Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLi, Yongdong.en_US
dc.description.abstractPrincipal component based algorithms have been extensively used in estimating the parameters of harmonics and the localization of radiating sources because of their rela-tively high resolution. In this thesis, we give the statistical performance analysis of the state-variable algorithm applied in frequency estimation. The analysis is achieved using the second-order Taylor series approximation of the principal singular vectors and val-ues of the data matrix. The first and second order perturbations of the singular vectors are first presented as vector-valued functions of the data, and the perturbations of the parameters related to the frequency estimator are derived via the functional relation-ship. Since the frequency estimator can be approximated by the second-order Taylor series expansion about the noise-free data, the bias and the variance expression of the frequency estimator are obtained without the assumption that the frequency estima-tor is unbiased. The derived theoretical expressions are verified via simulation results under different data matrix dimensions and different signal-to-noise ratios (SNR).en_US
dc.format.extent75 p.-
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titlePerturbation analysis of principal component based algorithm in frequency and DOA estimationen_US
dc.contributor.supervisorKot, Chichung Alexen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Engineeringen_US
item.fulltextWith Fulltext-
Appears in Collections:EEE Theses
Files in This Item:
File Description SizeFormat 
  Restricted Access
7.2 MBAdobe PDFView/Open

Page view(s) 50

Updated on Jul 23, 2024


Updated on Jul 23, 2024

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.