Classifying seismic signals into their corresponding types of volcanic earthquakes is among
the most important tasks for monitoring volcano activity. Such a duty must be routinely …

The automated classification of seismic volcanic signals has been faced with several
different pattern recognition approaches. Among them, hidden Markov models (HMMs) have …

Automatic pattern recognition applied to seismic signals from volcanoes may assist seismic
monitoring by reducing the workload of analysts, allowing them to focus on more …

This paper presents an automatic system based on machine learning algorithms for
recognition of seismo-volcanic signals, such as long-period events and volcano-tectonic …

Abstract Analysis of seismic data is the most important method for volcano monitoring. Such
data typically consists in digital signals acquired with an arrangement of triaxial seismic …

Discrimination between different rocket types is an important application for utilizing
infrasound in event monitoring within a range of 0-100 km. This is in contrast to traditional …

La actividad volcánica en nuestro planeta genera un gran impacto económico y social. Un
sistema automático capaz de detectar y clasificar eventos sismo-volcánicos en tiempo real …

Since the beginning of planet Earth, volcanic activity has generated a series of events of
great destructive capacity. Many populations located in areas close to volcanoes coexist …

Nowadays, with the development of sensor techniques and the growth in a number of
volcanic monitoring systems, more and more data about volcanic sensor signals are …

El monitoreo volcánico constituye una tarea imprescindible en el contexto de prevención y
gestión del riesgo; en este sentido, los observatorios vulcanológicos y sismológicos …