This paper deals with the topic of design of a navigation system for an autonomous mobile robot in a park-like environment. Precisely, designing methods for road detection using available sensoric system, designing a mathematical model for fusion of these data, and suggesting a representation of an environment suitable for planning and local navigation.

The dissertation thesis deals with the synthesis and design of active frequency filters using current (CC) and voltage (VC) conveyors, or current active elements CMI (Current Mirror and Inverter), MCMI (Multi-output CMI) and PCA (Programmable Current Amplifier). As introduction, these active elements are described as suitable for the design of the circuits working in the voltage-, current,- ,and mixed-mode, or in pure current-mode speaking about the current active elements. The new frequency filter structures presented in this thesis using the above mentioned active elements were designed by the generalized autonomous circuit method, transformation cells and signal flow-graph theory. The generalized autonomous circuit method is based on full admittance network to which generalized active elements are connected. The described admittance networks can be used for other active elements. The next method is based on the transformation cells that subsequently are used for the design of synthetic elements with higher-order imittance. Original conditions for the design of such blocks are given that lead to maximal simplicity of the final structure with minimal number of passive and active elements. For effective usage of another method utilizing signal flow-graphs, new reduced graphs of chosen active elements are given. Their usage leads to direct function blocks synthesis with required properties. The functionality and behavior of chosen circuit solutions have been verified by analyses in simulation programs. The active elements were simulated by the universal current conveyor (UCC) or universal voltage conveyors (UVC) that were designed at the FEEC, BUT in cooperation with AMI Semiconductor Design Centre Brno with the CMOS 0.35 m technology. These active elements have been also used for the realization of chosen filter structures. The experimental measurements were performed in the in the frequency range 10 KHz to 100 MHz.

The diplomma thesis is dealing with possibilities of Signal to noise ratio measurement by method, which is based on direct measurement. It is chosen the most suitable method – signal and noise separation to two different parallel signal branches, where is measured signal strength in one branch and root mean square value in the other. The thesis is consisted of a concept of detail block scheme of Signal to noise ratio meter, which was designed in terms of theoretical knowledge. Particular functional blocks were circuit-designed, the active and passive parts were chosen and their function were described. There were made simulation and displayed input and output time flows. There is designed the whole connection of engineered Signal to noise ratio meter in the last part of my thesis. The double-sided board of printed circuit is contained too. It was created simple programme for supervisor micro-processor. Thereby were constructed complete bases for realization.

This master’s thesis is focused on automating the process of differential leukocyte count in peripherial blood using image processing. It deals with the design of the processing of digital images - from scanning and image preprocessing, segmentation nucleus and cytoplasm, feature selection and classifier, including testing on a set of images that were scanned in the context of this work. This work introduces used segmentation methods and classification procedures which separate nucleus and the cytoplasm of leukocytes. A statistical analysis is performed on the basis of these structures. Following adequate statistical parameters, a set of features has been chosen. This data then go through a classification process realized by three artificial neural networks. Overall were classified 5 types of leukocytes: neutropfiles, lymphocytes, monocytes, eosinophiles and basophiles. The sensitivity and specificity of the classification made for 4 out of 5 leukocyte types (neutropfiles, lymphocytes, monocytes, eosinophiles) is higher than 90 %. Sensitivity of classiffication basophiles was evaluated at 75 % and specificity at 67 %. The total ability of classification has been tested on 111 leukocytes and was approximately 91% successful. All algorithms were created in the MATLAB program.

The aim of this work is describe common methods of biological feedback therapy that is used to treat some psychosomatic diseases. Subsequently, the description is focused on minimal brain dysfunction treatment by the help of EEG biofeedback. Properties and technical requirements for this therapy are concretized. The last part of this thesis is dedicated to the design and realization of practical software tool for EEG biofeedback therapy which is made in LabView 7.1. The M535 acquisition unit and NI USB-6221 measuring device are used for hardware solution.