NI Boyi, XIAO Deyun. Optimal Nonuniform Sampling for System Identification on Sparsely Sampled Data[J]. Chinese Journal of Electronics, 2012, 21(2): 292-298.
Citation: NI Boyi, XIAO Deyun. Optimal Nonuniform Sampling for System Identification on Sparsely Sampled Data[J]. Chinese Journal of Electronics, 2012, 21(2): 292-298.

Optimal Nonuniform Sampling for System Identification on Sparsely Sampled Data

  • Received Date: 2010-07-01
  • Rev Recd Date: 2011-08-01
  • Publish Date: 2012-04-25
  • In this paper, the problem of optimal Nonuniform sampling (NUS) is addressed for the purpose of sparsely sampled data system identification. Given a set of uniformly sampled data, its spectral information is available in the range limited by Nyquist rate, and results in alias out of the range. This cannot meet the “informative enough” condition, which is one indispensable prerequisite for system identifiability. Nevertheless, deliberate NUS pattern with certain random distributions can keep the alias-free feature of sampled signals and recover wider spectrum of the original signal, so that the identifiability is still guaranteed. In the case that no ideal alias-free signal is available, a criterion of alias suppression is founded and the optimal sampling is proposed to give an effective estimation of such systems with sparse samples. Simulation results shows the practicality and effectiveness of the proposed optimal sampling method, and how the identified model accuracy is affected by NUS.
  • loading
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (415) PDF downloads(1009) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return