prikaz prve stranice dokumenta Generiranje klasične glazbe pomoću Restricted Boltzmann machines
No public access
undergraduate thesis
Generiranje klasične glazbe pomoću Restricted Boltzmann machines
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:507641
Landeka, Ivan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Landeka, I. (2018). Generiranje klasične glazbe pomoću Restricted Boltzmann machines (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:507641

Landeka, Ivan. "Generiranje klasične glazbe pomoću Restricted Boltzmann machines." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:507641

Landeka, Ivan. "Generiranje klasične glazbe pomoću Restricted Boltzmann machines." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:507641

Landeka, I. (2018). 'Generiranje klasične glazbe pomoću Restricted Boltzmann machines', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 23 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:507641

Landeka I. Generiranje klasične glazbe pomoću Restricted Boltzmann machines [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 November 23] Available at: https://urn.nsk.hr/urn:nbn:hr:168:507641

I. Landeka, "Generiranje klasične glazbe pomoću Restricted Boltzmann machines", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:507641

Metadata
TitleGeneriranje klasične glazbe pomoću Restricted Boltzmann machines
Title (english)Generating classical music with Restricted Boltzmann machines
AuthorIvan Landeka
MentorSiniša Srbljić (mentor)
Committee memberSiniša Srbljić (predsjednik povjerenstva)
Committee memberAdrian Satja Kurdija (član povjerenstva)
Committee memberMiroslav Popović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2018-09-03, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu obrađuje se nenadzirano učenje u vidu generiranja glazbenih nizova. Na početku rada opisujemo kako je nastao interes za konektivističkim pristupom umjetnoj inteligenciji. Navode se razni modeli neuronskih mreža i gdje se koriste te kako se provodi učenje neuronskih mreža. Posebno se analizira generativni model RBM i metode Monte Carlo kojima generiramo rekonstrukciju podataka. Detaljno je objašnjen skup podataka, implementacija mreže i program za oblikovanje primjera za učenje. Proveli smo treniranje i analizirali rezultate za razne parametre mreže.
Abstract (english)
In this bachelor thesis we study unsupervised learning on generating classical music pieces. In the beginning we describe the rise of interest for connectivistic approach to artificial intelligence. Various models of neural networks are described, when we use them and how to train them. Especially, we analyze generative model RBM and Markov Chain Monte Carlo methods we use for reconstruction of the data. The dataset, implementation of the neural net and modelling the training examples are described in detail. We trained the model on various parameters and explained what the model has learned.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:507641
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Public note
Created on2019-03-13 22:13:55