Fong, S., Cho, K., Mohammed, O., Fiaidhi, J. and Mohammed, S. (2016) A Time Series Pre-Processing Methodology with Statistical And Spectral Analysis for Classifying Non-Stationary Stochastic Biosignals. The Journal of Supercomputing, 72, 3887-3908.
http://dx.doi.org/10.1007/s11227-016-1635-9

has been cited by the following article:

• TITLE: Spectral Density Estimation of Continuous Time Series

  AUTHORS: Ahmed Elhassanein

  KEYWORDS: Joint Segments of Observations, Modified Periodograms, Spectral Density Matrix, Wishart Matrix

  JOURNAL NAME: Applied Mathematics, Vol.7 No.17, November 17, 2016

  ABSTRACT: This paper studies spectral density estimation of a strictly stationary r-vector valued continuous time series including missing observations. The finite Fourier transform is constructed in L-joint segments of observations. The modified periodogram is defined and smoothed to estimate the spectral density matrix. We explore the properties of the proposed estimator. Asymptotic distribution is discussed.