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Secure robust collaborative spectrum sensing in the presence of smart attackers
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
In this paper, collaborative spectrum sensing to detect random signals corrupted by Gaussian noise in the presence of smart attackers is studied. Unlike to the most of related works, we consider a blind attacker detection ...
Subspace based network community detection using sparse linear coding
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
Information mining from networks by identifying communities is an important problem across a number of research fields including social science, biology, physics, and medicine. Most existing community detection algorithms ...
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, ...
Automated detection of anomalies in sewer closed circuit television videos using proportional data modeling
(
International Society for Trenchless Technology
, 2016 , Conference Paper)
Sewer pipeline condition information is usually collected using closed circuit television (CCTV). Moreover, in order to evaluate the condition of pipeline, data should be processed by a certified operator, which is time ...
Event-Triggered fault detection, isolation and control design of linear systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
In this paper, the problem of event-Triggered integrated fault detection, isolation and control (E-IFDIC) for discrete-Time linear systems is considered. Using a filter to represent, characterize, and specify the E-IFDIC ...
Evidence theory-based approach for epileptic seizure detection using EEG signals
(
IEEE
, 2012 , Conference Paper)
Electroencephalogram (EEG) is one of the potential physiological signals used for detecting epileptic seizure. Discriminant features, representing different brain conditions, are often extracted for diagnosis purposes. ...
Design and analysis of an adaptive compressive sensing architecture for epileptic seizure detection
(
IEEE Computer Society
, 2013 , Conference Paper)
Epileptic detection techniques rely heavily on the Electroencephalography (EEG) as a representative signal carrying valuable information pertaining to the current brain state. In this work, we investigate the stability of ...
Effective seizure detection through the fusion of single-feature enhanced-k-NN classifiers of EEG signals
(
IEEE
, 2013 , Conference Paper)
Electroencephalogram (EEG) physiological signals are widely used for detecting epileptic seizure. To reduce complexity stemming from the dimensionality problem, EEG signals are often reduced into a smaller set of discriminant ...
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 ...
Innovative ad-hoc wireless sensor networks to significantly reduce leakages in underground water infrastructures
(
IEEE
, 2010 , Conference Paper)
This paper presents an ICT solution to overcome the problem of water dispersion in water distribution networks. Leakage prevention and breaks identification in water distribution networks are fundamental for an adequate ...