Neural networks have proven to be a highly effective tool for solving complex problems in
many areas of life. Recently, their importance and practical usability have further been …

The ability to detect anomaly has long been recognized as an inherent human ability, yet to
date, practical AI solutions to mimic such capability have been lacking. This lack of progress …

This study presents a comprehensive review of the automated classification in partial
discharge (PD) source identification and probabilistic interpretation of the classification …

Limitations on bandwidth and power consumption impose strict bounds on data rates of
diagnostic imaging systems. Consequently, the design of suitable (ie task-and data-aware) …

Compressed sensing (CS) MRI relies on adequate under-sampling of the k-space to
accelerate the acquisition without compromising image quality. Consequently, the design of …

Abstract The Internet of Things (IoT) is used in many fields that generate sensitive data, such
as healthcare and surveillance. The increased reliance on IoT raised serious information …

The prediction of non-equilibrium transport phenomena in disordered media is a difficult
problem for conventional numerical methods. An example of a challenging problem is the …

This work addresses the unification of some basic functions and thresholds used in non-
parametric estimation of signals by shrinkage in the wavelet domain. The soft and hard …

Solving linear inverse problems plays a crucial role in numerous applications. Algorithm
unfolding based, model-aware data-driven approaches have gained significant attention for …

PHD THESIS Complex Wavelet Transform: application to denoising Page 1 POLITEHNICA
UNIVERSITY OF TIMISOARA TELECOM BRETAGNE PHD THESIS to obtain the title of PhD of …