Developing artificial learning systems that can understand and generate natural language has been one of the long-standing goals of artificial intelligence. Recent decades have witnessed an impressive progress on both of these problems, giving rise to a new family of approaches. Especially, the advances in deep learning over the past couple of years have led […]
This paper explores three groups of time–frequency distributions: the Cohen’s, affine, and reassigned classes of time–frequency representations (TFRs). This study provides detailed insight into the theory behind the selected TFRs belonging to these classes. Extensive numerical simulations were performed with examples that illustrate the behavior of the analyzed TFR classes in the joint time–frequency domain. […]
Assoc. Prof. Dr. Sc. Jonatan Lerga received an annual award from the Croatian Academy of Sciences and Arts for the highest scientific achievements in 2021 in the field of technical sciences for the work “Advanced Digital Signal Processing and Machine Learning,” containing 28 scientific papers in renowned international journals (13 of which were published in […]
Dr. Sc. Nikola Lopac successfully defended his doctoral dissertation “Detection of Gravitational-Wave Signals from Time-Frequency Distributions Using Deep Learning” at the University of Rijeka, Faculty of Engineering on the 11th of March 2022. The doctoral dissertation was defended under the supervision of Assoc. Prof. Dr. Sc. Jonatan Lerga.
Non-stationary signals are often analyzed using raw waveform data or spectrograms of those data; however, the possibility of alternative time–frequency representations being more informative than the original data or spectrograms is yet to be investigated. This paper tested whether alternative time–frequency representations could be more informative for machine learning classification of seismological data. The mentioned […]
In analyzing non-stationary noisy signals with time-varying frequency content, it’s convenient to use distribution methods in joint, time and frequency, domains. Besides different adaptive data-driven time-frequency (TF) representations, the approach with multiple orthogonal and optimally concentrated Hermite window functions is an effective solution to achieve a good trade-off between low variance and minimized stable bias […]
Traditional methods of marine navigation are undergoing a revolution brought about by the almost universal adoption of the Automatic Identification System (AIS). AIS exchanges a wealth of navigational information among vessels and between ships to shore through Very High Frequency (VHF). With AIS data integrated into the Electronic Chart Display and Information System (ECDIS), the […]
Due to the ever-increasing amount of data collected and the requirements for the rapid and reliable exchange of information across many interconnected communication devices, land-based communications networks are experiencing continuous progress and improvement of existing infrastructures. However, maritime communications are still characterized by slow communication speeds and limited communication capacity, despite a similar trend of […]