Interharmonic parameter intelligent estimation algorithm based on propagator method

被引：0
|
作者：
Chen G.-Z. [1 ]
Chen L.-D. [1 ]
Cai Z.-F. [1 ]
机构：
[1] College of Electrical Engineering, Zhejiang University
来源：
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2011年 / 45卷 / 04期
关键词：
Adaline neural network; Interharmonic; LM algorithm; Multiple signal classification (MUSIC); Propagator;
D O I：
10.3785/j.issn.1008-973X.2011.04.028
中图分类号：
学科分类号：
摘要：
An interharmonic frequency estimation algorithm based on propagator method (PM) was proposed in order to reduce the computational complexity of multiple signal classification (MUSIC). The propagator can be used to construct the noise subspace. The PM didn't involve covariance matrix and eigenvalue decomposition and the priori knowledge of interharmonic number, and had the approximation performance compared with MUSIC. A complex Adaline neural network was employed to obtain amplitudes and phases of harmonics and interharmonics. The proposed complex Adaline structure was based on Levenberg-Marquardt (LM) rule. The algorithm reduced input vectors and weights to half of the number that real Adaline used. These attributes can increase convergence speed. The simulation results show that the algorithm can accurately achieve frequencies, amplitudes and phases of interharmonics without synchronous sampling data.
引用
收藏
页码：759 / 764
页数：5
相关论文
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