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Language Identification of Text Document
Cakl, Jan ; Pešán, Jan (referee) ; Szőke, Igor (advisor)
The thesis deals with a language identification of a text document. The final program includes three different implementation methods of language identification. The first method is based on a frequency statistics of N-gram. The second one represents Markov chains and the last one uses the simulated neural net for the identification purposes. The result is implemented in the Python language.
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Music Improvisation
Angelov, Michael ; Hradiš, Michal (referee) ; Fapšo, Michal (advisor)
The thesis deals with problems concerning algorithmic music compositon, especially the domain of musical improvisation. There is an opening presentation of some of existing tools and approaches that are commonly used in domain of computer music. Consenquently there is a proposal of a new system, using main principles of markov chains and prediction suffix trees (PST) with description of its implementation. The main task of developped application is to analyze an external MIDI recording that is proposed to the system by user and create a new and inovative musical material in MIDI format that would sound close to the original recording giving an impression of a computer improvised music to the listener.
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Estimation in continuous time Markov chains
Nemčovič, Bohuš ; Prokešová, Michaela (advisor) ; Kadlec, Karel (referee)
Title: Estimation in continuous time Markov chains Author: Bohuš Nemčovič Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Michaela Prokešová, Ph.D., Department of Probability and Mathematical Statistics Abstract: In this work we deal with estimating the intensity matrices of continu- ous Markov chains in the case of complete observation and observation at selected discrete time points. To obtain an estimate we use the maximum likelihood met- hod. In the second chapter we first introduce the general EM algorithm and then adjust it for finding the intensity matrix estimate based on observations at disc- rete time points. In the last chapter we will illustrate the impact of the discrete step size on the quality of intensity matrix estimate. Keywords: Markov chains, intensity matrix, maximum likelihood estimation, EM algorithm 1
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Markov chains and credit risk theory
Cvrčková, Květa ; Prokešová, Michaela (advisor) ; Lachout, Petr (referee)
Markov chains have been widely used to the credit risk measurement in the last years. Using these chains we can model movements and distribution of clients within rating grades. However, various types of markov chains could be used. The goal of the theses is to present these types together with their advan- tages and disadvantages. We focus our attention primarily on various parameter estimation methods and hypotheses testing about the parameters. The theses should help the reader with a decision, which model of a markov chain and which method of estimation should be used for him observed data. We focus our attention primarily on the following models: a discrete-time markov chain, a continuous-time markov chain (we estimate based on continuous- time observations even discrete-time observations), moreover we present an even- tuality of using semi-markov chains and semiparametric multiplicative hazard model applied on transition intensities. We illustrate the presented methods on simulation experiments and simu- lation studies in the concluding part. Keywords: credit risk, markov chain, estimates in markov chains, probability of default 1
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Estimation in continuous time Markov chains
Nemčovič, Bohuš ; Prokešová, Michaela (advisor) ; Kadlec, Karel (referee)
Title: Estimation in continuous time Markov chains Author: Bohuš Nemčovič Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Michaela Prokešová, Ph.D., Department of Probability and Mathematical Statistics Abstract: In this work we deal with estimating the intensity matrices of continu- ous Markov chains in the case of complete observation and observation at selected discrete time points. To obtain an estimate we use the maximum likelihood met- hod. In the second chapter we first introduce the general EM algorithm and then adjust it for finding the intensity matrix estimate based on observations at disc- rete time points. In the last chapter we will illustrate the impact of the discrete step size on the quality of intensity matrix estimate. Keywords: Markov chains, intensity matrix, maximum likelihood estimation, EM algorithm 1
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Markov chains and credit risk theory
Cvrčková, Květa ; Prokešová, Michaela (advisor) ; Lachout, Petr (referee)
Markov chains have been widely used to the credit risk measurement in the last years. Using these chains we can model movements and distribution of clients within rating grades. However, various types of markov chains could be used. The goal of the theses is to present these types together with their advan- tages and disadvantages. We focus our attention primarily on various parameter estimation methods and hypotheses testing about the parameters. The theses should help the reader with a decision, which model of a markov chain and which method of estimation should be used for him observed data. We focus our attention primarily on the following models: a discrete-time markov chain, a continuous-time markov chain (we estimate based on continuous- time observations even discrete-time observations), moreover we present an even- tuality of using semi-markov chains and semiparametric multiplicative hazard model applied on transition intensities. We illustrate the presented methods on simulation experiments and simu- lation studies in the concluding part. Keywords: credit risk, markov chain, estimates in markov chains, probability of default 1
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Language Identification of Text Document
Cakl, Jan ; Pešán, Jan (referee) ; Szőke, Igor (advisor)
The thesis deals with a language identification of a text document. The final program includes three different implementation methods of language identification. The first method is based on a frequency statistics of N-gram. The second one represents Markov chains and the last one uses the simulated neural net for the identification purposes. The result is implemented in the Python language.
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Music Improvisation
Angelov, Michael ; Hradiš, Michal (referee) ; Fapšo, Michal (advisor)
The thesis deals with problems concerning algorithmic music compositon, especially the domain of musical improvisation. There is an opening presentation of some of existing tools and approaches that are commonly used in domain of computer music. Consenquently there is a proposal of a new system, using main principles of markov chains and prediction suffix trees (PST) with description of its implementation. The main task of developped application is to analyze an external MIDI recording that is proposed to the system by user and create a new and inovative musical material in MIDI format that would sound close to the original recording giving an impression of a computer improvised music to the listener.
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Optimization of Algae Population Growth Using Markov Chains and
Zouharová, Martina ; Kalčevová, Jana (advisor) ; Černý, Michal (referee)
The thesis deals with the task of refining the constructional and operational parameters of a tubular photobioreactor in order to maximise the growth rate of algae contained in the cultivation suspension. It builds on a basic growth model of the Porhydrium sp. alga, and focuses on the optimization of external irradiance, which is one of the key determinants of algae growth. Two distinct methodological approaches are applied: analytic approach, which employs Markov Chains, and simulation approach, which relies on agent-based simulations. In the analytic part, we introduce the construction of state transition matrix for a Markov Chain that accounts for varying irradiance inside the photobioreactor (in contrast to constant-irradiance methods that have been published so far). In the simulation part, we devised an agent-based model of algae population that enables us to analyze the system behaviour while interactively changing the model parameters. In the context of the results from both the analytic and simulation part, we conclude by suggesting the optimal level of external irradiance.
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