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Application for the Dynamic Programming Demonstration
Nereča, Tomáš ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
A result of this bachelor thesis is a web application which focuses on computer programming method called dynamic programming. Principles and advantages of dynamic programming are explained on several examples. Dynamic programming algorithm is explained both theoretically and also practically by a dynamically filled up table. Dynamic programming solution is also compared with simple recursive solution in charts and table.
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Optimizer for Exam Scheduling at the FIT
Paulík, Miroslav ; Burget, Radek (referee) ; Kolář, Dušan (advisor)
This paper describes automated examination scheduling for the Faculty of Information Technology of Brno University of Technology. It specifies a list of restrictions that must by satisfied. Furthermore, this limitations are classified due to their influence on a quality of the final version of the examination schedule. There are two types of restrictions; soft and hard. The task is to find such a solution that satisfies all hard constraints and breaks the minimum of soft constraints using techniques described in this paper.
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Solution of Continuous Systems by Evolutionary Computational Techniques
Lang, Stanislav ; Šeda, Miloš (referee) ; Olehla, Miroslav (referee) ; Matoušek, Radomil (advisor)
The thesis deals the issue of solution of continuous systems by evolutionary computational techniques. Evolutionary computing techniques fall into the field of softcomputing, an advanced metaheuristics optimization that is becoming more and more a method of solving complicated optimization problems with the gradual increase in computing performance of computers. The solution of continuous systems, or the synthesis of continuous control circuits, is one of the areas where these advanced algorithms find their application. When dealing with continuous systems we will focus on regulatory issues. Evolutionary computing can then become a tool not only for optimization of controller parameters but also to design its structure. Various algorithms (genetic algorithm, differential evolution, etc.) can be used to optimize the parameters of the controller, for the design of the controller structurewe usually encounter so called grammatical evolution. However, the use of grammatical evolution is not necessary if appropriate coding is used, as suggested in the presented thesis. The thesis presents a method of designing the structure and parameters of a general linear controller using the genetic algorithm. A general linear regulator is known also as so called polynomial controller, if we encounter the polynomial theory of control. The method of encoding the description of the general linear controller into the genetic chain is crucial, it determines a set of algorithms that are usable for optimization and influence the efficiency of the calculations. Described coding, effective EVT implementation, including multi-criteria optimization, is a key benefit of this work.
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Automation of Verification Using Artificial Neural Networks
Fajčík, Martin ; Husár, Adam (referee) ; Zachariášová, Marcela (advisor)
The goal of this thesis is to analyze and to find solutions of optimization problems derived from automation of functional verification of hardware using artificial neural networks. Verification of any integrated circuit (so called Design Under Verification, DUV) using technique called coverage-driven verification and universal verification methodology (UVM) is carried out by sending stimuli inputs into DUV. The verification environment continuously monitors percentual coverage of DUV functionality given by the specification. In current context, coverage stands for measurable property of DUV, like count of verified arithemtic operations or count of executed lines of code. Based on the final coverage, it is possible to determine whether the coverage of DUV is high enough to declare DUV as verified. Otherwise, the input stimuli set needs to change in order to achieve higher coverage. Current trend is to generate this set by technique called constrained-random stimulus generation. We will practice this technique by using pseudorandom program generator (PNG). In this paper, we propose multiple solutions for following two optimization problems. First problem is ongoing modification of PNG constraints in such a way that the DUV can be verified by generated stimuli as quickly as possible. Second one is the problem of seeking the smallest set of stimuli such that this set verifies DUV. The qualities of the proposed solutions are verified on 32-bit application-specific instruction set processors (ASIPs) called Codasip uRISC and Codix Cobalt.
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Removal of JPEG compression artefacts in image data
Lopata, Jan ; Kučera, Václav (advisor) ; Šroubek, Filip (referee)
This thesis is concerned with the removal of artefacts typical for JPEG im- age compression. First, we describe the mathematical formulation of the JPEG format and the problem of artefact removal. We then formulate the problem as an optimization problem, where the minimized functional is obtained via Bayes' theorem and complex wavelets. We describe proximal operators and algorithms and apply them to the minimization of the given functional. The final algorithm is implemented in MATLAB and tested on several test problems. 1
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Application for the Dynamic Programming Demonstration
Nereča, Tomáš ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
A result of this bachelor thesis is a web application which focuses on computer programming method called dynamic programming. Principles and advantages of dynamic programming are explained on several examples. Dynamic programming algorithm is explained both theoretically and also practically by a dynamically filled up table. Dynamic programming solution is also compared with simple recursive solution in charts and table.
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Solution of Continuous Systems by Evolutionary Computational Techniques
Lang, Stanislav ; Šeda, Miloš (referee) ; Olehla, Miroslav (referee) ; Matoušek, Radomil (advisor)
The thesis deals the issue of solution of continuous systems by evolutionary computational techniques. Evolutionary computing techniques fall into the field of softcomputing, an advanced metaheuristics optimization that is becoming more and more a method of solving complicated optimization problems with the gradual increase in computing performance of computers. The solution of continuous systems, or the synthesis of continuous control circuits, is one of the areas where these advanced algorithms find their application. When dealing with continuous systems we will focus on regulatory issues. Evolutionary computing can then become a tool not only for optimization of controller parameters but also to design its structure. Various algorithms (genetic algorithm, differential evolution, etc.) can be used to optimize the parameters of the controller, for the design of the controller structurewe usually encounter so called grammatical evolution. However, the use of grammatical evolution is not necessary if appropriate coding is used, as suggested in the presented thesis. The thesis presents a method of designing the structure and parameters of a general linear controller using the genetic algorithm. A general linear regulator is known also as so called polynomial controller, if we encounter the polynomial theory of control. The method of encoding the description of the general linear controller into the genetic chain is crucial, it determines a set of algorithms that are usable for optimization and influence the efficiency of the calculations. Described coding, effective EVT implementation, including multi-criteria optimization, is a key benefit of this work.
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