consists of a no-memory gain (of an assumed polynomial form) followed by a linear discrete system. The parameters of the pulse transfer function of the linear system and the coefficients of the polynomial non-linearity are alternately adjusted to minimize a mean square error criterion. Digital computer simulations are included to demonstrate the feasibility of the technique.

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Citations
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Nonlinear identification and self-learning CMAC neural network based control system of laser welding process

TL;DR: In this article, a self-learning CMAC neural network based control system is designed for the laser welding process in order to improve the performance, a PID controller is attached to it.
Dissertation

Técnicas de identificación algebraicas y espectrales de señales armónicas. Aplicaciones en mecatrónica y economía

TL;DR: The problem of the identificación de senales armonicas abarca un amplio rango of aplicaciones procedentes of a disciplina such as the Mecatronica or the Economia as discussed by the authors.
Proceedings ArticleDOI

Nonlinear adaptive digital filters using parallel neural networks

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Journal ArticleDOI

Identification of Hammerstein Model Based on Quantum Genetic Algorithm

TL;DR: Compared with the genetic algorithm, quantum genetic algorithm is an effective swarm intelligence algorithm, its salient features of the algorithm parameters, small population size, and the use of Quantum gate update populations, greatly improving the recognition in the optimization of speed and accuracy.
Patent

Model-plant mismatch detection using model parameter data clustering for paper machines or other systems

TL;DR: In this paper, a method is proposed to identify one or more values for model parameters of at least one model associated with a process using additional data associated with the process, and to detect a mismatch between the model and the process in response to determining that at least some of these values fall outside of the one or multiple clusters.
References
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Journal ArticleDOI

A technique for the identification of linear systems

TL;DR: In this paper, an iterative technique is proposed to identify a linear system from samples of its input and output in the presence of noise by minimizing the mean-square error between system and model outputs.
Journal ArticleDOI

On the Identification Problem

TL;DR: In this paper, the identification of zero-memory multipoles and two-poles of class n_1 was studied, where the test signals are sine waves of different amplitudes and frequencies, and the measured quanity is the describing function of the device.
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