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master's thesis
Optimizacija sažimajućeg očitavanja neuronskim mrežama
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:652326
Gajdić, Leonarda
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Gajdić, L. (2020). Optimizacija sažimajućeg očitavanja neuronskim mrežama (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:652326

Gajdić, Leonarda. "Optimizacija sažimajućeg očitavanja neuronskim mrežama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:652326

Gajdić, Leonarda. "Optimizacija sažimajućeg očitavanja neuronskim mrežama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:652326

Gajdić, L. (2020). 'Optimizacija sažimajućeg očitavanja neuronskim mrežama', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:652326

Gajdić L. Optimizacija sažimajućeg očitavanja neuronskim mrežama [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 July 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:652326

L. Gajdić, "Optimizacija sažimajućeg očitavanja neuronskim mrežama", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:652326

Metadata
TitleOptimizacija sažimajućeg očitavanja neuronskim mrežama
Title (english)Optimization of Compressive Sensing Using Neural Networks
AuthorLeonarda Gajdić
MentorAna Sović Kržić (mentor)
Committee memberAna Sović Kržić (predsjednik povjerenstva)
Committee memberDamir Seršić (član povjerenstva)
Committee memberDavor Petrinović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract
Sažimajuće očitavanje vrlo uspješno rekonstruira signal iz smanjenog broja mjerenja. Rekonstrukcija se najčešće provodi uz pretpostavku rijetkosti u nekoj domeni, izvođenjem optimizacijskog postupka. Kombiniranjem sažimajućeg očitavanja i neuronskih mreža mogu se postići još bolji rezultati, koji se ne oslanjaju isključivo na svojstvo rijetkosti. Vrlo efikasne u tom smislu pokazuju se generativne suparničke mreže (eng. Generative Adversarial Networks, GAN). Generativna mreža proizvodi bolje rješenje na način da poboljšava performanse i brzinu rekonstrukcije signala. Koristeći pretpostavke korištene kod metode sažimajućeg očitavanja razvija se novi način optimizacije GAN mreža koristeći gradijentne informacije diskriminatora.
Abstract (english)
The compression sensing very successfully reconstructs the signal from the reduced number of measurements. Reconstruction is most often carried out under the assumption of rarity in some of the domain, by performing an optimization procedure. Combining compression sensing and neural networks, one can achieve even better results, which do not rely solely on the rarity property. Generative Adversarial Networks (GAN) are proving to be very effective in this regard. The generative network produces a better solution in a way that it improves the performance and speed of signal reconstruction. Using the assumptions used in the compression sensing method, a new way of optimizing GAN networks using discriminant gradient information is developed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:652326
Study programmeTitle: Electrical Engineering and Information Technology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije (magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije)
Type of resourceText
File originBorn digital
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Created on2023-01-13 12:16:44