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Matched Filter
Dvořák, Petr ; Sysel, Petr (referee) ; Číž, Radim (advisor)
The main objective of this work is to study methods of reducing BER and suggest possible resolution of matched filter. In the first part, the methods are theoretically analyzed and subsequently their function models are sugested in the computer programme Matlab Simulink. On these models, the behaviour for different input values is simulated and on their basis, the output depending on probability of the false income on SNR for each of models is worked out. In the second part, the design of the laboratory preparation with a view to the matched filter is described. This suggestion is divided into the parts which are subsequently described and outputs from the implementation of the suggested resolution are added. Thereinafter, the implementation of the proposed resolution and the results achieved at measurement of the realized produkt are closely described. This product is to be made for educational and laboratory purposes in terms of lessons The Theory of Communication.
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Texture analysis of retinal images
Mikauš, Jakub ; Odstrčilík, Jan (referee) ; Gazárek, Jiří (advisor)
The thesis deals with the detection of the nerve fiber layer disruptions in retina scans. The introduction presents an overview of the human eye fysiology and analyses the input image data. The thesis continues with an investigation of two texture analysis methods. While the method of adapted filters does not produce very good results, the method of brightness assessment is shown to work satisfactorily. The final part of the thesis describes the implemented tool for the detection of the nerve fiber layer disruptions.
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Blood vessel segmentation in fundus images using classification methods
Šťastný, Pavel ; Štohanzlová, Petra (referee) ; Odstrčilík, Jan (advisor)
Segmentation blood vessel the local images of retinal is very important for evaluation and for diagnostics eye’s disease, especially diabetic retinopathy and glaucoma. This bachelor’s thesis is deal with segmentation blood vessel by classification methods. I used simple neural network as a classifier. First of all I taught her by delta rule and then I used matched filtering on the prepare image. At the end I compared all information with gold standard. Average va-lues from score for healthy images were sensitivity 0,7717, specificity 0,9571 and accuracy score 0,9225.
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Automated Detection of graphic elements in EEG signal
Jančová, Ivana ; Ronzhina, Marina (referee) ; Bubník, Karel (advisor)
This thesis deals with the analysis of EEG, namely detection of graphic elements. The aim of the thesis is to describe methods suitable for detection of graphic elements and implementation of the two methods in MATLAB. The first part of the thesis describes the basics rhythms, artifacts and epileptiform transients occurring in the EEG. The second part deals with the methods of detection and their mutual comparison. The discussed methods are spectral analysis, correlation analysis, wavelet transform, cluster analysis and matched filter. Other parts of the thesis describe the database PhysioBank and implementation of the correlation analysis and matched filter. In the last part is the comparison of the success of selected methods and comparison is done by calculating sensitivity and positive predictive value.
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Matched filter
Lehocký, Jiří ; Maršálek, Roman (referee) ; Šebesta, Vladimír (advisor)
This work implies the essential possibilities of spectrum sensing and their use. Main attention is paid to matched filtering as a method achieving high processing gain in a short time. The impact of main parameters on the result of the detection is shown in this work. By analysing the output of detector not only in ideal conditions, but also in real transmission system, the most realibly detectable sequences were identified. Further the possibilities of spectrum sensing by matched filter in OFDM based systems are presented.
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Demonstration of optimal receivers for the AWGN channel
Musil, Petr ; Šilhavý, Pavel (referee) ; Číž, Radim (advisor)
This thesis deals with the demonstration of bit error rate reduction techniques. In the theory section, different techniques of bit error rate reduction are presented, followed by the introduction of the communication channel and the communication system parameters. Each technique is simulated in Matlab Simulink environment using the additive white Gaussian noise channel model. The simulations are captured in waveform oscillograms of all the signal processing stages. The practical section of this thesis offers a functional laboratory solution demonstrating different ways of transmission: a direct-path signal, a path with a cross-correlation receiver and a path using matched filtering. The individual circuits are described in detail, including waveform oscillograms of the signal processing blocks for illustration. Furthermore, the practical section presents printed circuit boards designs, comprehensive documentation for production, measurement results and a sample laboratory protocol.
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Detection of optic disc in retinal fundus image
Nohel, M. ; Kolář, R.
This paper presents a comparison of several image processing methods for optic disc detection in retinal images. The detection algorithms are tested on five publicly available retinal databases (total 2140 images). Thresholding, Hough transform, and matched filtering followed by postprocessing were tested for optic disc detection. It has been shown that matched filtering followed by peak detection achieves the best success rate (98.8 %).
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Demonstration of optimal receivers for the AWGN channel
Musil, Petr ; Šilhavý, Pavel (referee) ; Číž, Radim (advisor)
This thesis deals with the demonstration of bit error rate reduction techniques. In the theory section, different techniques of bit error rate reduction are presented, followed by the introduction of the communication channel and the communication system parameters. Each technique is simulated in Matlab Simulink environment using the additive white Gaussian noise channel model. The simulations are captured in waveform oscillograms of all the signal processing stages. The practical section of this thesis offers a functional laboratory solution demonstrating different ways of transmission: a direct-path signal, a path with a cross-correlation receiver and a path using matched filtering. The individual circuits are described in detail, including waveform oscillograms of the signal processing blocks for illustration. Furthermore, the practical section presents printed circuit boards designs, comprehensive documentation for production, measurement results and a sample laboratory protocol.
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Blood vessel segmentation in fundus images using classification methods
Šťastný, Pavel ; Štohanzlová, Petra (referee) ; Odstrčilík, Jan (advisor)
Segmentation blood vessel the local images of retinal is very important for evaluation and for diagnostics eye’s disease, especially diabetic retinopathy and glaucoma. This bachelor’s thesis is deal with segmentation blood vessel by classification methods. I used simple neural network as a classifier. First of all I taught her by delta rule and then I used matched filtering on the prepare image. At the end I compared all information with gold standard. Average va-lues from score for healthy images were sensitivity 0,7717, specificity 0,9571 and accuracy score 0,9225.
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Automated Detection of graphic elements in EEG signal
Jančová, Ivana ; Ronzhina, Marina (referee) ; Bubník, Karel (advisor)
This thesis deals with the analysis of EEG, namely detection of graphic elements. The aim of the thesis is to describe methods suitable for detection of graphic elements and implementation of the two methods in MATLAB. The first part of the thesis describes the basics rhythms, artifacts and epileptiform transients occurring in the EEG. The second part deals with the methods of detection and their mutual comparison. The discussed methods are spectral analysis, correlation analysis, wavelet transform, cluster analysis and matched filter. Other parts of the thesis describe the database PhysioBank and implementation of the correlation analysis and matched filter. In the last part is the comparison of the success of selected methods and comparison is done by calculating sensitivity and positive predictive value.
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