Performance of binary FSK data transmission systems

Matched-filter detection of binary signals is discussed in terms of the probability of bit error. The equations for the probability of error are derived for coherent phase shift keying, and coherent frequency shift keying (FSK). Suboptimum detection of FSK signals is also discussed for discriminators

Recent statistical methods for orientation data

The application of statistical methods for determining the areas of animal orientation and navigation are discussed. The method employed is limited to the two-dimensional case. Various tests for determining the validity of the statistical analysis are presented. Mathematical models are included to support the theoretical considerations and tables of data are developed to show the value of information obtained by statistical analysis

Colour local feature fusion for image matching and recognition

This thesis investigates the use of colour information for local image feature extraction. The work is motivated by the inherent limitation of the most widely used state of the art local feature techniques, caused by their disregard of colour information. Colour contains important information that improves the description of the world around us, and by disregarding it; chromatic edges may be lost and thus decrease the level of saliency and distinctiveness of the resulting grayscale image. This thesis addresses the question of whether colour can improve the distinctive and descriptive capabilities of local features, and if this leads to better performances in image feature matching and object recognition applications. To ensure that the developed local colour features are robust to general imaging conditions and capable for real-world applications, this work utilises the most prominent photometric colour invariant gradients from the literature. The research addresses several limitations of previous studies that used colour invariants, by implementing robust local colour features in the form of a Harris-Laplace interest region detection and a SIFT description which characterises the detected image region. Additionally, a comprehensive and rigorous evaluation is performed, that compares the largest number of colour invariants of any previous study. This research provides for the first time, conclusive findings on the capability of the chosen colour invariants for practical real-world computer vision tasks. The last major aspect of the research involves the proposal of a feature fusion extraction strategy, that uses grayscale intensity and colour information conjointly. Two separate fusion approaches are implemented and evaluated, one for local feature matching tasks and another approach for object recognition. Results from the fusion analysis strongly indicate, that the colour invariants contain unique and useful information that can enhance the performance of techniques that use grayscale only based features

Automatický systém docházky na bázi rozpoznávání tváře

In colleges, universities, organizations, schools, and offices, taking attendance is one of the most important tasks that must be done on a timely or daily basis. Most of the time, it is done manually, for example, by calling names, passing around sheets of papers or checking respective identification cards. These methods are time consuming and sometimes the records are lost. Hence, there is a need for a computer-based attendance management system which can assist with this process of taking attendances automatically and saving them such that the record can be accessible at any time. The main goal of this project is to create a face recognition-based attendance system that will turn the manual process of taking attendance into an automated one. This project meets the requirements for bringing modernization to the way attendance is being taken, as well as the criteria for time management. It can be implemented in classrooms, offices or anywhere an attendance system is required. Users must be registered into the face recognition attendance system. Registration involves taking a picture of each user’s face, building a model from their facial characteristics, and then saving this model into a database. The camera is tasked with taking pictures of users faces and their facial characteristics are extracted using Python OpenCV. Moreover, the face recognition process comes in when users want to take their attendances. Their facial characteristics are compared to those stored in the database and up on a successful face recognition, the system automatically register the attendance and saves it to another database. An Excel sheet showing all recorded attendances can be generated at any time.Na vysokých školách, univerzitách, organizacích, školách a úřadech je docházka jedním z nejdůležitějších úkolů, které je třeba provádět včas nebo denně. To se obvykle provádí ručně, například vyvoláváním jmen, procházením papírů nebo kontrolou příslušných identifikačních karet. Tyto metody jsou časově náročné a někdy dochází ke ztrátě záznamů. Existuje tedy potřeba počítačového systému pro správu docházky, který může tomuto procesu automatického přebírání docházky a jejího ukládání napomáhat, aby byl záznam kdykoli zpřístupněn. Hlavním cílem této práce je vytvořit docházkový systém založený na rozpoznávání obličeje, který změní manuální proces přebírání docházky na automatizovaný. Tento projekt splňuje požadavky na modernizaci docházkové metody i kritéria pro time management. Může být implementován v učebnách, kancelářích nebo kdekoli, kde je vyžadován docházkový systém. Uživatelé musí být registrováni v docházkovém systému rozpoznávání obličejů. Registrace zahrnuje pořízení snímku obličeje každého uživatele, vytvoření modelu z jeho obličejových charakteristik a následné uložení tohoto modelu do databáze. Kamera má za úkol pořizovat snímky tváří uživatelů a jejich obličejové charakteristiky jsou extrahovány pomocí Python OpenCV. Proces rozpoznávání obličeje navíc přichází na řadu, když si uživatelé chtějí vzít docházku. Jejich obličejové charakteristiky jsou porovnávány s těmi uloženými v databázi a po úspěšném rozpoznání obličeje systém automaticky zaregistruje docházku a uloží ji do jiné databáze. List Excel zobrazující veškerou zaznamenanou docházku lze vygenerovat kdykoli.440 - Katedra telekomunikační technikydobř

Design studies of model reference adaptive control and identification systems

This thesis sets out to compare five well known design rules for the design of model reference adaptive systems. These are the M.I.T. rule, the Liapunov synthesis, the gradient rules of Dressier and Price, and the Monopoli design rule. A systematic performance comparison is made using two low order gain adjustment systems simulated on a digital computer. Step, sinusoidal and stochastic input signals are used and the system state variables and performance criteria are all expressed as dimensionless quantities. The results clearly demonstrate the superior performance of the Liapunov and Monopoli designs. The main disadvantage of other designs is that the dimensionless performance criteria is not a monotonic decreasing function of the dimensionless gain parameter. An analysis of the noisy case is then performed and this further points out the flexibility of the Liapunov synthesis. The next objective of the research is to extend the scope of application of the Liapunov designs. First a modification of the usual design algorithm for multivariable systems is made sc that a wider class of plants, in which the adjustable parameters may appear simultaneously in two or more elements of the plant and control matrices, can be readily treated. Examples are given to illustrate the design procedures and the typical performance of such designs. Secondly, the simultaneous parameter and state estimation system using model reference methods is investigated. Landau's hyperstability design, which can be shown to be equivalent to the Liapunov design, is preferred for this problem. To distinguish this design from the well known Generalized Equation Error (G.E.E.) design, we have called it the Stable Response Error (S.R.E.) design. The practical difficulty of using this globally stable design rule is found to be the implementation of the series (derivative) compensator. It is then shown how the problem is solved by using the state variable filters. Various simulation results substantiate the characteristics (namely unbiased estimates and very fast convergence) of the resulting design. The recovery of the simultaneous state estimates when the state variable filters are used with the S.R.E. design is then considered. With a moderate rate of convergence, the quality of the state estimates is found to be good. The main disadvantage of the S.R.E. method is that the range of parameter variations must be known a priori in order to design the series compensator which ensures the global stability. Finally, the extensions of the S.R.E. method to treat nonlinear and multivariable systems are presented. The main effort here is to find the appropriate structures of the estimation model. To conclude the thesis, a real case study is presented. This is the modelling of a nonlinear, third order internal combustion engine by a linear, first order model. The parameters of the model are adjusted according to the S.R.E. design rule. The practical results obtained demonstrate the feasibility of using the model reference method in a real physical system. Then some of the experiments are repeated with the estimation system based on the G.E.E. design rule. The results are found much inferior to those of the S.R.E. design