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 R. We examine the random projection method using artificial noisy i...

In a wind tunnel process, Mach number is the most important parameter. However, it difficult to measure directly, especially in multimode operation leading difficulty process monitoring. Thus, necessary indirectly by utilizing data-driven methods, and based on which, monitor status of process. this paper, therefore, flow field system monitoring strategy proposed. Since strongly nonlinear system...

The inclusion of internal noise in model observers is a common method to allow for quantitative comparisons between human and model observer performance in visual detection tasks. In this article, we studied two different strategies for inserting internal noise into Hotelling model observers. In the first strategy, internal noise was added to the output of individual channels: (a) Independent n...

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 R. We examine the random projection method using artificial noisy i...

We propose a space–time Hotelling model that introduces a unit size of the vertical time axis in the classical Hotelling unit interval model. The proposed model allows explicit consideration of the probability that a consumer arrives at a retail store up to time t to purchase goods. The proposed model is useful in a variety of retailing problems. We briefly demonstrate an application of the pro...