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State estimation with missing data and bounded uncertainty
Pavelková, Lenka
2011 - English
The paper deals with two problems in the state estimation: (i) bounded uncertainty and (ii) missing measurement data. An algorithm for the state estimation of the discrete-time state space model whose uncertainties are bounded is proposed here. The algorithm also copes with situations when some data for identification are missing. The Bayesian approach is used and maximum a posteriori probability estimates are evaluated in the discrete time instants. The proposed estimation algorithm is applied to the estimation of vehicle position when incomplete data from global positioning system together with complete data from the inertial measurement unit are at disposal.
Keywords:
state-space model; filtering; bounded noise; incomplete data
Fulltext is available at external website.
State estimation with missing data and bounded uncertainty
The paper deals with two problems in the state estimation: (i) bounded uncertainty and (ii) missing measurement data. An algorithm for the state estimation of the discrete-time state space model whose ...
Mathematical model of a production line checkpoint
Slimáček, Václav
2011 - English
Research report deals with a model of a checkpoint of a assembly line based on Markov and semi-Markov chains with decision processes. The model is motivated by a real situation.
Keywords:
Markov chain; Semi-Markov chain; Decision processes
Fulltext is available at external website.
Mathematical model of a production line checkpoint
Research report deals with a model of a checkpoint of a assembly line based on Markov and semi-Markov chains with decision processes. The model is motivated by a real situation.
Construction of Mass Migration Process
Fajfrová, Lucie; Saada, E.
2011 - English
A general model of conservative particle systems on $/Zd$ is treated in this report. We call it the Mass Migration Process. We bring out a construction of an appropriate Markov process, we set conditions on existence, attractiveness and we present many particular examples.
Keywords:
mass migration process; generalized zero range process; misanthrope process; construction
Available in digital repository of the ASCR
Construction of Mass Migration Process
A general model of conservative particle systems on $/Zd$ is treated in this report. We call it the Mass Migration Process. We bring out a construction of an appropriate Markov process, we set ...
MIMO techniques for xDSL
Mazanec, Tomáš
2011 - English
The research report presents particular achievements and conclusions accomplished within my doctoral thesis "MIMO Techniques for xDSL".
Keywords:
digital subscriber lines; space-time coding; MIMO techniques
Fulltext is available at external website.
MIMO techniques for xDSL
The research report presents particular achievements and conclusions accomplished within my doctoral thesis "MIMO Techniques for xDSL".
Mathematical model of a production line checkpoint-simulation program
Slimáček, Václav
2011 - English
The report is a continuation of research report UTIA No.2300 and contains the program in Matlab for simulatons of the mathematical model of a production line check point described in report No.2300
Keywords:
simulation program; Matlab
Fulltext is available at external website.
Mathematical model of a production line checkpoint-simulation program
The report is a continuation of research report UTIA No.2300 and contains the program in Matlab for simulatons of the mathematical model of a production line check point described in report No.2300
Goodness-of-fit test for the AFT model based on martingale residuals
Novák, Petr
2011 - English
The Accelerated Failure Time model presents a way how to easily describe survival data with regression on covariates. It is assumed that each observed unit ages internally faster or slower, depending on the covariate values. To use the model properly, we want to check if observed data fit the model assumptions. In the present work we introduce a goodness-of-fit statistics based on modern martingale theory. On simulated data we try to estimate empirical properties of the test for various situations.
Keywords:
accelerated failure time model; martingale residuals; goodness-of-fit test
Fulltext is available at external website.
Goodness-of-fit test for the AFT model based on martingale residuals
The Accelerated Failure Time model presents a way how to easily describe survival data with regression on covariates. It is assumed that each observed unit ages internally faster or slower, depending ...
Experimental Comparison of Sparse Signal Recovery Algorithms
Hoskovec, J.; Tichavský, Petr
2011 - English
This report presents an experimental comparison of some of the newest and/or most common algorithms that are used for solving the sparse recovery problem: matching pursuit, orthogonal matching pursuit (OMP), A*OMP, basis pursuit, re-weighted least square (also known as FOCUSS), re-weighted L1 optimization (RL1). The comparison is done on synthetic (random) data set (dictionary) of the size 50x250 and 500x2500.
Keywords:
compressed sensing; sparse signal; matching pursuit
Fulltext is available at external website.
Experimental Comparison of Sparse Signal Recovery Algorithms
This report presents an experimental comparison of some of the newest and/or most common algorithms that are used for solving the sparse recovery problem: matching pursuit, orthogonal matching ...
Fiscal developments and financial stress: a threshold VAR analysis
Baxa, Jaromír; Afonso, Antonio; Slavík, M.
2011 - English
We use a threshold VAR analysis to study whether the effects of fiscal policy on economic activity differ depending on financial market conditions. In particular, we investigate the possibility of a non-linear propagation of fiscal developments according to different financial market stress regimes. More specifically we employ a quarterly dataset, for the U.S., the U.K., Germany and Italy, for the period 1980:4-2009:4, encompassing macro, fiscal and financial variables. The results show that (i) the use of a nonlinear framework with regime switches is corroborated by nonlinearity tests; (ii) the responses of economic growth to a fiscal shock are mostly positive in both financial stress regimes; (iii) financial stress has a negative effect on output growth and worsens the fiscal position; (iv) the nonlinearity in the response of output growth to a fiscal shock is mainly associated with different behaviour across regimes; (v) the size of the fiscal multipliers is higher than average in the last crisis.
Keywords:
fiscal policy; threshold VAR; financial markets
Fulltext is available at external website.
Fiscal developments and financial stress: a threshold VAR analysis
We use a threshold VAR analysis to study whether the effects of fiscal policy on economic activity differ depending on financial market conditions. In particular, we investigate the possibility of a ...
Stable distributions: On densities
Karlová, Andrea
2011 - English
William Feller stated that densitites of stable distributions are probably not known. V.M. Zolotarev spent a lot of eort on deriving aproximative formulas via series expansions and integral representations for stable densities. In this report we investigate derivation of stable densities and stable distribution function. We further investigate relation between stable distribution functions and incomplete gamma functions.
Keywords:
stable distribution; integral representation; Infinitely divisible distribution
Fulltext is available at external website.
Stable distributions: On densities
William Feller stated that densitites of stable distributions are probably not known. V.M. Zolotarev spent a lot of eort on deriving aproximative formulas via series expansions and integral ...
Fast Dependency-Aware Feature Selection in Very-High-Dimensional Pattern Recognition Problems
Somol, Petr; Grim, Jiří
2011 - English
The paper addresses the problem of making dependency-aware feature selection feasible in pattern recognition problems of very high dimensionality. The idea of individually best ranking is generalized to evaluate the contextual quality of each feature in a series of randomly generated feature subsets. Each random subset is evaluated by a criterion function of arbitrary choice (permitting functions of high complexity). Eventually, the novel dependency-aware feature rank is computed, expressing the average benefit of including a feature into feature subsets. The method is efficient and generalizes well especially in very-high-dimensional problems, where traditional context-aware feature selection methods fail due to prohibitive computational complexity or to over-fitting. The method is shown well capable of over-performing the commonly applied individual ranking which ignores important contextual information contained in data.
Keywords:
feature selection,; high dimensionality; ranking; generalization; over-fitting; stability; classification; pattern recognition; machine learning
Fulltext is available at external website.
Fast Dependency-Aware Feature Selection in Very-High-Dimensional Pattern Recognition Problems
The paper addresses the problem of making dependency-aware feature selection feasible in pattern recognition problems of very high dimensionality. The idea of individually best ranking is generalized ...
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