Abstract—In this paper, we will propose a novel parameter
estimation algorithm which is based on the modified particle
swarm optimization (PSO) algorithm for the Volterra digital
system. In the modified PSO algorithm, another adjusting
factor is added into the velocity updating formula to enhance
the algorithm’s search capacity. On the basis of a series of
input-output data pairs, we wish that the modified PSO
approach can successfully solve for the unknown parameters of
the Volterra digital system. The whole design steps based on the
modified PSO is presented for parameter estimations. Besides,
different sets of algorithm initial conditions are examined to
confirm the feasibility and robustness. Finally, simulation
results sufficiently reveal that the proposed method can
correctly solve for the parameters of the Volterra digital
system.
Index Terms—Parameter estimation, Volterra digital system,
Particle swarm optimization (PSO).
The authors are with the Department of Computer and Communication,
Shu-Te University, Kaohsiung, Taiwan (e-mail: wdchang@stu.edu.tw,
pipn@stu.edu.tw, spshih@stu.edu.tw, s12115260@stu.edu.tw).
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Cite: Wei-Der Chang, Ching-Lung Chi, Shun-Peng Shih, and Bo-Hong Ye, "Parameter Estimation Algorithms for Volterra Digital Systems," International Journal of Future Computer and Communication vol. 6, no. 3, pp. 115-118, 2017.
