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
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 07 September 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 September 07] 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