WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 13, 2017
Stable Adaptive IIR System Identification Using Particle Swarm Optimization
Authors: ,
Abstract: This paper presents an adaptive IIR system identification method using Particle Swarm Optimization (PSO). System identification is a method for estimating characteristic of an unknown system using the measured input and output signals. In PSO, potential solutions called particles are updated according to simple mathematical formulas of particle’s positions and velocities. However, the IIR system identification methods using PSO have a problem that it is very difficult to get the global optimum solution when the adaptive filter becomes once unstable during system identification. Moreover, the standard PSO has a problem that it tends to converge to local optimal solution because of its strong directivity. In the proposed method, the particle’s velocities are updated using plural better solutions in order to avoid the convergence to local optimal solution and the output signal of an unknown system is used as the feedback signal of the adaptive filter in order to achieve stable system identification. Some simulation results show that the proposed method has higher identification accuracy than conventional methods.
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Pages: 248-255
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 13, 2017, Art. #28