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Dynamic mode decomposition of extreme events [PDF]
Nonlinear Processes in GeophysicsMost data-driven methods, among them Dynamic Mode Decomposition (DMD), focus on analysing and reconstructing the average behaviour of a system. However, the primary interest often lies in the anomalous behaviour, known as extreme events.
M. Ann, J. Behrens, J. Sillmann
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Sound Event Detection for Human Safety and Security in Noisy Environments
IEEE Access, 2022 The objective of a sound event detector is to recognize anomalies in an audio clip and return their onset and offset. However, detecting sound events in noisy environments is a challenging task. This is due to the fact that in a real audio signal several
Michael Neri +3 more
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Annals of Geophysics, 2000 In this paper we explore the time dynamics of geoelectrical signals measured in two seismic active areas in the Mediterranean region: the Southern Apennine chain (Italy) and the Hellenic arc (Crete Island, Greece).
F. Vallianatos +3 more
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Physical Review Research, 2021 We investigate the coexisting rogue wave dynamics associated with two fundamental-frequency optical waves interacting in a quadratic nonlinear medium.
Changchang Pan +5 more
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, 2020 Among the different sources of environmental noise, Road Traffic Noise (RTN) has become the main acoustic pollutant in urban and suburban areas in recent years negatively affecting the quality of life of their citizens. In order to address this problem, the European authorities require their member states to fulfil the European Environmental Noise ...
Alias, Francesc +3 more
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An Investigation into Healthcare-Data Patterns
Future Internet, 2019 Visualising complex data facilitates a more comprehensive stage for conveying knowledge. Within the medical data domain, there is an increasing requirement for valuable and accurate information.
Aaron Boddy +5 more
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Detection of Abnormal Cardiac Response Patterns in Cardiac Tissue Using Deep Learning
Mathematics, 2022 This study reports a method for the detection of mechanical signaling anomalies in cardiac tissue through the use of deep learning and the design of two anomaly detectors.
Xavier Marimon +4 more
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24th International Conference on Sound and Vibration 2017, London CallingDynamic noise maps are computed to represent the noise levels generated by road traffic in realtime to determine the population exposure to environmental noise. To this aim, a network ofacoustic sensors can be deployed in representative street locations to capture and process rawacoustic data before estimating the equivalent noise levels (Leq) of the ...
Orga, F +6 more
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Entropic Approach to the Detection of Crucial Events
Entropy, 2019 In this paper, we establish a clear distinction between two processes yielding anomalous diffusion and 1 / f noise. The first process is called Stationary Fractional Brownian Motion (SFBM) and is characterized by the use of stationary correlation
Garland Culbreth +2 more
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Unsupervised Anomaly Detection and Localization Based on Deep Spatiotemporal Translation Network
IEEE Access, 2020 Anomaly detection is of great significance for intelligent surveillance videos. Current works typically struggle with object detection and localization problems due to crowded and complex scenes.
Thittaporn Ganokratanaa +2 more
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