Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

Estimation of large sets of stochastic signals: The case of sparse sampling

Torokhti, A., Howlett, P. and Laga, H.ORCID: 0000-0002-4758-7510 (2014) Estimation of large sets of stochastic signals: The case of sparse sampling. Sampling Theory in Signal and Image Processing, 13 (3). pp. 207-230.

Abstract

In many applications, a priori information on a large set of signals of interest can only be obtained for a few signals, p, while information on other signals is missing. At the same time, it is required to estimate each reference signal. The signal is a stochastic vector and the observations are noisy. The conceptual foundation of the proposed filter is an optimal least squares linear estimate of the incremental change to the p signal pairs, extended by a natural interpolation to an estimated value of each reference signal. The new filter is expressed in terms of the Moore-Penrose pseudo-inverse matrices and therefore is always well-defined.

Item Type: Journal Article
Publisher: Sample Publishing
Copyright: 2014 Sampling Publishing
Publishers Website: http://stsip.org/
URI: http://researchrepository.murdoch.edu.au/id/eprint/33464
Item Control Page Item Control Page