Stohastičen algoritem za iskanje kratkih binarnih sekvenc z nizkimi avtokorelacijami

diplomsko delo

Kristijan Bošak (Author), Janez Brest (Mentor), Borko Bošković (Co-mentor)

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

algoritmi;problem LABS;avtokorelacijska funkcija;binarne sekvence;samoizogibajoči se sprehod;razpršene tabele;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2021
Typology:	2.11 - Undergraduate Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[K. Bošak]
UDC:	004.424.4.021(043.2)
COBISS:	96311555
Views:	225
Downloads:	17
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Stochastic algorithm for finding short binary sequences with low autocorrelations
Secondary 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.
Secondary keywords:	algorithm;LABS problem;autocorrelation function;binary sequences;self-avoiding walk;hash table;
Type (COBISS):	Bachelor thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages:	VI, 33 str.
ID:	13284623