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Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring
(
IEEE
, 2013 , Conference Paper)
Brain is the most important part in the human body controlling muscles and nerves; Electroencephalogram (EEG) signals record brain electric activities. EEG signals capture important information pertinent to different ...
A review of time-frequency matched filter design with application to seizure detection in multichannel newborn EEG
(
Elsevier Inc.
, 2014 , Article)
This paper presents a novel design of a time-frequency (t-f) matched filter as a solution to the problem of detecting a non-stationary signal in the presence of additive noise, for application to the detection of newborn ...
Time-frequency detection of slowly varying periodic signals with harmonics: Methods and performance evaluation
(2011 , Article)
We consider the problem of detecting an unknown signal from an unknown noise type. We restrict the signal type to a class of slowly varying periodic signals with harmonic components, a class which includes real signals ...
On the selection of time-frequency features for improving the detection and classification of newborn EEG seizure signals and other abnormalities
(2012 , Conference Paper)
This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by translating some relevant time features or frequency features to the joint time-frequency domain. ...
Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
(
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 ...
A Cyber-Security Methodology for a Cyber-Physical Industrial Control System Testbed
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Due to recent increase in deployment of Cyber-Physical Industrial Control Systems in different critical infrastructures, addressing cyber-security challenges of these systems is vital for assuring their reliability and ...
Flow-based intrusion detection algorithm for supervisory control and data acquisition systems: A real-time approach
(
John Wiley and Sons Inc
, 2021 , Article)
Intrusion detection in supervisory control and data acquisition (SCADA) systems is integral because of the critical roles of these systems in industries. However, available approaches in the literature lack representative ...
Time-frequency compressed spectrum sensing in cognitive radios
(
Institute of Electrical and Electronics Engineers Inc.
, 2013 , Conference Paper)
In this paper, we investigate the use of time-frequency analysis for improvement of spectrum sensing in cognitive radios and exploit compressed sensing (sampling) to reduce the extremely high sampling rate of signal in ...
High-resolution time-frequency distributions for fall detection
(
SPIE
, 2015 , Conference Paper)
In this paper, we examine the role of high-resolution time-frequency distributions (TFDs) of radar micro-Doppler signatures for fall detection. The work supports the recent and rising interest in using emerging radar ...
Nonparametric structural damage detection algorithm for ambient vibration response: Utilizing artificial neural networks and self-organizing maps
(
American Society of Civil Engineers (ASCE)
, 2016 , Article)
This study presentes a new nonparametric structural damage detection algorithm that integrates self-organizing maps with a pattern-recognition neural network to quantify and locate structural damage. In this algorithm, ...