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Journal of Applied Mathematics
Volume 2014, Article ID 827206, 9 pages
http://dx.doi.org/10.1155/2014/827206
Research Article

A Comparison of Evolutionary Computation Techniques for IIR Model Identification

1Departamento de Electrónica, Universidad de Guadalajara, CUCEI, Avenida Revolución 1500, 44430 Guadalajara, JAL, Mexico
2Centro Universitario Azteca, Unidad de Investigación, Avenida Juárez 340, 44280 Guadalajara, JAL, Mexico
3CUTONALA, Avenida Nuevo Periférico 555, Ejido San José Tateposco, 48525 Tonalá, JAL, Mexico

Received 18 August 2014; Accepted 30 September 2014; Published 25 December 2014

Academic Editor: Xin-She Yang

Copyright © 2014 Erik Cuevas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [7 citations]

The following is the list of published articles that have cited the current article.

  • Qifang Luo, Sen Zhang, Zhiming Li, and Yongquan Zhou, “A Novel Complex-Valued Encoding Grey Wolf Optimization Algorithm,” Algorithms, vol. 9, no. 1, pp. 4, 2015. View at Publisher · View at Google Scholar
  • Akhilesh Gotmare, Sankha Subhra Bhattacharjee, Rohan Patidar, and Nithin V. George, “Swarm and evolutionary computing algorithms for system identification and filter design: A comprehensive review,” Swarm and Evolutionary Computation, 2016. View at Publisher · View at Google Scholar
  • Erik Cuevas, Valentín Osuna, Diego Oliva, Erik Cuevas, Valentín Osuna, and Diego Oliva, “Introduction,” Evolutionary Computation Techniques: A Comparative Perspective, vol. 686, pp. 1–8, 2016. View at Publisher · View at Google Scholar
  • Pedro Lagos-Eulogio, Juan Carlos Seck-Tuoh-Mora, Norberto Hernandez-Romero, and Joselito Medina-Marin, “A new design method for adaptive IIR system identification using hybrid CPSO and DE,” Nonlinear Dynamics, 2017. View at Publisher · View at Google Scholar
  • Dhabitah Lazim, Azlan Mohd Zain, Mahadi Bahari, and Abdullah Hisham Omar, “Review of modified and hybrid flower pollination algorithms for solving optimization problems,” Artificial Intelligence Review, 2017. View at Publisher · View at Google Scholar
  • Yongquan Zhou, Ying Ling, and Qifang Luo, “Lévy Flight Trajectory-Based Whale Optimization Algorithm for Global Optimization,” IEEE Access, pp. 1–1, 2017. View at Publisher · View at Google Scholar
  • Nor Azlina Ab Aziz, Zuwairie Ibrahim, Marizan Mubin, Sophan Wahyudi Nawawi, and Mohd Saberi Mohamad, “Improving Particle Swarm Optimization via Adaptive Switching Asynchronous - Synchronous Update,” Applied Soft Computing, 2018. View at Publisher · View at Google Scholar