Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise
Detection of Signals in Noise
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Detection of disturbances in voltage signals for power quality analysis using HOS
EURASIP Journal on Applied Signal Processing
Polyspectra of ordered signals
IEEE Transactions on Information Theory
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This paper discusses and presents a different perspective for classifying single and multiple disturbances in electric signals, such as voltage and current ones. Basically, the principle of divide to conquer is applied to decompose the electric signals into what we call primitive signals or components from which primitive patterns can be independently recognized. A technique based on such concept is introduced to demonstrate the effectiveness of such idea. This technique decomposes the electric signals into three main primitive components. In each primitive component, few high-order-statistics-(HOS-) based features are extracted. Then, Bayes' theory-based techniques are applied to verify the ocurrence or not of single or multiple disturbances in the electric signals. The performance analysis carried out on a large number of data indicates that the proposed technique outperforms the performance attained by the technique introduced by He and Starzyk. Additionally, the numerical results verify that the proposed technique is capable of offering interesting results when it is applied to classify several sets of disturbances if one cycle of the main frequency is considered, at least.