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Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
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Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature extraction and classification. Such ...
Long-term epileptic EEG classification via 2D mapping and textural features
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Elsevier Ltd
, 2015 , Article)
Interpretation of long-term Electroencephalography (EEG) records is a tiresome task for clinicians. This paper presents an efficient, low cost and novel approach for patient-specific classification of long-term epileptic ...
Combining Fisher locality preserving projections and passband DCT for efficient palmprint recognition
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Elsevier B.V.
, 2015 , Article)
In this paper a new graph based approach referred to as Fisher Locality Preserving Projections (FLPP) is proposed for efficient palmprint recognition. The technique employs two graphs with the first being used to characterize ...
Time-frequency features for pattern recognition using high-resolution TFDs: A tutorial review
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Elsevier Inc.
, 2015 , Article)
This paper presents a tutorial review of recent advances in the field of time-frequency (t, f) signal processing with focus on exploiting (t, f) image feature information using pattern recognition techniques for detection ...
Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
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Elsevier B.V.
, 2016 , Article)
Time-frequency (TF) based machine learning methodologies can improve the design of classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF feature extraction is performed on multi-channel ...
Principles of time-frequency feature extraction for change detection in non-stationary signals: Applications to newborn EEG abnormality detection
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Elsevier Ltd
, 2015 , Article)
This paper considers the general problem of detecting change in non-stationary signals using features observed in the time-frequency (t,f) domain, obtained using a class of quadratic time-frequency distributions (QTFDs). ...