Related papers: Semantic Segmentation of Solar Radio Spikes at Low…
We consider the problem of automatically detecting small-scale solar photovoltaic arrays for behind-the-meter energy resource assessment in high resolution aerial imagery. Such algorithms offer a faster and more cost-effective solution to…
The minimum and the mean bandwidth of individual narrowband spikes in two events in decimetric radio waves is determined by means of multi-resolution analysis. Spikes of a few tens of millisecond duration occur at decimetric/microwave…
Solar radio bursts are some of the brightest emissions at radio frequencies in the solar system. The emission mechanisms that generate these bursts offer a remote insight into physical processes in solar coronal plasma, while fine spectral…
Solar radio spikes are short duration and narrow bandwidth fine structures in dynamic spectra observed from GHz to tens of MHz range. Their very short duration and narrow frequency bandwidth are indicative of sub-second small-scale energy…
We analyze a dense cluster of solar radio spikes registered at ~ 4.5 -- 6 GHz by the Purple Mountain Observatory spectrometer (Nanjing, China) operating in the 4.5 -- 7.5 GHz range with the 5 ms temporal resolution. To handle with the data…
A new multichannel spectrometer, Phoenix-3, is in operation having capabilities to observe solar flare radio emissions in the 0.1 - 5 GHz range at an unprecedented spectral resolution of 61.0 kHz with high sensitivity. The present setup for…
Spiking Neural Networks (SNNs) promise efficient and dynamic spatio-temporal data processing. This paper reformulates a significant challenge in radio astronomy, Radio Frequency Interference (RFI) detection, as a time-series segmentation…
Low radio frequency solar observations using the Murchison Widefield Array have recently revealed the presence of numerous weak, short-lived and narrow-band emission features, even during moderately quiet solar conditions. These non-thermal…
Radio Frequency Interference (RFI) poses a significant challenge in radio astronomy, arising from terrestrial and celestial sources, disrupting observations conducted by radio telescopes. Addressing RFI involves intricate heuristic…
Interpreting spectropolarimetric observations of the solar atmosphere takes much longer than the acquiring the data. The most important reason for this is that the model fitting, or "inversion", used to infer physical quantities from the…
Among several heliophysical and geophysical quantities, the accurate evolution of the solar irradiance is fundamental to forecast the evolution of the neutral and ionized components of the Earth's atmosphere.We developed an artificial…
Automated classification of animal sounds is a prerequisite for large-scale monitoring of biodiversity. Convolutional Neural Networks (CNNs) are among the most promising algorithms but they are slow, often achieve poor classification in the…
The identification of siren sounds in urban soundscapes is a crucial safety aspect for smart vehicles and has been widely addressed by means of neural networks that ensure robustness to both the diversity of siren signals and the strong and…
Solar radio bursts exhibit complex fine structures that reveal intricate coronal plasma dynamics. Here, we report detection of spike-like repeating burst pairs, characterized by two short-lived (0.1-2 s), narrowband components separated by…
Radio Frequency (RF) sensing holds the potential for enabling pervasive monitoring applications. However, modern sensing algorithms imply complex operations, which clash with the energy-constrained nature of edge sensing devices. This calls…
Accurately measuring stellar ages and internal structures is challenging, but the inclusion of asteroseismic observables can substantially improve precision. However, the curse of dimensionality means this comes at a high computational cost…
Spike sorting is a valuable tool in understanding brain regions. It assigns detected spike waveforms to their origins, helping to research the mechanism of the human brain and the development of implantable brain-machine interfaces (iBMIs).…
Spiking neural networks (SNN) hold the promise of being a more biologically plausible, low-energy alternative to conventional artificial neural networks. Their time-variant nature makes them particularly suitable for processing…
Understanding electron acceleration associated with magnetic energy release at sub-second scales presents a major challenges in solar physics. Solar radio spikes observed as sub-second, narrow bandwidth bursts with…
Waveform sampling systems are used pervasively in the design of front end electronics for radiation detection. The introduction of new feature extraction algorithms (eg. neural networks) to waveform sampling has the great potential to…