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Example creation system
Suzdaleva, Evgenia; Nagy, Ivan; Dungl, Martin
2010 - English
The technical report describes a system for creation of examples for fully probabilistic dynamic decision making. It represents a documentation for author who wishes to create examples for PhD students or to add their new developed algorithms to the system.
Keywords:
dynamic decision making; example creation; matlab
Fulltext is available at external website.
Example creation system
The technical report describes a system for creation of examples for fully probabilistic dynamic decision making. It represents a documentation for author who wishes to create examples for PhD ...
Automatic Removal of Sparse Artifacts in Electroencephalogram
Zima, Miroslav; Tichavský, Petr; Krajča, V.
2010 - English
This report presents an algorithm for removing artifacts from EEG signal, which is based on the method of independent component analysis utilizing the signal nonstationarity or sparsity of the artifacts. The algorithm is computationally very fast, enables online processing of long data records with excellent separation accuracy. The algorithm also incorporates using wavelet denoising of the artifact components, recently proposed by Castellanos and Makarov, which reduces distortion of the cleaned data.
Keywords:
electroencephalogram; independent component analysis; artifact removal; wavelet denoising
Fulltext is available at external website.
Automatic Removal of Sparse Artifacts in Electroencephalogram
This report presents an algorithm for removing artifacts from EEG signal, which is based on the method of independent component analysis utilizing the signal nonstationarity or sparsity of the ...
Introduction to Feature Selection Toolbox 3 – The C++ Library for Subset Search, Data Modeling and Classification
Somol, Petr; Vácha, Pavel; Mikeš, Stanislav; Hora, Jan; Pudil, Pavel; Žid, Pavel
2010 - English
We introduce a new standalone widely applicable software library for feature selection (also known as attribute or variable selection), capable of reducing problem dimensionality to maximize the accuracy of data models, performance of automatic decision rules as well as to reduce data acquisition cost. The library can be exploited by users in research as well as in industry. Less experienced users can experiment with different provided methods and their application to real-life problems, experts can implement their own criteria or search schemes taking advantage of the toolbox framework. In this paper we first provide a concise survey of a variety of existing feature selection approaches. Then we focus on a selected group of methods of good general performance as well as on tools surpassing the limits of existing libraries. We build a feature selection framework around them and design an object-based generic software library. We describe the key design points and properties of the library.
Keywords:
feature selection; software library; subset search; attribute selection; variable selection; optimization; machine learning; classification; pattern recognition
Fulltext is available at external website.
Introduction to Feature Selection Toolbox 3 – The C++ Library for Subset Search, Data Modeling and Classification
We introduce a new standalone widely applicable software library for feature selection (also known as attribute or variable selection), capable of reducing problem dimensionality to maximize the ...
How Does Monetary Policy Change? Evidence on Inflation Targeting Countries
Baxa, Jaromír; Horváth, R.; Vašíček, B.
2010 - English
We examine the evolution of monetary policy rules in a group of inflation targeting countries (Australia, Canada, New Zealand, Sweden and the United Kingdom), applying a moment-based estimator in a time-varying parameter model with endogenous regressors. Using this novel flexible framework, our main findings are threefold. First, monetary policy rules change gradually, pointing to the importance of applying a time-varying estimation framework. Second, the interest rate smoothing parameter is much lower than typically reported by previous time-invariant estimates of policy rules. External factors matter for all countries, although the importance of the exchange rate diminishes after the adoption of inflation targeting. Third, the response of interest rates to inflation is particularly strong during periods when central bankers want to break a record of high inflation, such as in the UK or Australia at the beginning of the 1980s.
Keywords:
Taylor rule; Inflation targeting; time-varying parameter model
Fulltext is available at external website.
How Does Monetary Policy Change? Evidence on Inflation Targeting Countries
We examine the evolution of monetary policy rules in a group of inflation targeting countries (Australia, Canada, New Zealand, Sweden and the United Kingdom), applying a moment-based estimator in a ...
Multifractal height cross-correlation analysis
Krištoufek, Ladislav
2010 - English
We introduce a new method for detection of long-range cross-correlations and cross-multifractality – multifractal height cross-correlation analysis (MF-HXA). We show that long-range cross-correlations can be caused by long-range dependence of separate processes and the correlations above them. Similar separation applies for cross-multifractality – standard sep- aration between distributional properties and correlations is enriched by division of correlations between auto-correlations and cross-correlations. Efficiency of the method is showed on two types of simulated series – ARFIMA and Mandelbrot’s Binomial Multifractal model. We further ap- ply the method on returns and volatility of NASDAQ and S&P500 indices and uncover some interesting results.
Keywords:
multifractality; long-range dependence; cross-correlations
Fulltext is available at external website.
Multifractal height cross-correlation analysis
We introduce a new method for detection of long-range cross-correlations and cross-multifractality – multifractal height cross-correlation analysis (MF-HXA). We show that long-range cross-correlations ...
Impact of forgetting on models of rolling mills
Dedecius, Kamil; Jirsa, Ladislav
2010 - English
The research report deals with an analysis of various models for modelling of the cold sheet rolling process. It comprises a thorough analysis of a mass-flow model and its weaknesses, brief analysis of normalization impact on modelling and exhaustive analysis of 4 defined models with exponential and partial forgetting and their comparison to models without forgetting. The report ends with a computer-intensive search for new blackbox models.
Keywords:
bayesian modelling; forgetting; parameter estimation
Fulltext is available at external website.
Impact of forgetting on models of rolling mills
The research report deals with an analysis of various models for modelling of the cold sheet rolling process. It comprises a thorough analysis of a mass-flow model and its weaknesses, brief analysis ...
Divergences between models and data under hypothetical and empirical quantizations
Vajda, Igor; van der Meulen, Edward
2010 - English
Je ukazáno, že hypotetické kvantování generuje clasická statistická kriteria Pearsonova typu, zatim co empirické kvantování generuje kriteria asymptoticky ekvivalentní klasickým přírůstkovým statistickým kriteriím.Jsou odvozeny asymptotické vlastnosti empiricky generovaných kriterií a dokázána optimálnost kvadratického kriteria. It is shown that the hypothetical quantization generates classical Pearson-type statistical criteria while the empirical quantization generates criteria asymptotically equivalent to the classical spacings-type statistical criteria. Asymptotic properties of the empirically generated criteria are derived and optimality of the quadratic criterion is proved.
Keywords:
Disparities; Hypothetical quantization; Asymptotic normality; Power divergences; Empirical quantization; Divergences; Asymptotic optimality; Consistency
Fulltext is available at external website.
Divergences between models and data under hypothetical and empirical quantizations
Je ukazáno, že hypotetické kvantování generuje clasická statistická kriteria Pearsonova typu, zatim co empirické kvantování generuje kriteria asymptoticky ekvivalentní klasickým přírůstkovým ...
How monetary policy changes in inflation targeting countries
Baxa, Jaromír; Horváth, R.; Vašíček, B.
2009 - English
V tomto paperu jsme analyzovali vývoj měnové politiky řady zemí s inflačním cílováním za pomoci časově proměnlivých (stochastických) koeficientů. In this paper, we examine the evolution of monetary policy rules in a group of inflation targeting countries (Australia, Canada, New Zealand, Sweden and the United Kingdom) applying moment estimator at time-varying parameter model with endogenous
Keywords:
Taylor rule; inflation targeting; monetary policy
Fulltext is available at external website.
How monetary policy changes in inflation targeting countries
V tomto paperu jsme analyzovali vývoj měnové politiky řady zemí s inflačním cílováním za pomoci časově proměnlivých (stochastických) koeficientů.
Bidirectional Texture Function Compression Based on Multi-Level Vector Quantization - Supplemental Material
Havran, V.; Filip, Jiří; Myszkowski, K.
2009 - English
Dvousměrná texturní funkce (BTF) se používá pro přesné zachycení vzhledu materálů. Tento text shrnuje výsledky nově navržené metody komprese BTF dat. Metoda je založená na nové reprezentaci dat pro jednotlivé pixely v závislosti na úhlech pohledu a osvětlení tvořící fukce pravděpodobnostních hustot. Tyto funkce jsou komprimovány pomocí navrženého víceúrovňového algoritmu založeného na vektorové kvantizaci. Výsledkem je skupina kódových knih obsahujících indexační a škálovací hodnoty. Rekonstrukce dat je pak dosažena pomocí vnořené indexace v těchto knihách. Luminanční a barevná složka jsou zpracovány odděleně a to umožňuje dosáhnout nízké rekonstrukční chyby a zároveň vysoké komprese 1:233-1:2040 v závislosti na složitosti komprimovaného vzorku. Navržená metoda je porovnána ze současnými metodami, jak numericky tak prostřednictvím psychovisuálního experimentu. Metoda byla rovněž implementována na grafické kartě a umožňuje vzorkování texturních dat podle důležitosti. The Bidirectional Texture Function (BTF) is becoming widely used for accurate representation of real-world material appearance. In this paper a novel BTF compression model is proposed. The model resamples input BTF data into a parametrization, allowing decomposition of individual view and illumination dependent texels into a set of multidimensional conditional probability density functions. These functions are compressed in turn using a novel multi-level vector quantization algorithm. The result of this algorithm is a set of index and scale code-books for individual dimensions. BTF reconstruction from the model is then based on fast chained indexing into the nested stored code-books. In the proposed model, luminance and chromaticity are treated separately to achieve further compression. The proposed model achieves low distortion and compression ratios 1:233-1:2040, depending on BTF sample variability.
Keywords:
texture; compression; BTF; vector quantization
Fulltext is available at external website.
Bidirectional Texture Function Compression Based on Multi-Level Vector Quantization - Supplemental Material
Dvousměrná texturní funkce (BTF) se používá pro přesné zachycení vzhledu materálů. Tento text shrnuje výsledky nově navržené metody komprese BTF dat. Metoda je založená na nové reprezentaci dat pro ...
Filtering with mixed continuous and discrete states: special case
Suzdaleva, Evgenia
2009 - English
Článek se zabývá algoritmy pro odhadování stavu smíšeného (spojitého a diskrétního) typu s aplikací v oblasti řízení městské dopravní sítě. The paper deals with algorithms of the state estimation with mixed-type (continuous and discrete) states with application in urban traffic control area.
Keywords:
state estimation; mixed data
Fulltext is available at external website.
Filtering with mixed continuous and discrete states: special case
Článek se zabývá algoritmy pro odhadování stavu smíšeného (spojitého a diskrétního) typu s aplikací v oblasti řízení městské dopravní sítě.
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