Subspace-Based Rational Interpolation of Analytic Functions From Phase Data

被引:8
作者
Akcay, Hueseyin [1 ]
机构
[1] Anadolu Univ, Dept Elect & Elect Engn, TR-26470 Eskisehir, Turkey
关键词
Phase data; rational interpolation; strong consistency; subspace-based identification; time-delay estimation; IDENTIFICATION; APPROXIMATION; SYSTEMS;
D O I
10.1109/TSP.2009.2033326
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, two simple subspace-based identification algorithms to identify stable linear-time-invariant systems from corrupted phase samples of frequency response function are developed. The first algorithm uses data sampled at nonuniformly spaced frequencies and is strongly consistent if corruptions are zero-mean additive random variables with a known covariance function. However, this algorithm is biased when corruptions are multiplicative, yet it exactly retrieves finite-dimensional systems from noise-free phase data using a finite amount of data. The second algorithm uses phase data sampled at equidistantly spaced frequencies and also has the same interpolation and strong consistency properties if corruptions are zero-mean additive random variables. The latter property holds also for the multiplicative noise model provided that some noise statistics are known a priori. Promising results are obtained when the algorithms are applied to simulated data.
引用
收藏
页码:1069 / 1081
页数:13
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