doctoral thesis
Method for classification of fetal phonocardiography signals using empirical mode decomposition and psychoacoustic parameters
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:532472

Vican, Ivan
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Electroacoustics

Institutional repository: FER Repository

Cite this document

Vican, I. (2022). Method for classification of fetal phonocardiography signals using empirical mode decomposition and psychoacoustic parameters (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:532472

Vican, Ivan. "Method for classification of fetal phonocardiography signals using empirical mode decomposition and psychoacoustic parameters." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:532472

Vican, Ivan. "Method for classification of fetal phonocardiography signals using empirical mode decomposition and psychoacoustic parameters." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:532472

Vican, I. (2022). 'Method for classification of fetal phonocardiography signals using empirical mode decomposition and psychoacoustic parameters', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:532472

Vican I. Method for classification of fetal phonocardiography signals using empirical mode decomposition and psychoacoustic parameters [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 December 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:532472

I. Vican, "Method for classification of fetal phonocardiography signals using empirical mode decomposition and psychoacoustic parameters", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:532472