Automatic multichannel volcano-seismic classification using machine learning and EMD
This article proposes the design of an automatic classifier using the empirical mode
decomposition (EMD) along with machine learning techniques for identifying the five most …
decomposition (EMD) along with machine learning techniques for identifying the five most …
Parallel system architecture (PSA): An efficient approach for automatic recognition of volcano-seismic events
Automatic recognition of volcano-seismic events is becoming one of the most demanded
features in the early warning area at continuous monitoring facilities. While human-driven …
features in the early warning area at continuous monitoring facilities. While human-driven …
A comparative study of dimensionality reduction algorithms applied to volcano-seismic signals
Detection and classification of the different seismic events are important tasks in
volcanological observatories. Trying to make these an automatic process is fundamental for …
volcanological observatories. Trying to make these an automatic process is fundamental for …
Advanced signal recognition methods applied to seismo-volcanic events from Planchon Peteroa Volcanic Complex: Deep Neural Network classifier
Advanced techniques in the recognition and classification of seismo-volcanic events are
transcendental when studying active volcanoes, not only for their importance as an accurate …
transcendental when studying active volcanoes, not only for their importance as an accurate …
Discriminative feature selection for automatic classification of volcano-seismic signals
Feature extraction is a critical element in automatic pattern classification. In this letter, we
propose different sets of parameters for classification of volcano-seismic signals, and the …
propose different sets of parameters for classification of volcano-seismic signals, and the …
Autoencoders as a characterization technique and aid in the classification of volcanic earthquakes
ADP Lotufo - IEEE Journal of Selected Topics in Applied …, 2023 - ieeexplore.ieee.org
Volcanic seismicity is one of the most relevant parameters for the evaluation of volcanic
activity and consequently the prognosis of eruptions. Earthquakes of volcanic origin are of …
activity and consequently the prognosis of eruptions. Earthquakes of volcanic origin are of …
A simple and effective MLP-Based seismic signal classifier using temporal and spectral envelope features with genetic Algorithm-Optimization
A Atmani, ES Akhouayri, D Agliz - Measurement, 2025 - Elsevier
Nowadays, automatic seismic signal classifiers are indispensable in digital seismic
monitoring network. These classifiers can significantly assist analysts by reducing …
monitoring network. These classifiers can significantly assist analysts by reducing …
An Efficient Gaussian Mixture Model Classifier for Outdoor Surveillance using Seismic Signals
For surveillance of high-security zones, seismic sensors have received considerable
attention in numerous civilian and military applications. Since seismic sensors are highly …
attention in numerous civilian and military applications. Since seismic sensors are highly …
Development of a diagnostic system using LPC/cepstrum analysis in machine vibration
M Chamay, S Oh, YJ Kim - Journal of Mechanical Science and Technology, 2013 - Springer
Based on the linear predictive coding (LPC) and cepstrum analysis coefficients
(LPC/Cepstrum), the implementation of LPC procedure to detect faults in engine assembly …
(LPC/Cepstrum), the implementation of LPC procedure to detect faults in engine assembly …
[PDF][PDF] Preprocessing and feature extraction for asynchronous multi-class noninvasive brain computer interface based on EEG signal
HS AlZu'bi - Masdar Institute, 2011 - academia.edu
Abstract A Brain Computer Interface (BCI) is a system which allows direct communication
between the brain and a computer. It can be used to allow paralyzed as well as healthy …
between the brain and a computer. It can be used to allow paralyzed as well as healthy …