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Identifier 000460745
Title Application of convolutional neural networks in inverse problems of Ocean acoustics
Alternative Title Εφαρμογή συνελικτικών νευρωνικών δικτύων σε αντίστροφα προβλήματα θαλάσσιας ακουστικής
Author Τζιράκης, Βασίλειος
Thesis advisor Ταρουδάκης, Μιχαήλ
Reviewer Χατζηπαντελής, Παναγιώτης
Μακράκης, Γεώργιος
Abstract The main goal of the thesis is to study the application of a Convolutional Neural Network for the estimation of the dispersion curves that characterize the spectrogram of an acoustic signal recorded in an ocean waveguide. Dispersion curves are input data for a class of inverse problems in underwater acoustics which are treated using the time frequency analysis of a recorded signal. To make a concise presentation of my work, the thesis starts with a brief presentation of wave theory with a special reference to modeling a broadband source. Chapter 2 is devoted to Fourier transform as it is the main tool for signal processing in my work. The spectrogram is introduced in this chapter. As the applications considered in the thesis are related to inverse problems, an introduction to the theory of inverse problems is is presented in Chapter 3. In Chapter 4, the basic features of a Convolutional Neural Network (CNN), which is the main tool used to extract the information on the dispersion curves, are presented. Finally Chapter 5 presents a test case on the application of the CNN in a simulated underwater acoustic signal, which is of the form of signals used in applications of ocean acoustic tomography or seabed classification. The conclusions of my study are presented in the final chapter.
Language English
Subject Wave theory
Κυματική θεωρία
Issue date 2023-11-24
Collection   School/Department--School of Sciences and Engineering--Department of Mathematics and Applied Mathematics--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/d/1/b/metadata-dlib-1701327555-851481-19370.tkl Bookmark and Share
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