Stochastic Maximum Likelihood (SML) is a popular direction of arrival (DOA) estimation technique in array signal processing. It is a parametric method that jointly estimates signal and instrument noise by maximum likelihood, achieving excellent statistical ...
In this thesis, we take a signal-processing approach to two research areas outside of the core of the signal processing research: geometry reconstruction and light propagation through non-uniform media.In the first area, we consider new sampling schemes ...
Walsh-Hadamard based orthogonal sampling of signals is studied in this paper, and an application of this technique is presented. Using orthogonal sampling, a single analog-to-digital converter (ADC) only is sufficient to perform parallel (simultaneous) rec ...
Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a ...
We measure the anisotropic clustering of the quasar sample from Data Release 16 (DR16) of the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (eBOSS). A sample of 343 708 spectroscopically confirmed quasars between redshift 0.8 ...
The present paper discusses the climatic effects of humidity and temperature on cochlear implant functioning and the quality of the electrical sound signal. MATLAB Simulink simulations were prepared, offering insights into signal behavior under such climat ...
Inspired by the human ability to localize sounds, even with only one ear, as well as to recognize objects using active echolocation, we investigate the role of sound scattering and prior knowledge in regularizing ill-posed inverse problems in acoustics. In ...
The article provides a new channel-based current function, which aims at faithfully reproducing the salient parameters of lightning currents. All the model parameters can be set in a fully analytical way, guaranteeing the possibility of changing them (acco ...
This thesis focuses on two kinds of statistical inference problems in signal processing and data science. The first problem is the estimation of a structured informative tensor from the observation of a noisy tensor in which it is buried. The structure com ...
The increasing integration of intermittent renewable generation, especially at the distribution level, necessitates advanced planning and optimisation methodologies contingent on the knowledge of the admittance matrix, capturing the topology and line param ...
