Iir Model Identification Using Batch-recursive Adaptive Simulated Annealing Algorithm

نویسنده

  • Sheng Chen
چکیده

System identification using infinite-impulse-response (IIR) model is considered. Because the error surface of IIR filters is generally multi-modal, global optimisation techniques are preferred in order to avoid local minima. An efficient global optimisation method, called the adaptive simulated annealing (ASA), is adopted, and a new batch-recursive ASA algorithm is developed for on-line identification. Simulation study shows that the proposed approach is accurate and has a fast convergence rate, and the results obtained demonstrate that the ASA offers a viable tool to IIR model identification.

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تاریخ انتشار 2000