|
|
Face Reader
Bučko, Peter ; Juránek, Roman (referee) ; Beran, Vítězslav (advisor)
This thesis deals with computer face recognition. Methods of Components Analysis (PCA), Linear Discriminant Analysis (LDA) and Elastic Bunch Graph Matching (EBGM) are described here. Aim of this thesis is creation of a demonstration aplication for a face recognition. Moreover I test PCA and LDA methods to find out, how accurate it can be and how can be affected by changing of parameters, such as size of a database and picture count per person.
|
|
|
Porovnání metod pro odhad omezených veličin s aplikací na ekonomická data
Musil, Karel ; Pavelková, Lenka (advisor) ; Hlávka, Zdeněk (referee)
The thesis introduces an overview of techniques for filtering of unobserved variables using a state-space representation of a model and state inequality constraints. It is mainly aimed at a derivation of the linear Kalman filter, its extension into a form of a non-linear filter and imposing state constraints. The state uniform model with noise bounds and the sequential importance sampling, as a method of particle filters using Monte Carlo simulations, are described as alternative methods. These three methods are applied on a simple semi-structural model for a monetary policy analysis. The filtration is based on Czech macroeconomic data and reflects an imposed non-negative state constraint on the interest rate. Results of the algorithms are compared and discussed.
|
|
|
Methods for Constrained State Estimation: Comparison and Application to Zero-Bound Interest Rate Problem
Musil, Karel ; Hlávka, Zdeněk (referee)
The thesis introduces an overview of techniques for filtering of unobserved variables using a state-space representation of a model and state inequality constraints. It is mainly aimed at a derivation of the linear Kalman filter and imposing state constraints. The state uniform model with noise bounds and the sequential importance sampling, as a method of particle filters using Monte Carlo simulations, are described as alternative methods. These three methods are applied on a simple semi-structural model for a monetary policy analysis. The filtration is based on Czech macroeconomic data and reflects an imposed time-varying non-negative state constraint on the nominal interest rate. Results of the algorithms are compared and discussed. Powered by TCPDF (www.tcpdf.org)
|
|
|
Porovnání metod pro odhad omezených veličin s aplikací na ekonomická data
Musil, Karel ; Pavelková, Lenka (advisor) ; Hlávka, Zdeněk (referee)
The thesis introduces an overview of techniques for filtering of unobserved variables using a state-space representation of a model and state inequality constraints. It is mainly aimed at a derivation of the linear Kalman filter, its extension into a form of a non-linear filter and imposing state constraints. The state uniform model with noise bounds and the sequential importance sampling, as a method of particle filters using Monte Carlo simulations, are described as alternative methods. These three methods are applied on a simple semi-structural model for a monetary policy analysis. The filtration is based on Czech macroeconomic data and reflects an imposed non-negative state constraint on the interest rate. Results of the algorithms are compared and discussed.
|
|
|
Methods for Constrained State Estimation: Comparison and Application to Zero-Bound Interest Rate Problem
Musil, Karel ; Hlávka, Zdeněk (referee)
The thesis introduces an overview of techniques for filtering of unobserved variables using a state-space representation of a model and state inequality constraints. It is mainly aimed at a derivation of the linear Kalman filter and imposing state constraints. The state uniform model with noise bounds and the sequential importance sampling, as a method of particle filters using Monte Carlo simulations, are described as alternative methods. These three methods are applied on a simple semi-structural model for a monetary policy analysis. The filtration is based on Czech macroeconomic data and reflects an imposed time-varying non-negative state constraint on the nominal interest rate. Results of the algorithms are compared and discussed. Powered by TCPDF (www.tcpdf.org)
|
|
|
Face Reader
Bučko, Peter ; Juránek, Roman (referee) ; Beran, Vítězslav (advisor)
This thesis deals with computer face recognition. Methods of Components Analysis (PCA), Linear Discriminant Analysis (LDA) and Elastic Bunch Graph Matching (EBGM) are described here. Aim of this thesis is creation of a demonstration aplication for a face recognition. Moreover I test PCA and LDA methods to find out, how accurate it can be and how can be affected by changing of parameters, such as size of a database and picture count per person.
|
guest ::
