A comparison of evolutionary computation techniques for IIR model identification

DOI10.1155/2014/827206zbMath1463.93047OpenAlexW2164527846WikidataQ59052645 ScholiaQ59052645MaRDI QIDQ2336757

Salvador Hinojosa, Omar Avalos, Daniel Zaldivar, Erik Cuevas, Jorge A. Gálvez, Marco Perez-Cisneros

Publication date: 19 November 2019

Published in: Journal of Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/827206

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) System identification (93B30) Impulsive control/observation systems (93C27)

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Cites Work

• Nonlinear system identification and control using state transition algorithm
• Analysis of the dynamics of a memoryless nonlinear gradient IIR adaptive notch filter
• Advances in evolutionary algorithms. Theory, design and practice.
• Digital image processing for non-linear system identification
• A new design method based on artificial bee colony algorithm for digital IIR filters
• A new mutated quantum-behaved particle swarm optimizer for digital IIR filter design
• A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 special session on real parameter optimization
• An electromagnetism-like mechanism for global optimization
• Adaptive parameter identification of linear SISO systems with unknown time-delay
• Lévy flights, non-local search and simulated annealing
• Flower Pollination Algorithm for Global Optimization

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