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The heterogeneous distribution of frequency support from dispersed renewable generation sources results in varying inertia within the system. The effects of disturbances exhibit non-uniform variations contingent upon the disturbance's…
In this paper, we study the problem of joint wideband spectrum sensing and direction-of-arrival (DoA) estimation in a sub-Nyquist sampling framework. Specifically, considering a scenario where a few uncorrelated narrowband signals spread…
Recent work has studied the uncertainty in predictions for A(d,p)B reactions using the distorted-wave Born approximation (DWBA), coming from the parameterization of the effective dA interactions [Lovell et al., Phys. Rev. C 95, 024611].…
We propose a feature-extraction procedure based on the statistical characterization of waveforms, applied as a fast pre-processing stage in a pattern recognition task using simple artificial neural network models. This procedure involves…
We calculate the X-ray diffraction spectrum produced by a pinned charge density wave (CDW). The signature of the presence of a CDW consists of two satellite peaks, asymmetric as a consequence of disorder. The shape and the intensity of…
Pattern discharge is a common mode in dielectric barrier discharge (DBD) and has broad application prospects in various industrial fields, such as material surface treatment, environmental monitoring, and biomedical applications. In this…
We analyse a sample of 26 active galactic nuclei with deep XMM-Newton observations, using principal component analysis (PCA) to find model independent spectra of the different variable components. In total, we identify at least 12…
Systematic errors in the database of $np$ differential cross sections below 350 MeV are studied. By applying angle-dependent normalizations with the help of the energy-dependent Nijmegen partial-wave analysis PWA93 the $\chi^2$-values of…
Brainwave signals are read through Electroencephalogram (EEG) devices. These signals are generated from an active brain based on brain activities and thoughts. The classification of brainwave signals is a challenging task due to its…
A statistical approach based on the interval analysis (IA) is proposed for the analysis of the effects, on the radiation patterns radiated by phased arrays, of random errors and tolerances in the amplitudes and phases of the array-elements…
Wideband spectrum sensing (WSS) is critical for orchestrating multitudinous wireless transmissions via spectrum sharing, but may incur excessive costs of hardware, power and computation due to the high sampling rate. In this article, a deep…
Alternating Current Optimal Power Flow (AC-OPF) aims to optimize generator power outputs by utilizing the non-linear relationships between voltage magnitudes and phase angles in a power system. However, current AC-OPF solvers struggle to…
The analysis of multiwavelength properties of propagating disturbances (PDs) using Hinode/EIS observations is presented. Quasi-periodic PDs were mostly interpreted as slow magnetoacoustic waves in early studies, but recently suggested to be…
The time-domain analysis of pulse width modulated (PWM) single-phase inverters is presented for different load circuits. It is demonstrated that this analysis can be reduced to the solution of linear simultaneous algebraic equations with…
We present a computational scheme to study spin excitations in magnetic materials from first principles. The central quantity is the transverse spin susceptibility, from which the complete excitation spectrum, including single-particle…
A set of curves or images of similar shape is an increasingly common functional data set collected in the sciences. Principal Component Analysis (PCA) is the most widely used technique to decompose variation in functional data. However, the…
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor dysfunction and abnormal neural oscillations. These symptoms can be modulated through electrical stimulation. Traditional neural activity analysis in PD has…
In this study we show that a Convolutional Neural Network (CNN) model is able to accuratelydiscriminate between 4 different phases of neurological status in a non-Electroencephalogram(EEG) dataset recorded in an experiment in which subjects…
Central pattern generators (CPGs) appear to have evolved multiple times throughout the animal kingdom, indicating that their design imparts a significant evolutionary advantage. Insight into how this design is achieved is hindered by the…
Deep Neural Networks are actively being used in the design of autonomous Cyber-Physical Systems (CPSs). The advantage of these models is their ability to handle high-dimensional state-space and learn compact surrogate representations of the…