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Title:Algoritem za iskanje binarnih sekvenc z nizko avtokorelacijo : diplomsko delo
Authors:ID Vuk, Miha (Author)
ID Bošković, Borko (Mentor) More about this mentor... New window
ID Brest, Janez (Comentor)
Files:.pdf VS_Vuk_Miha_2021.pdf (1,04 MB)
MD5: 4B7E87BBDBB9917495B18D50CF83290D
PID: 20.500.12556/dkum/5f75094e-82d1-4586-a341-62d1d01fbfaf
 
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 predstavljamo algoritem za iskanje binarnih sekvenc z nizko avtokorelacijo. S tem algoritmom najdemo binarne sekvence najnižjih dokumentiranih avtokorelacijskih nivojev. Omenjeni algoritem se ponuja z učinkovitim delovanjem in enostavno implementacijo. Skozi diplomsko delo opišemo idejo, kakšna je strategija pristopa in zakaj, predpogoje ter delovanje. Predstavimo lastna opažanja in ugotovitve, do katerih smo prišli med razvojem in raziskovanjem ter prikažemo dobljene rezultate.
Keywords:algoritem, binarna sekvenca, avtokorelacija
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[M. Vuk]
Year of publishing:2021
Number of pages:VII, 46 str
PID:20.500.12556/DKUM-80717 New window
UDC:004.421(043.2)
COBISS.SI-ID:86838531 New window
Publication date in DKUM:18.10.2021
Views:1062
Downloads:69
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:30.09.2021

Secondary language

Language:English
Title:Algorithm for finding low autocorrelation binary sequences
Abstract:In this thesis, we present an algorithm for finding low autocorrelation binary sequences. This algorithm is able to find sequences with the lowest documented autocorrelation levels. The mentioned algorithm promises efficiency and simple implementation. Through this thesis, we present the idea behind the design, the approach strategy and why it is used, the prerequisites, and how the algorithm functions. We present newly acquired knowledge and findings reached through the development and research with the results.
Keywords:algorithm, binary sequence, autocorrelation


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