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This thesis investigates a cultural logic of information. In a world saturated with information, how is representation defined, and what kinds of boundaries does it consequently set up for establishing what can be known? I argue that a cultural logic of information articulates a common cultural definition for representation: information is understood as either a “true” representation of reality, or a substitute for reality itself. As a result, information comes to be conflated with knowledge. But, in contrast to calls (scholarly and otherwise) to police the boundaries of information, I argue 1) that information is exceedingly difficult to separate, in kind, from storytelling, because 2) the provision of information almost always entails scrambles for narrative representation, which 3) are always staged in the terms of genre. The function of these conclusions is the constant undermining of this cultural logic. I examine the intersection of a variety of cultural and theoretical objects, including: Fox News and “Make America Great Again”; scientific modelling of climate change; Claude Shannon’s mathematical theory of communication; Karl Ove Knausgaard’s My Struggle; YouTube “lifestyle” communities; and the documentary “The Act of Killing.” I suggest that a methodology that accounts for the imbrication of information and storytelling better accounts for the vicissitudes of, and ideological struggles over, these cultural phenomena. It does so, in particular, by engaging with the subjective experience of information, and assessing how subjects imagine their relations to information and to networks. The purpose of this argument is to intervene in conversations about the articulation of life in control societies. / Graduate / 2021-06-20

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This semestral thesis deals with methods for continuous estimation of the quality of the ECG signal. The theoretical part includes the functional anatomy of the heart, the basics of electrocardiography, the types of noise that can be found in the ECG records, and a description of several methods for the continuous estimation of the ECG signal quality. Next here are some approaches to segmenting ECG signals based on their quality. The practical part deals with the implementation of two methods. The first method is the SNR estimation method based on the Wiener filter. The second method is the method of segmentation of ECG signals based on their quality. Both methods were tested on artificial and real signals.

V předložené práci je definována stochastická diferenciální rovnice a jsou uvedeny její základní vlastnosti. Stochastické diferenciální rovnice se používají k popisu fyzikálních jevů, které jsou ovlivněny i náhodnými vlivy. Řešením stochastického modelu je náhodný proces. Cílem analýzy náhodných procesů je konstrukce vhodného modelu, který umožní porozumět mechanismům, na jejichž základech jsou generována sledovaná data. Znalost modelu také umožňuje předvídání budoucnosti a je tak možné kontrolovat a optimalizovat činnost daného systému. V práci je nejdříve definován pravděpodobnostní prostor a Wienerův proces. Na tomto základě je definována stochastická diferenciální rovnice a jsou uvedeny její základní vlastnosti. Závěrečná část práce obsahuje příklad ilustrující použití stochastických diferenciálních rovnic v praxi.

Restoration of image data has become an essential part of the processing of medical images obtained by any system. The same applies in the case of optical coherence tomography. The aim of this work is to study the first restoration methods. Second, the description of the data representation from optical coherence tomography and subsequent discussions that restoration methods based on deconvolution would potentially find application in processing of Optical coherence tomography. Finally, the third to create a program solution of the OCT data restoration process in MATLAB environment and followed by discussion of effectiveness of the presented solutions.

The work deals with the wavelet transformation, focusing on wavelet transforms with discrete time (DTWT). The practical part is focused on the implementation of redundant packet DTWT and its use in the filtration of ECG signals. The main part of the work is to design wiener filter that uses redundant packet DTWT, designed to eliminate interference myopotentials of ECG signals. The actual solution is implemented in Matlab. Testing is performed on the library CSE using noise model myopotentials used to noising original signals. For optimum parameters designed filter is used the genetic algorithm (GA). The work is carried out comparing the proposed filter redundant packet DTWT a variant of redundant dyadic DTWT.

The aim of this work is introduction with method of filtering the ECG signals using wavelet transformation and use of this method for filtering of signal disturbed with myopotencials. The work deals with general properties and with genesis of ECG signals and describes ECG curve. Next part of work is focused on wavelet transformation, types of wavelet transformation and different methods calculation thresholds and thresholding. Design part of work is focused on design Wiener filter for remove myopotencials from ECG signals and finding optimal parameters of this filter using optimization algorithm. For optimization is used simplex method. Discovered optimal parameters are assessed on CSE and MIT-BIH Arrhythmia database and compared with results of other authors.

The thesis focuses on the use of wavelet wiener filtration to remove muscular interference from ECG signals. As part of it, a filter has been implemented in the MATLAB programming environment. The main part of the thesis deals with the optimization of numerical parameters of the proposed filter. The results of the filtration are compared with the results reported by other authors.