Practical approach to asynchronous multivariate time series anomaly detection and localization

A Abdulaal, Z Liu, T Lancewicki - Proceedings of the 27th ACM SIGKDD …, 2021 - dl.acm.org
Engineers at eBay utilize robust methods in monitoring IT system signals for anomalies.
However, the growing scale of signals, both in volumes and dimensions, overpowers …

Robust multisensor time–frequency signal processing: A tutorial review with illustrations of performance enhancement in selected application areas

B Boashash, A Aïssa-El-Bey - Digital Signal Processing, 2018 - Elsevier
This paper presents high-resolution multisensor time–frequency distributions (MTFDs) and
their applications to the analysis of multichannel non-stationary signals. The approach …

Time-frequency based phase-amplitude coupling measure for neuronal oscillations

TTK Munia, S Aviyente - Scientific reports, 2019 - nature.com
Oscillatory activity in the brain has been associated with a wide variety of cognitive
processes including decision making, feedback processing, and working memory. The high …

Time-frequency processing of nonstationary signals: Advanced TFD design to aid diagnosis with highlights from medical applications

B Boashash, G Azemi… - IEEE signal processing …, 2013 - ieeexplore.ieee.org
This article presents a methodical approach for improving quadratic time-frequency
distribution (QTFD) methods by designing adapted time-frequency (TF) kernels for diagnosis …

Inferring functional neural connectivity with phase synchronization analysis: a review of methodology

J Sun, Z Li, S Tong - Computational and mathematical methods …, 2012 - Wiley Online Library
Functional neural connectivity is drawing increasing attention in neuroscience research. To
infer functional connectivity from observed neural signals, various methods have been …

A tensor decomposition-based approach for detecting dynamic network states from EEG

AG Mahyari, DM Zoltowski, EM Bernat… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Functional connectivity (FC), defined as the statistical dependency between distinct brain
regions, has been an important tool in understanding cognitive brain processes. Most of the …

Condition assessment of I&C cables in nuclear power plants via stepped-frequency waveform reflectometry

CK Lee, GY Kwon, YJ Shin - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
A nuclear power plant (NPP) depends on instrumentation and control (I&C) systems to
ensure its safe and efficient operation. In particular, I&C cables take on the pivotal role of …

Detection of epileptic dysfunctions in EEG signals using Hilbert vibration decomposition

AY Mutlu - Biomedical Signal Processing and Control, 2018 - Elsevier
Epilepsy is a neurological brain dysfunction that is manifested by recrudescent seizures.
Due to high temporal resolution, brain activities recorded by electroencephalography (EEG) …

Recursive tensor subspace tracking for dynamic brain network analysis

A Ozdemir, EM Bernat… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Recent years have seen a rapid growth in computational methods for a better understanding
of functional connectivity brain networks constructed from neuroimaging data. Most of the …

A weighted small world network measure for assessing functional connectivity

M Bolanos, EM Bernat, B He, S Aviyente - Journal of neuroscience …, 2013 - Elsevier
There is a growing need to develop measures that can characterize complex patterns of
functional connectivity among brain regions. Graph theoretic measures have emerged as an …