An R library for nonlinear black-box system identification-Reference-Cited by-同舟云学术

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An R library for nonlinear black-box system identification

Published:2020-01 Issue: Volume:11 Page:100495
ISSN:2352-7110
Container-title:SoftwareX
language:en
Short-container-title:SoftwareX

Author:

Ayala Helon Vicente Hultmann,Gritti Marcos Cesar,dos Santos Coelho Leandro

Funder

CAPES

National Council of Scientific and Technologic Development of Brazil — CNPq

FA

Publisher

Elsevier BV

Subject

Computer Science Applications,Software

Reference36 articles.

1. Computational intelligence methods applied to nonlinear black-box system identification;Ayala,2016

2. Representations of non-linear systems: the NARMAX model;Chen;Internat J Control,1989

3. Identification of nonlinear systems using NARMAX model;Rahrooh;Nonlinear Anal TMA,2009

4. A novel APSO-aided weighted LSSVM method for nonlinear hammerstein system identification;Ma;J Franklin Inst B,2017

5. A type-2 fuzzy wavelet neural network for system identification and control;Abiyev;J Franklin Inst B,2013

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