Digital IIR filter design using differential evolution algorithm
EURASIP Journal on Applied Signal Processing
A Self-Organizing Particle Swarm Optimization Algorithm and Application
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 04
A PSO with quantum infusion algorithm for training simultaneous recurrent neural networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems
IEEE Transactions on Evolutionary Computation
Adaptive IIR filtering algorithms for system identification: ageneral framework
IEEE Transactions on Education
IIR system identification using cat swarm optimization
Expert Systems with Applications: An International Journal
Parameters identification of nonlinear state space model of synchronous generator
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
Bacteria foraging optimisation algorithm for optimal FIR filter design
International Journal of Bio-Inspired Computation
A new design method using opposition-based BAT algorithm for IIR system identification problem
International Journal of Bio-Inspired Computation
A Novel Firefly Algorithm for Optimal Linear Phase FIR Filter Design
International Journal of Swarm Intelligence Research
Entropy based Binary Particle Swarm Optimization and classification for ear detection
Engineering Applications of Artificial Intelligence
Natural Computing: an international journal
International Journal of Hybrid Intelligent Systems
International Journal of Hybrid Intelligent Systems
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System identification is a challenging and complex optimization problem due to nonlinearity of the systems and even more in a dynamic environment. Adaptive infinite impulse response (IIR) systems are preferably used in modeling real world systems because of their reduced number of coefficients and better performance over the finite impulse response filters. Particle swarm optimization (PSO) and its other variants has been a subject of research for the past few decades for solving complex optimization problems. In this paper, PSO with quantum infusion (PSO-QI) is used in identification of benchmark IIR systems and a real world problem in power systems. PSO-QI's performance is compared with PSO and differential evolution PSO (DEPSO) algorithms. The results show that PSO-QI has better performance over these algorithms in identifying dynamical systems.