Article citationsMore>>

Li, H.B., Stoica, E.P. and Li, J. (1999) Computationally Efficient Maximum Likelihood Estimation of Structured Covariance Matrices. IEEE Transactions on Signal Processing, 47, 1314-1323.
https://doi.org/10.1109/78.757219

has been cited by the following article:

• TITLE: Constrained Low Rank Approximation of the Hermitian Nonnegative-Definite Matrix

  AUTHORS: Haixia Chang

  KEYWORDS: Low Rank Approximation, Hermitian Matrix, Nonnegative-Definite Matrix, Least Square

  JOURNAL NAME: Advances in Linear Algebra & Matrix Theory, Vol.10 No.2, June 29, 2020

  ABSTRACT: In this paper, we consider a constrained low rank approximation problem: , where E is a given complex matrix, p is a positive integer, and is the set of the Hermitian nonnegative-definite least squares solution to the matrix equation . We discuss the range of p and derive the corresponding explicit solution expression of the constrained low rank approximation problem by matrix decompositions. And an algorithm for the problem is proposed and the numerical example is given to show its feasibility.