Title: Robust estimation of IIR system's parameter using modified particle swarm optimisation algorithm
Authors: Meera Dash; Trilochan Panigrahi; Renu Sharma
Addresses: Department of ECE, ITER, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha-751030, India ' Department of ECE, National Institute of Technology Goa, Farmagudi, Ponda, Goa-403401, India ' Department of EEE, ITER, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha-751030, India
Abstract: This paper introduces a novel method of robust parameter estimation of infinite impulse response (IIR) system. When training signal contains strong outliers, the conventional squared error-based cost function fails to provide desired performance. Thus a computationally efficient robust cost functions are used here. It is a fact that the IIR system falls in local minima. Thus the gradien-based algorithm which is good for finite impulse response (FIR) system, can not be used for IIR. Therefore the parameters of the IIR system is estimated using modified particle swarm optimisation algorithm. The most used and analysed robust cost functions such as Hubers and saturation nonlinearity function are used in the optimisation algorithm. The simulation results show that the proposed robust algorithms are providing better performance than the Wilcoxon norm-based robust algorithm and conventional error squared-based PSO algorithms.
Keywords: IIR system; impulsive noise; robust estimation; Wilcoxon norm; Hubers cost function; adaptive particle swarm optimisation; saturation nonlinearity.
International Journal of Computational Intelligence Studies, 2019 Vol.8 No.1/2, pp.122 - 142
Received: 15 Mar 2018
Accepted: 15 Jul 2018
Published online: 14 Feb 2019 *