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Title:Stohastičen algoritem za iskanje kratkih binarnih sekvenc z nizkimi avtokorelacijami : diplomsko delo
Authors:ID Bošak, Kristijan (Author)
ID Brest, Janez (Mentor) More about this mentor... New window
ID Bošković, Borko (Comentor)
Files:.pdf UN_Bosak_Kristijan_2021.pdf (942,64 KB)
MD5: 46BACACA6E699AA2500C1B278538C9A5
PID: 20.500.12556/dkum/7f75c831-6674-40fd-a778-b8fdd6bc442f
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V sklopu diplomskega dela raziščemo problem iskanja binarnih zaporedij z nizko avtokorelacijsko funkcijo. V glavnem delu implementiramo stohastičen algoritem LABSsolv. Algoritem pri preiskovanju velikega iskalnega prostora uporablja samoizogibajoči se sprehod in razpršeno tabelo. V eksperimentalnem delu nas zanima število ovrednotenj, ki so potrebna, da dosežemo že znane najboljše vrednosti PSL, ter čas, ki je za to potreben.
Keywords:algoritem, problem LABS, avtokorelacijska funkcija, binarne sekvence, samoizogibajoči se sprehod, razpršena tabela
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[K. Bošak]
Year of publishing:2021
Number of pages:VI, 33 str.
PID:20.500.12556/DKUM-80063 New window
UDC:004.424.4.021(043.2)
COBISS.SI-ID:96311555 New window
Publication date in DKUM:18.10.2021
Views:1006
Downloads:55
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:27.08.2021

Secondary language

Language:English
Title:Stochastic algorithm for finding short binary sequences with low autocorrelations
Abstract:As part of the thesis, we research the problem of searching for binary sequences with a low autocorrelation function. In the main part of the thesis, we implement a stochastic algorithm LABSsolv. We use the self-avoiding walk and the hash table to search through the large search space. In the experimental part of the thesis, we focus on the number of evaluations needed to reach the known optimal PSL values as well as the time necessary.
Keywords:algorithm, LABS problem, autocorrelation function, binary sequences, self-avoiding walk, hash table


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