کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
564859 875649 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Distributed and robust parameter estimation of IIR systems using incremental particle swarm optimization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
Distributed and robust parameter estimation of IIR systems using incremental particle swarm optimization
چکیده انگلیسی

In recent years because of substantial use of wireless sensor network the distributed estimation has attracted the attention of many researchers. Two popular learning algorithms: incremental least mean square (ILMS) and diffusion least mean square (DLMS) have been reported for distributed estimation using the data collected from sensor nodes. But these algorithms, being derivative based, have a tendency of providing local minima solution particularly for minimization of multimodal cost function. Hence for problems like distributed parameters estimation of IIR systems, alternative distributed algorithms are required to be developed. Keeping this in view the present paper proposes two population based incremental particle swarm optimization (IPSO) algorithms for estimation of parameters of noisy IIR systems. But the proposed IPSO algorithms provide poor performance when the measured data is contaminated with outliers in the training samples. To alleviate this problem the paper has proposed a robust distributed algorithm (RDIPSO) for IIR system identification task. The simulation results of benchmark IIR systems demonstrate that the proposed algorithms provide excellent identification performance in all cases even when the training samples are contaminated with outliers.


► Proposes a novel distributed population based learning algorithm IPSO.
► Estimates global IIR parameters using IPSO.
► Computes robust distributed IIR parameters using Wilcoxon norm.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 23, Issue 4, July 2013, Pages 1303–1313
نویسندگان
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