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Extraction of impedance model circuit parameters and its emulation
Semenov, Dmitrii ; Brančík, Lubomír (referee) ; Šotner, Roman (advisor)
V této bakalářské práci byly představeny dva optimalizační algoritmy v MATLABu: první je pro extrahování nul/pólů, jejích počtu a frekvence celočíselných kořenu přenosových funkcí s komplexním kmitočtem "s". Tento algoritmus byl ověřen na aktivních a pasivních filtrech typů Pásmová Propust (PP), Pásmová Zadrž (PZ) a bilineárních sekcích. Druhý algoritmus aproximuje fraktální přenosové charakteristiky s určitým (nastavitelným uživatelem) počtem nul/pólů pomocí optimalizace "roje včel". Tento algoritmus byl ověřen na vzorku bioimpedance, jako je pomerančová šťáva. Vlastní testovací deska plošného spoje (DPS) emulátoru, která je založená na vlastních Operačních Transkonduktančních Zesilovačích (OTA), které jsou vyrobené v procesu I3T25 350nm, byla vyvinuta pro emulaci charakteristik bioimpedance s parametry extrahovanými pomocí algoritmu. Výsledky emulace byly poté porovnány z hlediska přesnosti s komerčním softwarem NOVA Metrohm pro elektrochemickou analýzu.
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Aplikace evolučního algoritmu na optimalizační úlohu vibračního generátoru
Nguyen, Manh Thanh ; Kovář, Jiří (referee) ; Hadaš, Zdeněk (advisor)
This thesis will deal with the use of artificial intelligence methods for solving optimization problems with multiple variables. A theorethical part presents problems of global optimization and overview of solution methods. For practical reasons, special attention is paid to evolutionary algorithms. The subject of optimization itself is energy harvester based on a piezoelectric effect. Its nature and modeling is devoted to one chapter. A part of the thesis is the implementation of the SOMA algorithm for finding the optimal parameters of the generator for maximum performance.
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The global optimalization methods
Dudová, Aneta ; Kozumplík, Jiří (referee) ; Mézl, Martin (advisor)
This bachelor work is dedicated to advanced methods of global optimization, and especially problem traveling salesman. It focuses on the description of the problem and its various options, including graph theory, heuristic algorithms, evolutionary algorithms, in which mainly genetic algorithms and optimization by ant colonies. In conclusion, the implementation of these methods and performed testing on different data sets of algorithms that approximately solve the traveling salesman problem.
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Synthesis of electromagnetic bandgap structures
Šedý, Michal ; Kovács, Peter (referee) ; Raida, Zbyněk (advisor)
In microwave frequency band, the planar technology is mainly used to fabricate electronic circuits. Propagation of surface waves belongs to the significant problem of this technology. Surface waves can cause unwanted coupling among particular parts of the structure and can degrade its parameters. The problem can be solved using an electromagnetic band gap structure (EBG). These periodic structures are able to suppress surface waves in different frequency bands. This thesis is focused on the modeling of these structures in the program COMSOL Multiphysics.
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Bayesian Optimization of Hyperparameters Using Gaussian Processes
Arnold, Jakub ; Straka, Milan (advisor) ; Vomlelová, Marta (referee)
The goal of this thesis was to implement a practical tool for optimizing hy- perparameters of neural networks using Bayesian optimization. We show the theoretical foundations of Bayesian optimization, including the necessary math- ematical background for Gaussian Process regression, and some extensions to Bayesian optimization. In order to evaluate the performance of Bayesian op- timization, we performed multiple real-world experiments with different neural network architectures. In our comparison to a random search, Bayesian opti- mization usually obtained a higher objective function value, and achieved lower variance in repeated experiments. Furthermore, in three out of four experi- ments, the hyperparameters discovered by Bayesian optimization outperformed the manually designed ones. We also show how the underlying Gaussian Process regression can be a useful tool for visualizing the effects of each hyperparameter, as well as possible relationships between multiple hyperparameters. 1
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Aplikace evolučního algoritmu na optimalizační úlohu vibračního generátoru
Nguyen, Manh Thanh ; Kovář, Jiří (referee) ; Hadaš, Zdeněk (advisor)
This thesis will deal with the use of artificial intelligence methods for solving optimization problems with multiple variables. A theorethical part presents problems of global optimization and overview of solution methods. For practical reasons, special attention is paid to evolutionary algorithms. The subject of optimization itself is energy harvester based on a piezoelectric effect. Its nature and modeling is devoted to one chapter. A part of the thesis is the implementation of the SOMA algorithm for finding the optimal parameters of the generator for maximum performance.
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Employing GPUs in Global Optimization Problems
Hošala, Michal ; Kruliš, Martin (advisor) ; Brabec, Michal (referee)
The global optimization problem -- i.e., the problem of finding global extreme points of given function on restricted domain of values -- often appears in many real-world applications. Improving efficiency of this task can reduce the latency of the application or provide more precise result since the task is usually solved by an approximative algorithm. This thesis focuses on the practical aspects of global optimization algorithms, especially in the domain of algorithmic trading data analysis. Successful implementations of the global optimization solver already exist for CPUs, but they are quite time demanding. The main objective of this thesis is to design a GO solver that utilizes the raw computational power of the GPU devices. Despite the fact that the GPUs have significantly more computational cores than the CPUs, the parallelization of a known serial algorithm is often quite challenging due to the specific execution model and the memory architecture constraints of the existing GPU architectures. Therefore, the thesis will explore multiple approaches to the problem and present their experimental results.
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The global optimalization methods
Dudová, Aneta ; Kozumplík, Jiří (referee) ; Mézl, Martin (advisor)
This bachelor work is dedicated to advanced methods of global optimization, and especially problem traveling salesman. It focuses on the description of the problem and its various options, including graph theory, heuristic algorithms, evolutionary algorithms, in which mainly genetic algorithms and optimization by ant colonies. In conclusion, the implementation of these methods and performed testing on different data sets of algorithms that approximately solve the traveling salesman problem.
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