Results 21 to 30 of about 1,601,810 (338)
Sensors, 2021 The automated quantification of the behaviour of freely moving animals is increasingly needed in applied ethology. State-of-the-art approaches often require tags to identify animals, high computational power for data collection and processing, and are ...
Alexandre Dore +9 more
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Radiometric Identification of Signals by Matched Whitening Transform
Sensors, 2021 Radiometric identification is the problem of attributing a signal to a specific source. In this work, a radiometric identification algorithm is developed using the whitening transformation.
Bijan G. Mobasseri, Amro Lulu
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Underwater Target Signal Classification Using the Hybrid Routing Neural Network
Sensors, 2021 In signal analysis and processing, underwater target recognition (UTR) is one of the most important technologies. Simply and quickly identify target types using conventional methods in underwater acoustic conditions is quite a challenging task.
Xiao Cheng, Hao Zhang
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Anomalous pattern based clustering of mental tasks with subject independent learning – some preliminary results [PDF]
, 2012 In this paper we describe a new method for EEG signal classification in which the classification of one subject’s EEG signals is based on features learnt from another subject.
Amorim, Renato +2 more
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Target classification using Renyi entropy features of cyclic bispectrum
The Journal of Engineering, 2019 In this study, a target classification method is proposed based on a third-order cyclic statistics technique. The authors introduce cyclic bispectrum (CBS) to reveal the non-linear cyclic nature contained by the micro-Doppler signal, and it is observed ...
Cai Wang, Yan Li, Meiguo Gao
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Thresholding Wavelet Networks for Signal Classification [PDF]
International Journal of Wavelets, Multiresolution and Information Processing, 2003 This paper reports a new signal classification tool, a modified wavelet network called Thresholding Wavelet Networks (TWN). The network is designed for the purposes of classifying signals. The philosophy of the technique is that often the difference between signals may not lie in the spectral or temporal region where the signal strength is high ...
Pah, Nemuel Daniel, Kumar, Dinesh Kant
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IEEE Access, 2019 By classifying the heart sound signals, it can provide very favorable clinical information to the diagnosis of cardiovascular diseases. According to the characteristics of heart sound signals which are complex and difficult to classify and recognize, a ...
Jinghui Li +5 more
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Broadband angle of arrival estimation methods in a polynomial matrix decomposition framework [PDF]
, 2013 A large family of broadband angle of arrival estimation algorithms are based on the coherent signal subspace (CSS) method, whereby focussing matrices appropriately align covariance matrices across narrowband frequency bins.
Alrmah, Mohamed +4 more
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Classification of the Heart Auscultation Signals
Proceedings of the International Conference on Health Informatics, 2015 Listening to the internal body sounds (auscultation) is one of the oldest techniques in medicine to diagnose heart and lung diseases. The digital heart auscultation signals are obtained with digital electronic stethoscope and can be processed automatically to obtain some coarse indications about the heart or lung condition.
Primoz Kocuvan, Drago Torkar
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Classification of EEG Signals in Depressed Patients
Balkan Journal of Electrical and Computer Engineering, 2020 Electroencephalography (EEG) are electrical signals that occur in every activity of the brain. Investigation of normal and abnormal changes that take place in the human brain using EEG signals is a widely used method in recent years. The World Health Organization (WHO) states that one of the most important health problems in today's society is ...
Server Göksel ERALDEMİR +5 more
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