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Title:BREZIZGUBNO STISKANJE MERILNIH PODATKOV
Authors:ID Eferl, Boštjan (Author)
ID Planinšič, Peter (Mentor) More about this mentor... New window
Files:.pdf UN_Eferl_Bostjan_2016.pdf (1,51 MB)
MD5: 9A2D9D63E26854FB7832E40EB627746E
 
Language:Slovenian
Work type:Undergraduate thesis
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Delo obravnava brezizgubno kompresijo podatkov, temeljna obravnavana metoda je lastno razvita metoda, ki za komprimiranje uporablja celoštevilske ostanke pri deljenju števila n, ki predstavlja podatke z nekim številom m, ki je lahko naključno generirano. Komprimirane podatke predstavlja ostanek r, za zapis katerega je potrebno manj bitov, kot za zapis števila n. Dekomprimiranje se vrši tako, da se najde tisto število k, ki zadovolji enačbo n_domnevni =km + r na ta način, da dobljen nd prestane teste s kriteriji, ki jih pričakujemo, da jih bo izpolnjeval komprimiran tip podatkov. Števila n, nd, k, m in r so cela števila. Če stopnja kompresije ni prevelika, skoraj zagotovo obstaja samo en poizkus iz velike množice poizkusov, ki ta test prestane. Lažno pozitivnih rezultatov dekomprimiranja ni, ker se podatki po tem ko so komprimirani preizkusno dekomprimirajo, če obstaja samo en poizkus dekodiranja, ki prestane teste in so ti dekomprimirani podatki enaki izvornim, bodo tudi vsa nadaljnja dekomprimiranja pravilna, če se le uporabi enaka metoda dekomprimiranja.
Keywords:brezizgubno stiskanje, merilni podatki, Python
Place of publishing:Maribor
Publisher:[B. Eferl]
Year of publishing:2016
PID:20.500.12556/DKUM-62702 New window
UDC:004.627(043.2)
COBISS.SI-ID:19937046 New window
NUK URN:URN:SI:UM:DK:JNPQJYXA
Publication date in DKUM:15.09.2016
Views:1417
Downloads:116
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:LOSSLESS COMPRESSION OF MEASUREMENT DATA
Abstract:Work treats lossless data compression, the main method treated is the method of own development, which uses whole number reminders obtained by division of number n by some number m, which can be randomly generated. Number r represents compressed data, for whose representation less bits are needed than for the representation of the number n. Decompression is done by finding such number k which satisfies the equation n_domnevni = km + r in such a way that obtained nd passes the tests with criteria which are expected for the compressed type of data to satisfy. Numbers n, nd, k, m and r are whole numbers. If the level of compression is not to high, then almost certainly exists only one test from the large set of tests, which passes this test. There are no false positive attempts of decompression, because right after the compression the attempt of decompression is performed, if there exists only one attempt of decompression, which passes the tests and these decompressed data are the same as the source data, then all the subsequent decompressions will be correct, if the same decompression method is used.
Keywords:lossless compression, measurement data, Python


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