National Repository of Grey Literature 5 records found  Search took 0.01 seconds. 
Application of distributed and stochastic algorithms in network.
Yarmolskyy, Oleksandr ; Kenyeres, Martin (referee) ; Novotný, Bohumil (advisor)
This thesis deals with the distributed and stochastic algorithms including testing their convergence in networks. The theoretical part briefly describes above mentioned algorithms, including their division, problems, advantages and disadvantages. Furthermore, two distributed algorithms and two stochastic algorithms are chosen. The practical part is done by comparing the speed of convergence on various network topologies in Matlab.
Application of distributed and stochastic algorithms in network.
Yarmolskyy, Oleksandr ; Kenyeres, Martin (referee) ; Škorpil, Vladislav (advisor)
This thesis deals with the distributed and stochastic algorithms, including testing their convergence in networks. The theoretical part briefly describes above mentioned algorithms, including their division, problems, advantages and disadvantages. Futhermore, two distributed algorithms and two stochastic algorithms are chosen. The practical part is done by comparing the speed of convergence on various network topologies in MATLAB.
Application of distributed and stochastic algorithms in network.
Yarmolskyy, Oleksandr ; Kenyeres, Martin (referee) ; Škorpil, Vladislav (advisor)
This thesis deals with the distributed and stochastic algorithms, including testing their convergence in networks. The theoretical part briefly describes above mentioned algorithms, including their division, problems, advantages and disadvantages. Futhermore, two distributed algorithms and two stochastic algorithms are chosen. The practical part is done by comparing the speed of convergence on various network topologies in MATLAB.
Application of distributed and stochastic algorithms in network.
Yarmolskyy, Oleksandr ; Kenyeres, Martin (referee) ; Novotný, Bohumil (advisor)
This thesis deals with the distributed and stochastic algorithms including testing their convergence in networks. The theoretical part briefly describes above mentioned algorithms, including their division, problems, advantages and disadvantages. Furthermore, two distributed algorithms and two stochastic algorithms are chosen. The practical part is done by comparing the speed of convergence on various network topologies in Matlab.
Application of distributed and stochastic algorithms in network.
Yarmolskyy, Oleksandr ; Kenyeres, Martin (referee) ; Novotný, Bohumil (advisor)
This thesis deals with the distributed and stochastic algorithms including testing their convergence in networks. The theoretical part briefly describes above mentioned algorithms, including their division, problems, advantages and disadvantages. Furthermore, two distributed algorithms and two stochastic algorithms are chosen. The practical part is done by comparing the speed of convergence on various network topologies in Matlab.

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