Numerické optimalizační metody
Lukšan, Ladislav
2024 - Czech Tato zpráva popisuje teoretické i praktické vlastnosti numerických metod pro nepodmíněnou optimalizaci. Studují se metody pro obecné i speciální optimalizační úlohy, mezi které patří minimalizace součtu čtverců, součtu absolutních hodnot, maximní hodnoty a dalších nehladkých funkcí. Kromě metod pro standardní úlohy středních rozměrů jsou studovány i metody pro rozsáhlé řídké a strukturované úlohy. Velká pozornost je věnována soustavám nelineárních rovnic.\n Keywords: Numerická optimalizace; nelineární aproximace; systémy nelineárních rovnic; algoritmy Available on request at various institutes of the ASCR Numerické optimalizační metody

Tato zpráva popisuje teoretické i praktické vlastnosti numerických metod pro nepodmíněnou optimalizaci. Studují se metody pro obecné i speciální optimalizační úlohy, mezi které patří minimalizace ...

Lukšan, Ladislav
Ústav informatiky, 2024

Some modifications of the limited-memory variable metric optimization methods
Vlček, Jan; Lukšan, Ladislav
2023 - English Several modifications of the limited-memory variable metric (or quasi-Newton) line search methods for large scale unconstrained optimization are investigated. First the block version of the symmetric rank-one (SR1) update formula is derived in a similar way as for the block BFGS update in Vlˇcek and Lukˇsan (Numerical Algorithms 2019). The block SR1 formula is then modified to obtain an update which can reduce the required number of arithmetic operations per iteration. Since it usually violates the corresponding secant conditions, this update is combined with the shifting investigated in Vlˇcek and Lukˇsan (J. Comput. Appl. Math. 2006). Moreover, a new efficient way how to realize the limited-memory shifted BFGS method is proposed. For a class of methods based on the generalized shifted economy BFGS update, global convergence is established. A numerical comparison with the standard L-BFGS and BNS methods is given. Keywords: unconstrained minimization; variable metric methods; limited-memory methods; variationally derived methods; arithmetic operations reduction; global convergence Available in a digital repository NRGL Some modifications of the limited-memory variable metric optimization methods

Several modifications of the limited-memory variable metric (or quasi-Newton) line search methods for large scale unconstrained optimization are investigated. First the block version of the symmetric ...

Vlček, Jan; Lukšan, Ladislav
Ústav informatiky, 2023

Souhrnná zpráva projektu LINE za rok 2023
Brabec, Marek; Juruš, Pavel; Malý, Marek; Pelikán, Emil; Šrotýř, M.; Turčičová, Marie
2023 - Czech Tato zpráva byla vytvořena řešitelským týmem Ústavu informatiky AV ČR, v.v.i. v Praze pro potřeby společnosti GasNet, s.r.o. na základě objednávky č. 4500028548. Ve zprávě jsou shrnuty výsledky činností prováděných v roce 2023. Je popsán proces zpracování vstupních dat a jsou řešeny úlohy detekce odlehlých pozorování spotřeby, analýzy bilančních rozdílů a charakterizace vývoje spotřeby plynu v prostoru a čase. Available at various institutes of the ASCR Souhrnná zpráva projektu LINE za rok 2023

Tato zpráva byla vytvořena řešitelským týmem Ústavu informatiky AV ČR, v.v.i. v Praze pro potřeby společnosti GasNet, s.r.o. na základě objednávky č. 4500028548. Ve zprávě jsou shrnuty výsledky ...

Brabec, Marek; Juruš, Pavel; Malý, Marek; Pelikán, Emil; Šrotýř, M.; Turčičová, Marie
Ústav informatiky, 2023

Etika AI: Přehled současné debaty v kontextu energetiky
Černý, David; Trčka, M.; Kolaříková, L.; Hvorecký, J.; Pelikán, Emil; Hříbek, T.; Novotný, D.; Wiedermann, Jiří
2023 - Czech Available at various institutes of the ASCR Etika AI: Přehled současné debaty v kontextu energetiky

Černý, David; Trčka, M.; Kolaříková, L.; Hvorecký, J.; Pelikán, Emil; Hříbek, T.; Novotný, D.; Wiedermann, Jiří
Ústav informatiky, 2023

Estimates of covariances for estimated concentration field
Brabec, Marek; Malý, Marek; Malá, Ivana
2023 - Czech Developing estimation of relevant covariance matrix entries for the spatial model as a necessary part for computing pointwise standard errors (as formalizations of local uncertainty for the gridded estimates). They, in turn are precursors for optimization algorithms aimed at measurement network design problems (location of added and/or deleted measurement points). BIBLIOGRAFICKÉ ÚDAJE: Výzkumná zpráva č. SS02030031-V95. Praha: ICS CAS, 2023. 22 s. ANOTACE: Obsahem tohoto dokumentu je popis výsledku typu O: SS02030031-V95, Odhady kovariancí odhadnutého prostorového pole koncentrací. Jde o postup odhadu kovariančních parametrů jak samotného latentního Gaussovského prostorového pole, tak o odhad kovariance regresních parametrů v modelu. Dále též formulace modelu malého měřítka vybraného z dříve testovaných variant. Testování algoritmu optimalizace umístění stanic na předvybraném scénáři. Keywords: spatial estimation; covariances; uncertainty Available at various institutes of the ASCR Estimates of covariances for estimated concentration field

Developing estimation of relevant covariance matrix entries for the spatial model as a necessary part for computing pointwise standard errors (as formalizations of local uncertainty for the gridded ...

Brabec, Marek; Malý, Marek; Malá, Ivana
Ústav informatiky, 2023

Spatio-Spectral EEG Patterns in the Source-Reconstructed Space and Relation to Resting-State Networks: An EEG-fMRI Study
Jiříček, Stanislav; Koudelka, V.; Mantini, D.; Mareček, R.; Hlinka, Jaroslav
2022 - English In this work, we present and evaluate a novel EEG-fMRI integration approach combining a spatio-spectral decomposition method and a reliable source localization technique. On the large 72 subjects resting- state hdEEG-fMRI data set we tested the stability of the proposed method in terms of both extracted spatio-spectral patterns(SSPs) as well as their correspondence to the BOLD signal. We also compared the proposed method with the spatio-spectral decomposition in the electrode space as well as well-known occipital alpha correlate in terms of the explained variance of BOLD signal. We showed that the proposed method is stable in terms of extracted patterns and where they correlate with the BOLD signal. Furthermore, we show that the proposed method explains a very similar level of the BOLD signal with the other methods and that the BOLD signal in areas of typical BOLD functional networks is explained significantly more than by a chance. Nevertheless, we didn’t observe a significant relation between our source-space SSPs and the BOLD ICs when spatio-temporally comparing them. Finally, we report several the most stable source space EEG-fMRI patterns together with their interpretation and comparison to the electrode space patterns. Keywords: EEG-fMRI Integration; EEG-informed fMRI; Spatio-spectral Decomposition; Electrical Source Imaging; Independent Component Analysis; Resting State Networks Available in digital repository of the ASCR Spatio-Spectral EEG Patterns in the Source-Reconstructed Space and Relation to Resting-State Networks: An EEG-fMRI Study

In this work, we present and evaluate a novel EEG-fMRI integration approach combining a spatio-spectral decomposition method and a reliable source localization technique. On the large 72 subjects ...

Jiříček, Stanislav; Koudelka, V.; Mantini, D.; Mareček, R.; Hlinka, Jaroslav
Ústav informatiky, 2022

Tisková zpráva - měření tepelného komfortu
Geletič, Jan; Lehnert, M.
2022 - Czech Fulltext is available at external website. Tisková zpráva - měření tepelného komfortu

Geletič, Jan; Lehnert, M.
Ústav informatiky, 2022

A Measure of Variability WIthin Parametric Families of Continuous Distributions
Fabián, Zdeněk
2022 - English A continuous probability measure on an open interval of the real line induces in it a unique geometry, "center of gravity" of which is the typical value of the distribution. In the paper is identified a score variance as a finite measure of variability of distributions with respect to the typical value and discussed its properties and methods of estimation. Itroducing a generalized Rao distance in the sample space one can appraise the precision of the estimate of the typical value. Keywords: scalar-valued score; score mean; score variance; distance in the sample space Available at various institutes of the ASCR A Measure of Variability WIthin Parametric Families of Continuous Distributions

A continuous probability measure on an open interval of the real line induces in it a unique geometry, "center of gravity" of which is the typical value of the distribution. In the paper is identified ...

Fabián, Zdeněk
Ústav informatiky, 2022

Score correlation for skewed distributions
Fabián, Zdeněk
2022 - English Based on the new concept of the scalar-valued score function of continuous distributions we introduce the score correlation coefficient ”tai-lored” to the assumed probabilistic model and study its properties by means of simulation experiments. It appeared that the new correlation method is useful for enormously skewed distributions. Keywords: Scalar-valued score; score coefficient of variation; Monte Carlo Available at various institutes of the ASCR Score correlation for skewed distributions

Based on the new concept of the scalar-valued score function of continuous distributions we introduce the score correlation coefficient ”tai-lored” to the assumed probabilistic model and study its ...

Fabián, Zdeněk
Ústav informatiky, 2022

Introduction to statistical inference based on scalar-valued scores
Fabián, Zdeněk
2022 - English In the report we maintain consistently the following point of view: Given a continuous model, there are not the observed values, which are to be used in probabilistic and statistical considerations, but their ”treated forms”,the values of the scalar-valued score function corresponding to the model. Based on this modified concept of the score function, we develop theory of score random variables, study their geometry and define their new characteristics, finite even in cases of heavy-tailed models. A generalization for parametric families provides a new approach to parametric point estimation. Keywords: continuous distributions; score mean; score variance; score moment estimation method; score distance Available at various institutes of the ASCR Introduction to statistical inference based on scalar-valued scores

In the report we maintain consistently the following point of view: Given a continuous model, there are not the observed values, which are to be used in probabilistic and statistical considerations, ...

Fabián, Zdeněk
Ústav informatiky, 2022