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- Publisher
- Springer Journals
- Copyright
- Copyright © 2016 by The Natural Computing Applications Forum
- Subject
- Computer Science; Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Probability and Statistics in Computer Science; Computational Science and Engineering; Image Processing and Computer Vision; Computational Biology/Bioinformatics
- ISSN
- 0941-0643
- eISSN
- 1433-3058
- DOI
- 10.1007/s00521-016-2201-3
- Publisher site
- See Article on Publisher Site
Abstract
This paper presents a hybrid approach for infinite impulse response (IIR) system identification, called ABC-PS, that combines artificial bee colony (ABC) and tissue P systems. A tissue P system with fully connected structure of cells has been considered as its computing framework. A modification of ABC was developed as evolution rules for objects according to fully connected structure and communication mechanism. With the control of the object’s evolution-communication mechanism, the tissue P system designed can effectively and efficiently identify the optimal filter coefficients for an IIR system. The performance of ABC-PS was compared with artificial bee colony and several other evolutionary algorithms. Simulation results show that ABC-PS is superior or comparable to the other algorithms for the employed examples and can be efficiently used for IIR system identification.
Journal
Neural Computing and Applications – Springer Journals
Published: Feb 4, 2016