Práce se zabývá implementací simulátoru superskalárního procesoru. Implementace se odvíjí od existujících simulátorů a jejich chybějících částí. Simulátor umí vykonávat instrukční sadu RISC-V, ovšem je umožněno přidání jakékoli RISC instrukční sady. Simulátor má deterministickou predikci skoku. Části procesoru lze upravovat. Součástí je i editor kódu pro danou instrukční sadu.

In this master’s thesis are discussed static properties of network traffic trace. There are also addressed the possibility of a predication with a focus on neural networks. Specifically, therefore recurrent neural networks. Training data were downloaded from freely accessible on the internet link. This is the captured packej of traffic of LAN network in 2001. They are not the most actual, but it is possible to use them to achieve the objective results of the work. Input data needed to be processed into acceptable form. In the Visual Studio 2005 was created program to aggregate the intensities of these data. The best combining appeared after 100 ms. This was achieved by the input vector, which was divided according to the needs of network training and testing part. The various types of networks operate with the same input data, thereby to make more objective results. In practical terms, it was necessary to verify the two principles. Principle of training and the principle of generalization. The first of the nominated designs require stoking training and verification training by using gradient and mean square error. The second one represents unknown designs application on neural network. It was monitored the response of network to these input data. It can be said that the best model seemed the Layer recurrent neural network (LRN). So, it was a solution developed in this direction, followed by searching the appropriate option of recurrent network and optimal configuration. Found a variant of topology is 10-10-1. It was used the Matlab 7.6, with an extension of Neural Network toolbox 6. The results are processed in the form of graphs and the final appreciation. All successful models and network topologies are on the enclosed CD. However, Neural Network toolbox reported some problems when importing networks. In creating this work wasn’t import of network functions practically used. The network can be imported, but the majority appear to be non-trannin. Unsuccessful models of networks are not presented in this master’s thesis, because it would be make a deterioration of clarity and orientation.

This thesis deals with delay prediction issue between nodes on the Internet. Accurate delay prediction helps with choosing of the nearest internet neighbor and contributes to effective usage of network sources. Unnecessary network load is decreased due to algorithms of delay prediction (no need for many latency measuring). The thesis focuses theoretically on the three main algorithms using coordinate systems - GNP, Vivaldi, Lighthouses. Last one is at the same time the main subject of the thesis too. Algorithm Lighthouses is explored in detail theoretically and in practise too. In order to verify the accurate of delay prediction of Lighthouses algorithm the simulation application was developed. The application is able to compute node coordinates of synthetic network using Lighthouses algorithm. Description of simulation application and evaluation of simalution results are part of practice part of this thesis.

This paper deals with simulation models of the human operator controlling lateral position of simulated vehicle. I am comparing parameters and quality of the McRuer human driver model and the PID controller. Simulated system is single-track vehicle model. Simulated driver is tasked to pass a Moose test with this vehicle model. I am using the simulated annealing method to find optimal parameters of the driver model and then I visualize realized test in 2D and 3D visualization. In the end of this paper I compare simulations of the driver models and assess achieved results.

Thesis deals with multimedia signal comparison of compression options focused on video and advanced codecs. Specifically it describes the encoding and decoding of video recordings according to the MPEG standard. The theoretical part of the thesis describes characteristic properties of the video signal and justification for the need to use recording and transmission compression. There are also described methods for elimination of encoded video signal redundancy and irrelevance. Further on are discussed ways of measuring the video signal quality. A separate chapter is focused on the characteristics of currently used and promising codecs. In the practical part of the thesis were created functions in Matlab environment. These functions were implemented into graphic user interface that simulates the activity of functional blocks of the encoder and decoder. Based on user-specified input parameters it performs encoding and decoding of any given picture, composed of images in RGB format, and displays the outputs of individual functional blocks. There are implemented algorithms for the initial processing of the input sequence including sub-sampling, as well as DCT, quantization, motion compensation and their inverse operations. Separate chapters are dedicated to the realisation of codec description in the Matlab environment and to the individual processing steps output. Further on are mentioned compress algorithm comparisons and the impact of parameter change onto the final signal. The findings are summarized in conclusion.

This thesis deals with issues of smart houses and smart buildings. In the first part there is a research of possible systems installed in smart house. Each system is described from the perspective of its function and importance .The second part is focused on energy demands and where there is described European standard EN 15232 (Energy demand of building – influence of control automation and house management). In the practical part there was created scheme with devices which can be equipped smart houses with and their separation according to their relation to electricity. Each device is characterized by its electrical and nonelectrical parameters typical for family houses. Next part is about the proposal of prediction model of electricity consumption and generation. There are also stated quantities needed for prediction model and then method for prediction model realization.

Main goal of this thesis is to create forex automated trading system with possibility to add trading strategies as modules and implementation of trading strategy module based on neural networks. Created trading system is composed of client part for MetaTrader 4 trading platform and server GUI application. Trading strategy modules are implemented as dynamic libraries. Proposed trading strategy uses multilayer neural networks for prediction of direction of 45 minute moving average of close prices in one hour time horizon. Neural networks were able to find relationship between inputs and output and predict drop or growth with success rate higher than 50%. In live demo trading, strategy displayed itself as profitable for currency pair EUR/USD, but it was losing for currency pair GBP/USD. In tests with historical data from year 2014, strategy was profitable for currency pair EUR/USD in case of trading in direction of long-term trend. In case of trading against direction of trend for pair EUR/USD and in case of trading in direction and against direction of trend for pair GBP/USD, strategy was losing.

This diploma thesis deals with the utilization of artificial intelligence methods for prediction at capital markets and includes project of utilization of the chosen parts of chaos theory and artificial neural networks for prediction at capital markets.

The master's thesis is focused on evaluation of development project for the purpose of recommendation, how the company should continue with the project in the future. The analysis of the commercial real estate market and evaluation of up-to-date financial results are included. In the practical part, alternatives of selling the project and the prediction of future progress in case of lease-continuation are compared.

The master’s thesis is focused on prediction on capital market by fundamental analysis. It's principle and methods that can be used for intrinsic stock value evaluation are described in the theoretical part. The experimental part goes in for the fundamental analysis of the company ČEZ. Evaluated intrinsic value of the stock is compared with the current price of a stock on the Czech stock exchange and the investment strategy is discussed.