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Advanced Evolutionary Image Filtering
Saranová, Ivana ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
This work aims to use cellular automata with a transition function of conditionally matching rules designed by the evolution strategy for the removal of noises of different types and intensities from digital images. The proposed method improves the original concept of conditionally matching rules by modifying the right side of the rule, extending it from a single value to a selection of functions. Furthermore, various evolution strategy setups were explored, including usage of different noise models for evolution, training on partially damaged images, and other setups, resulting in high-quality filters for each noise model. Comparing these filters to the existing methods shows great improvement from the original approach and the ability to evolutionarily design filters that are placed among the top methods quality-wise.
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Acceleration of Particles Tracking on CBM Experiment
Roth, Michael ; Kolář, Martin (referee) ; Musil, Petr (advisor)
The focus of this work is to research various methods of particle track reconstruction in the CBM experiment, and the problem of hardware acceleration of these methods. The advantages and disadvantages of the extended methods were discussed and a reconstruction method based on cellular automata and Extended Kalman filters was selected for further study. In particular, the thesis details the development of a simulation model suitable for generating test data to facilitate the implementation of the selected tracking algorithm, which was subsequently sped up using distributed computing methods. Two different particle simulation models and a reconstruction algorithm were implemented, with the reconstruction algorithm offering up to 800 per cent speed up factor in respect to the sequential algorithm and up to four orders of magnitude lower memory complexity.
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Complexity in Cellular Automata
Hudcová, Barbora ; Mikolov, Tomáš (advisor)
In order to identify complex systems capable of modeling artificial life, we study the notion of complexity within a class of dynamical systems called cellu- lar automata. We present a novel classification of cellular automata dynamics, which helps us identify interesting behavior in large automaton spaces. We give a detailed comparison of our results to previous methods of dynamics classification. In the second part of the thesis, we study the backward dynamics of cellular au- tomata. We present a novel representation of one-dimensional cellular automata, which can be used to charcterize all their garden of eden configurations. We demonstrate the usefulness of this method on examples. 1
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Acceleration of Particles Tracking on CBM Experiment
Roth, Michael ; Kolář, Martin (referee) ; Musil, Petr (advisor)
The focus of this work is to research various methods of particle track reconstruction in the CBM experiment, and the problem of hardware acceleration of these methods. The advantages and disadvantages of the extended methods were discussed and a reconstruction method based on cellular automata and Kalman filters was selected for further study. In particular, the thesis details the development of a simulation model suitable for generating test data to facilitate future implementation of the selected tracking algorithm. Two different particle simulators have been developed and will be used in the following work to calculate the prediction step of the extended Kalman filter and to test the quality of the implemented reconstruction method.
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Using Cellular Automata for Data Encryption
Dvořák, Martin ; Trunda, Otakar (advisor) ; Mráz, František (referee)
Cellular automata are discrete systems with very simple rules but very diverse behaviour. Some cellular automata can generate high-quality pseudorandom bit sequences. This leads us to the question of whether cellular automata could be used in cryptography, as a replacement for stream ciphers for instance. We will create and compare various methods for generating long one-time-pads from short keys, where our methods will utilize cellular automata. Besides direct design of cryptographical algorithms, we will also create an evolutionary algorithm, which will try to connect our building blocks in the best possible way. The outcome of our work will be a Windows desktop application for file encryption. Powered by TCPDF (www.tcpdf.org)
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Spatial modeling of brain tissue
John, Pavel ; Neruda, Roman (advisor) ; Brom, Cyril (referee)
Neural connections in the human brain are known to be modified by experiences. Yet, little is known about the mechanism of the modification and its implications on the brain function. The aim of this thesis is to investigate what impact the spatial properties of brain tissue can have on learning and memory. In particular, we focus on the dendritic plasticity. We present a model where the tissue is represented by a two-dimensional grid and its structure is characterized by various connections between the grid cells. We provide a formal definition of the model and we prove it to be computational as strong as the Turing machine. An adaptation algorithm proposed enables the model to reflect the environmental feedback, while evolutionary algorithms are employed to search for a satisfactory architecture of the model. Implementation is provided and several experiments are driven to demonstrate the key properties of the model. Powered by TCPDF (www.tcpdf.org)
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Artificial life
Weigl, František ; Šoustek, Petr (referee) ; Dvořák, Jiří (advisor)
This bachelor thesis deals with the issue of artificial life. The first part provides a brief overview of the history of artificial life and the current division of artificial life. The second part describes some important software models of artificial life. The last part of the work contains simple experiments with a cellular automaton.
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Mobile robot path planning by means of cellular automata
Holoubek, Tomáš ; Šoustek, Petr (referee) ; Dvořák, Jiří (advisor)
This thesis deals with a path planning using cellular automata algorithms in a rectangular grid environment. Theoretical part starts with an overview of commonly used approaches for path planning and later on focuses on existing cellular automata solutions and capabilities in detail. Implemented cellular automata algorithms and the commonly used path planning algorithms are together with a map generator described in the practical part. Conclusion of this thesis contains results completed in a special application.
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Complexity in Cellular Automata
Hudcová, Barbora ; Mikolov, Tomáš (advisor) ; Kupsa, Michal (referee)
In order to identify complex systems capable of modeling artificial life, we study the notion of complexity within a class of dynamical systems called cellu- lar automata. We present a novel classification of cellular automata dynamics, which helps us identify interesting behavior in large automaton spaces. We give a detailed comparison of our results to previous methods of dynamics classification. In the second part of the thesis, we study the backward dynamics of cellular au- tomata. We present a novel representation of one-dimensional cellular automata, which can be used to charcterize all their garden of eden configurations. We demonstrate the usefulness of this method on examples. 1
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Self-Modifying Cellular Automata
Szabo, Peter ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
This work deals with cellular automata with a concept of self- modification and their comparsion against regular cellular automatons . For this task we constructed a simulator , that lets us define the logic of artificial inteligence, number generator and statistical test, which are used by the automata , on their own . Consequently two experiments are carried out that demonstrate the concept of self- modification .
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