Number of found documents: 1452
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Influence diagrams for speed profile optimization" computational issues
Vomlel, Jiří; Kratochvíl, Václav
2015 - English
Influence diagrams were applied to diverse decision problems. However, the general theory is still not sufficiently developed if the variables are continuous or hybrid and the utility functions are nonlinear. In this paper, we study computational problems related to the application of influence diagrams to vehicle speed profile optimization and suggest an approximation of the nonlinear utility functions by piecewise linear functions. Keywords: influence diagram; speed profile; optimization Fulltext is available at external website.
Influence diagrams for speed profile optimization" computational issues

Influence diagrams were applied to diverse decision problems. However, the general theory is still not sufficiently developed if the variables are continuous or hybrid and the utility functions are ...

Vomlel, Jiří; Kratochvíl, Václav
Ústav teorie informace a automatizace, 2015

Scenario Generation via L1 Norm
Kaňková, Vlasta
2015 - English
Optimization problems depending on a probability measure correspond to many economic and financial situations. It can be very complicated to solve these problems, especially when the underlying probability measure belongs to continuous type. Consequently, the underlying continuous probability measure is often replaced by discrete one with finite number of atoms (scenario). The aim of the contribution is to deal with the above mentioned approximation in a special form of stochastic optimization problems with an operator of the mathematical expectation in the objective function. The stability results determined by the help of the Wasserstein metric (based on the L_1 norm) are employed to generate approximate distributions Keywords: One-stage stochastic programming problems; multistage stochastic problems; L_1 norm; Wasserstein metric Fulltext is available at external website.
Scenario Generation via L1 Norm

Optimization problems depending on a probability measure correspond to many economic and financial situations. It can be very complicated to solve these problems, especially when the underlying ...

Kaňková, Vlasta
Ústav teorie informace a automatizace, 2015

Information fusion with functional Bregman divergence
Dedecius, Kamil
2015 - English
The report summarizes the basics of the Bregman divergence, its functional form and potential use for information fusion. Keywords: information fusion; bregman divergence; entropy Fulltext is available at external website.
Information fusion with functional Bregman divergence

The report summarizes the basics of the Bregman divergence, its functional form and potential use for information fusion.

Dedecius, Kamil
Ústav teorie informace a automatizace, 2015

Recursive Estimation of High-Order Markov Chains: Approximation by Finite Mixtures
Kárný, Miroslav
2015 - English
A high-order Markov chain is a universal model of stochastic relations between discrete-valued variables. The exact estimation of its transition probabilities suers from the curse of dimensionality. It requires an excessive amount of informative observations as well as an extreme memory for storing the corresponding su cient statistic. The paper bypasses this problem by considering a rich subset of Markov-chain models, namely, mixtures of low dimensional Markov chains, possibly with external variables. It uses Bayesian approximate estimation suitable for a subsequent decision making under uncertainty. The proposed recursive (sequential, one-pass) estimator updates a product of Dirichlet probability densities (pds) used as an approximate posterior pd, projects the result back to this class of pds and applies an improved data-dependent stabilised forgetting, which counteracts the dangerous accumulation of approximation errors. Keywords: Markov chain; approximate parameter estimation; Bayesian recursive estimation; adaptive systems; Kullback-Leibler divergence; forgetting Available at various institutes of the ASCR
Recursive Estimation of High-Order Markov Chains: Approximation by Finite Mixtures

A high-order Markov chain is a universal model of stochastic relations between discrete-valued variables. The exact estimation of its transition probabilities suers from the curse of dimensionality. ...

Kárný, Miroslav
Ústav teorie informace a automatizace, 2015

Normal and uniform noise - violation of the assumption on noise distribution in model identification
Jirsa, Ladislav; Pavelková, Lenka
2015 - English
Mathematical modelling under uncertainty together with the field of applied statistics represent tools useful in many practical domains. Widely accepted assumption of normal (Gaussian) noise has created the basis for theoretical and algorithmic solutions of respective tasks. However, many continuous variables are strictly bounded and their uncertainty may have origin in various physical processes which causes a non-normal distribution of their noise. Furthermore, adaptation of algorithms based on normal model for identification of models with bounded noise can distort the estimates due to inconsistent handling of uncertainty. This report describes a study to compare results of estimation algorithms based on assumption of normal and uniform noise. Data sequences processed by the algorithms have normal noise bounded by a low limit with respect to standard deviation. We illustrate disparity between noise assumption and a true noise distribution and its influence on the quality of the estimates. It is a part of an effort to develop theory and fast algorithms for estimation with bounded noise, applicable in practice. Keywords: uncertainty; bounded variable; uniform noise; model identification; assumption of normal noise; estimation comparison Fulltext is available at external website.
Normal and uniform noise - violation of the assumption on noise distribution in model identification

Mathematical modelling under uncertainty together with the field of applied statistics represent tools useful in many practical domains. Widely accepted assumption of normal (Gaussian) noise has ...

Jirsa, Ladislav; Pavelková, Lenka
Ústav teorie informace a automatizace, 2015

Prediction of Pedestrian Movement During The Egress Situation
Hrabák, Pavel; Ticháček, O.
2015 - English
The report summarizes the up-to-now progress in the application of the recursive estimation on the prediction of the pedestrian movement during the egress or evacuation situation. For these purposes a simple decision-making model has been introduced taking into account only the forward and sideways movement of pedestrians. Based on this model, a test simulation has been developed in order to test the applicability of the estimation tool to the stated decision-making model. Two main approaches of the decision process incorporated in the simulation are discussed and a modified version of the original model is presented. The report contains a manual to the used Matlab scripts and functions. The codes of needed m-files are incorporated as well. Keywords: Recursive estimation; mixture of Markov chains; pedestrian movement; egress simulation Fulltext is available at external website.
Prediction of Pedestrian Movement During The Egress Situation

The report summarizes the up-to-now progress in the application of the recursive estimation on the prediction of the pedestrian movement during the egress or evacuation situation. For these purposes ...

Hrabák, Pavel; Ticháček, O.
Ústav teorie informace a automatizace, 2015

Blind Separation of Mixtures of Piecewise AR(1) Processes and Model Mismatch
Tichavský, Petr; Šembera, Ondřej; Koldovský, Zbyněk
2015 - English
Modeling real-world acoustic signals and namely speech signals as piecewise stationary random processes is a possible approach to blind separation of linear mixtures of such signals. In this paper, the piecewise AR(1) modeling is studied and is compared to the more common piecewise AR(0) modeling, which is known under the names Block Gaussian SEParation (BGSEP) and Block Gaussian Likelihood (BGL). The separation based on the AR(0) modeling uses an approximate joint diagonalization (AJD) of covariance matrices of the mixture with lag 0, computed at epochs (intervals) of stationarity of the separated signals. The separation based on the AR(1) modeling uses the covariances of lag 0 and covariances of lag 1 jointly. For this model, we derive an approximate Cram´er-Rao lower bound on the separation accuracy for estimation based on the full set of the statistics (covariance matrices of lag 0 and lag 1) and covariance matrices with lag 0 only. The bounds show the condition when AR(1) modeling leads to significantly improved separation accuracy. Keywords: Autoregressive processes; Cramer-Rao bound; Blind source separation Fulltext is available at external website.
Blind Separation of Mixtures of Piecewise AR(1) Processes and Model Mismatch

Modeling real-world acoustic signals and namely speech signals as piecewise stationary random processes is a possible approach to blind separation of linear mixtures of such signals. In this paper, ...

Tichavský, Petr; Šembera, Ondřej; Koldovský, Zbyněk
Ústav teorie informace a automatizace, 2015

On Linear Probabilistic Opinion Pooling Based on Kullback-Leibler Divergence
Sečkárová, Vladimíra
2015 - English
In this contribution we focus on the finite collection of sources, providing their opinions about a hidden (stochastic) phenomenon, that is not directly observable. The assumption on obtaining opinions yields a decision making process commonly referred to as opinion pooling. Due to the complexity of the space of possible decisions we consider the probability distributions over this set rather than single values, exploited before, e.g., in [2]. The final decision (result of pooling) is then a combination of probability distributions provided by sources. Keywords: linear opinion pooling; minimum cross-entropy principle; expected Kullback-Leibler divergence Fulltext is available at external website.
On Linear Probabilistic Opinion Pooling Based on Kullback-Leibler Divergence

In this contribution we focus on the finite collection of sources, providing their opinions about a hidden (stochastic) phenomenon, that is not directly observable. The assumption on obtaining ...

Sečkárová, Vladimíra
Ústav teorie informace a automatizace, 2015

Proceedings of the 10th Workshop on Uncertainty Processing
Kratochvíl, Václav
2015 - English
WUPES 2015 is organized jointly by the Institute of Information Theory and Automation of the Czech Academy of Sciences and by the Faculty of Management, University of Economics, Prague. It is quite natural that such a meeting could not materialize if it were not for the hard work of many our colleagues and friends. This is why we want to express our gratitude to all the members of both the Programme and Organizing Committees. Last but not least, we also want to acknowledge the fact that this workshop is organized, due to the fact that the research of several members of the Organizing Committee is financially supported by grants GA CR no 15-00215S and 13-20012S. Keywords: Bayesian networks; uncertainty; optimization Fulltext is available at external website.
Proceedings of the 10th Workshop on Uncertainty Processing

WUPES 2015 is organized jointly by the Institute of Information Theory and Automation of the Czech Academy of Sciences and by the Faculty of Management, University of Economics, Prague. It is quite ...

Kratochvíl, Václav
Ústav teorie informace a automatizace, 2015

Model of Risk and Losses of a Multigeneration Mortgage Portfolio
Šmíd, Martin
2015 - English
During the last decades, Merton-Vasicek factor model (1987), later generalize by Frye at al. (2000), became standards in credit risk management. We present a generalization of these models allowing multiple sub-portfolios of loans possibly starting at different times and lasting more than one period. We show that, given this model, a one-to-one mapping between factors and the overall default rate and the charge-off rate exists, is differentiable and numerically computable. Keywords: risk management; loan portfolio; default rate; charge off rate Fulltext is available at external website.
Model of Risk and Losses of a Multigeneration Mortgage Portfolio

During the last decades, Merton-Vasicek factor model (1987), later generalize by Frye at al. (2000), became standards in credit risk management. We present a generalization of these models allowing ...

Šmíd, Martin
Ústav teorie informace a automatizace, 2015

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