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Protein Domains Prediction
Valenta, Martin ; Martínek, Tomáš (referee) ; Burgetová, Ivana (advisor)
The work is focused on the area of the proteins and their domains. It also briefly describes gathering methods of the protein´s structure at the various levels of the hierarchy. This is followed by examining of existing tools for protein´s domains prediction and databases consisting of domain´s information. In the next part of the work selected representatives of prediction methods are introduced. These methods work with the information about the internal structure of the molecule or the amino acid sequence. The appropriate chapter outlines applied procedure of domains´ boundaries prediction. The prediction is derived from the primary structure of the protein, using a neural network The implemented procedure and its possibility of further development in the related thesis are introduced at the conclusion of this work.
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The use of artificial intelligence in cryptography
Lavický, Vojtěch ; Rosenberg, Martin (referee) ; Babnič, Patrik (advisor)
Goal of this thesis is to get familiar with problematics of neural networks and commonly used security protocols in cryptography. Theoretical part of the thesis is about neural networks theory and chooses best suitable type of neural network to use in cryptographic model. In practical part, a new type of security protocol is created, using chosen neural network.
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Neural networks in audio signal watermarking algorithms
Kaňa, Ondřej ; Smékal, Zdeněk (referee) ; Zezula, Radek (advisor)
Digital watermarking is a technique for digital multimedia copyright protection. The robustness and the imperceptibility are the main requirements of the watermark. This thesis deals with watermarking audio signals using artificial neural networks. There is described audio watermarking method in the DCT domain. Method is based on human psychoacoustic model and the techniques of neural networks.
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Neural networks in audio signal watermarking algorithms
Kaňa, Ondřej ; Smékal, Zdeněk (referee) ; Zezula, Radek (advisor)
Digital watermarking is a technique for digital multimedia copyright protection. The robustness and the imperceptibility are the main requirements of the watermark. This thesis deals with watermarking audio signals using artificial neural networks. There is described audio watermarking method in the DCT domain. Method is based on human psychoacoustic model and the techniques of neural networks.
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Use of neural networks in classification of heart diseases
Skřížala, Martin ; Tannenberg, Milan (referee) ; Hrubeš, Jan (advisor)
This thesis discusses the design and the utilization of the artificial neural networks as ECG classifiers and the detectors of heart diseases in ECG signal especially myocardial ischaemia. The changes of ST-T complexes are the important indicator of ischaemia in ECG signal. Different types of ischaemia are expressed particularly by depression or elevation of ST segments and changes of T wave. The first part of this thesis is orientated towards the theoretical knowledges and describes changes in the ECG signal rising close to different types of ischaemia. The second part deals with to the ECG signal pre-processing for the classification by neural network, filtration, QRS detection, ST-T detection, principal component analysis. In the last part there is described design of detector of myocardial ischaemia based on artificial neural networks with utilisation of two types of neural networks back – propagation and self-organizing map and the results of used algorithms. The appendix contains detailed description of each neural networks, description of the programme for classification of ECG signals by ANN and description of functions of programme. The programme was developed in Matlab R2007b.
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