B. Jaishankar, Department of Electronics and Communication Engineering KPR Institute of Engineering and Technology, India.
V. Govindaraj, Assistant Professor, Department of Electronics and Communication Engineering, Dr.NGP Institute of Technology, India.
Srikanth, Design Engineer, Simulus Automation, Chennai, India.
Online First : 30 December 2020
Publisher Name : IJAICT India Publications, India.
Print ISBN : 978-81-950008-0-7
Online ISBN : 978-81-950008-1-4
Page :095-099
Abstract
In the modern world, the digital signal processing embeds more in real time applications. Several researchers focused on filtering process to identify the limitation in traditional methods. In this article, the meta-heuristic algorithm is deployed for optimizing infinite impulse response (IIR) filter design. The traditional IIR filter results create computational complexity and its performance is worse in the case of a noisy environment. In signal processing, IIR plays several roles in filtering and monitoring the signal amplitude. The African Buffalo Optimization (ABO) is quite easy for implementation and its performance outcomes solved many problems in various domains. Hence, it is selected for solving IIR filter problems for obtaining optimal filter coefficients. Initially, IIR filter is designed for different orders under ABO concept. The ABO based IIR filter’s performance is superior to those obtained by Genetic Algorithm and cuckoo search algorithm. The proposed method’s performance result proves that it has a smaller magnitude error and phase error with fast convergence rate.
Keywords
Signal processing algorithms, Genetic Algorithms, African Buffalo Optimization, IIR filter design, Optimal Delay.
Cite this article
B. Jaishankar, V. Govindaraj, Srikanth, “IIR Filter Design Using African Buffalo Optimization”, Innovations in Information and Communication Technology, pp. 095-099, December 2020.
Copyright
© 2020 B. Jaishankar, V. Govindaraj, Srikanth. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
