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Title:Jedrnat zapis redkih matrik
Authors:ID Golob, Klemen (Author)
ID Žalik, Borut (Mentor) More about this mentor... New window
ID Jeromel, Aljaž (Comentor)
Files:.pdf VS_Golob_Klemen_2024.pdf (2,05 MB)
MD5: 5554725749E93474CCA67FB434FADBFD
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu opisujemo postopke in implementacijo metod stiskanja redkih matrik. Implementirali smo metode CSR (angl. Compressed Sparse Row), CSF (angl. Coordinate Storage Format), CSV (angl. Compressed Sparse Vector), MSF (angl. Modified Storage Format) in CC (angl. Coordinate Compression). Kot primere redkih matrik smo uporabili decimirane sivinske rastrske slike. Po predstavitvi elementov redke matrike z omenjenimi metodami smo dobljeno zaporedje stisnili z aritmetičnim kodiranjem in z algoritmoma Gzip ter bzip2. Eksperimenti so pokazali, da je metoda CSV najučinkovitejša izmed opisanih metod.
Keywords:stiskanje podatkov, stiskanje koordinat, metode stiskanja matrik CSR, CSF, CSV, MSF, CC.
Place of publishing:Maribor
Publisher:[K. Golob]
Year of publishing:2024
PID:20.500.12556/DKUM-89457 New window
UDC:004.627(043.2)
COBISS.SI-ID:220215299 New window
Publication date in DKUM:19.09.2024
Views:132
Downloads:53
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:11.07.2024

Secondary language

Language:English
Title:Concise representation of sparse matrices
Abstract:In this thesis, procedures and implementation of methods Compressed Sparse Row, Coordinate Storage Format, Compressed Sparse Vector, Modified Storage Format and Coordinate Compression for compressing sparse matrices are described. Decimated grayscale raster images were used as examples of such matrices. The resulting sequences were compressed with arithmetic coding, Gzip, and bzip2 algorithms after representing the sparce matrices by above methods. Experimental results have shown that CSV is the most efficient method.
Keywords:data compression, coordinate compression, matrix compression methods, Compressed Sparse Row, Coordinate Storage Format, Compressed Sparse Vector, Modified Storage Format, Coordinate Compression.


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