Outliers detection in non-stationary time-series: Support vector machine versus principal component analysis

Authors

Keywords

Adaptation models, approximation theory, Kernel, learning (artificial intelligence), nonlinear input-output model, nonstationary time-series, outliers detection techniques, principal component analysis, principal component analysis theory, rank-1 modification, Robustness, robust orthonormal projection approximation subspace tracking, sliding window-based learning algorithm, support vector machines, support vector machine technique, time series, Training, Training data

Conference

2016 12th IEEE International Conference on Control and Automation (ICCA) 2016

DOI