an integrated process monitoring approach combining dynamic independent component analysis and local outlier factor

Multivariate Outlier Detection Using Independent Component Analysis

The recent developments by considering a rather unexpected application of the theory of Independent component analysis (ICA) found in outlier detection , data clustering and multivariate data visualization etc . Accurate identification of outliers plays an important role in statistical analysis. If classical statistical models are blindly applied to data containing outliers, the results can be ...

A process monitoring method based on noisy independent component analysis

Independent component analysis (ICA) is an effective feature extraction tool for process monitoring. However, the conventional ICA-based process monitoring methods usually adopt noise-free ICA models and thus may perform unsatisfactorily under the adverse effects of the measurement noise. In this paper, a process monitoring method using a new noisy independent component analysis, referred to as...

Modified Independent Component Analysis for Multivariate Statistical Process Monitoring

In this paper, a modified independent component analysis (ICA) and its application to process monitoring are proposed. The basic idea of this approach is to use the modified ICA to extract some dominant independent components from normal operating process data and to combine them with statistical process monitoring techniques. The proposed monitoring method is applied to fault detection and ide...

Independent Component Analysis: An Approach to Clustering

Efficiency Measurement of Clinical Units Using Integrated Independent Component Analysis-DEA Model under Fuzzy Conditions

Background and Objectives: Evaluating the performance of clinical units is critical for effective management of health settings. Certain assessment of clinical variables for performance analysis is not always possible, calling for use of uncertainty theory. This study aimed to develop and evaluate an integrated independent component analysis-fuzzy-data envelopment analysis approach to accurate ...

An independent component analysis-based disturbance separation scheme for statistical process monitoring

In this paper, an independent component analysis (ICA)-based disturbance separation scheme is proposed for statistical process monitoring. ICA is a novel statistical signal processing technique and has been widely applied in medical signal processing, audio signal processing, feature extraction and face recognition. However, there are still few applications of using ICA in process monitoring. I...