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Převod notového zápisu do digitální formy / Optical Music RecognitionKonečný, Ondřej Unknown Date (has links)
The aim of thesis is the recognition of the symbols in musical notation. Functions are implemented searching for a template in the image.
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The use of Inverse Neural Networks in the Fast Design of Printed Lens AntennasGosal, Gurpreet Singh January 2015 (has links)
In this thesis the major objective is the implementation of the inverse neural network concept in the design of printed lens (transmitarray) antenna. As it is computationally extensive to perform full-wave simulations for entire transmitarray structure and thereafter perform optimization, the idea is to generate a design database assuming that a unit cell of the transmitarray is situated inside a 2D infinite periodic structure. This way we generate a design database of transmission coefficient by varying the unit cell parameters. Since, for the actual design, we need dimensions for each cell on the transmitarray aperture and to do this we need to invert the design database.
The major contribution of this thesis is the proposal and the implementation of database inversion methodology namely inverse neural network modelling. We provide the algorithms for carrying out the inversion process as well as provide check results to demonstrate the reliability of the proposed methodology. Finally, we apply this approach to design a transmitarray antenna, and measure its performance.
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Detekce logopedických vad v řeči / Detection of Logopaedic Defects in SpeechPešek, Milan January 2009 (has links)
The thesis deals with a design and an implementation of software for a detection of logopaedia defects of speech. Due to the need of early logopaedia defects detecting, this software is aimed at a child’s age speaker. The introductory part describes the theory of speech realization, simulation of speech realization for numerical processing, phonetics, logopaedia and basic logopaedia defects of speech. There are also described used methods for feature extraction, for segmentation of words to speech sounds and for features classification into either correct or incorrect pronunciation class. In the next part of the thesis there are results of testing of selected methods presented. For logopaedia speech defects recognition algorithms are used in order to extract the features MFCC and PLP. The segmentation of words to speech sounds is performed on the base of Differential Function method. The extracted features of a sound are classified into either a correct or an incorrect pronunciation class with one of tested methods of pattern recognition. To classify the features, the k-NN, SVN, ANN, and GMM methods are tested.
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