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Now showing items 11-20 of 25
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, ...
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 ...
Design of a high-resolution separable-kernel quadratic TFD for improving newborn health outcomes using fetal movement detection
(2012 , Conference Paper)
Prior to birth, fetus health can be monitored by the variety and scale of its movements. In addition, at birth, EEG signals are recorded from at-risk newborns. Studies have shown that both fetal movements and newborn EEGs ...
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 ...
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 ...
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 ...
On the use of time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
This paper proposes new time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals. These features are obtained by translating and combining the most relevant time-domain ...
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 ...
On the detection and estimation of correlated signal using circular antenna arrays
(
IEEE
, 2011 , Conference Paper)
This paper presents the design and analysis of smart antenna systems used for the detection and estimation of correlated radio signals encountered in multipath environments using circular antenna arrays. The MUSIC algorithm ...
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 ...