Random projections and hotelling's t2 statistics for change detection in high-dimensional data streams

15Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

The method of change (or anomaly) detection in high-dimensional discrete-time processes using a multivariate Hotelling chart is presented. We use normal random projections as a method of dimensionality reduction. We indicate diagnostic properties of the Hotelling control chart applied to data projected onto a random subspace of Rn. We examine the random projection method using artificial noisy image sequences as examples.

Cite

CITATION STYLE

APA

Skubalska-Rafajłowicz, E. (2013). Random projections and hotelling’s t2 statistics for change detection in high-dimensional data streams. International Journal of Applied Mathematics and Computer Science, 23(2), 447–461. https://doi.org/10.2478/amcs-2013-0034

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free