24 citations · 60 across the 8 of their papers we have counts for
8 papers
Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices II: Computation and Applications
J. F. Lutzeyer, A. T. Walden
The extended Davis-Kahan theorem makes use of polynomial matrix transformations to produce bounds at least as tight as the standard Davis-Kahan theorem. The optimization problem of…
Comparing Graph Spectra of Adjacency and Laplacian Matrices
J. F. Lutzeyer, A. T. Walden
Typically, graph structures are represented by one of three different matrices: the adjacency matrix, the unnormalised and the normalised graph Laplacian matrices. The spectral (ei…
Intrinsic Analysis of the Sample Fréchet Mean and Sample Mean of Complex Wishart Matrices
L. Zhuang, A. T. Walden
We consider two types of averaging of complex covariance matrices, a sample mean (average) and the sample Fréchet mean. We analyse the performance of these quantities as estimators…
A Frequency Domain Test for Propriety of Complex-Valued Vector Time Series
Swati Chandna, Andrew T. Walden
This paper proposes a frequency domain approach to test the hypothesis that a complex-valued vector time series is proper, i.e., for testing whether the vector time series is uncor…
A Sampling Strategy for Projecting to Permutations in the Graph Matching Problem
R. J. Wolstenholme, A. T. Walden
In the context of the graph matching problem we propose a novel method for projecting a matrix , which may be a doubly stochastic matrix, to a permutation matrix We observe…
Partial Coherence Estimation via Spectral Matrix Shrinkage under Quadratic Loss
D. Schneider-Luftman, A. T. Walden
Partial coherence is an important quantity derived from spectral or precision matrices and is used in seismology, meteorology, oceanography, neuroscience and elsewhere. If the numb…
An Efficient Approach to Graphical Modelling of Time Series
R. J. Wolstenholme, A. T. Walden
A method for selecting a graphical model for -vector-valued stationary Gaussian time series was recently proposed by Matsuda and uses the Kullback-Leibler divergence measure to…
Random Matrix Derived Shrinkage of Spectral Precision Matrices
A. T. Walden, D. Schneider-Luftman
Much research has been carried out on shrinkage methods for real-valued covariance matrices. In spectral analysis of -vector-valued time series there is often a need for good sh…