Sándor Kolumbán
Budapest University of Technology and Economics
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Publication
Featured researches published by Sándor Kolumbán.
Automatica | 2015
Sándor Kolumbán; István Vajk; Johan Schoukens
Hypothesis testing methods that do not rely on exact distribution assumptions have been emerging lately. The method of sign-perturbed sums (SPS) is capable of characterizing confidence regions with exact confidence levels for linear regression and linear dynamical systems parameter estimation problems if the noise distribution is symmetric. This paper describes a general family of hypothesis testing methods that have an exact user chosen confidence level based on finite sample count and without relying on an assumed noise distribution. It is shown that the SPS method belongs to this family and we provide another hypothesis test for the case where the symmetry assumption is replaced with exchangeability. In the case of linear regression problems it is shown that the confidence regions are connected, bounded and possibly non-convex sets in both cases. To highlight the importance of understanding the structure of confidence regions corresponding to such hypothesis tests it is shown that confidence sets for linear dynamical systems parameter estimates generated using the SPS method can have non-connected parts, which have far reaching consequences.
Performance Evaluation | 2011
Márton Balázs; Gábor Horváth; Sándor Kolumbán; Péter Kovács; Miklós Telek
Markov fluid models with fluid level dependent behaviour are considered in this paper. One of the main difficulties of the analysis of these models is to handle the case when in a given state the fluid rate changes sign from positive to negative at a given fluid level. We refer to this case as zero transition. The case when this sign change is due to a discontinuity of the fluid rate function results in probability mass at the given fluid level. We show that the case when the sign change is due to a continuous finite polynomial function of the fluid rate results in a qualitatively different behaviour: no probability mass develops and different stationary equations apply. We consider this latter case of sign change, present its stationary description and propose a numerical procedure for its evaluation.
instrumentation and measurement technology conference | 2015
J. Schoukens; Sándor Kolumbán
In this paper the effect of short data lengths in system identification is studied. It addresses the question of the minimum required data length that is needed in order to apply the asymptotic results on the uncertainty analysis. this paper is focused on the IIR-case by analyzing initially a first order system. The conclusions are extended to higher order systems by normalizing all results on the time constant of this system, and by adding a model complexity factor.
Acta Cybernetica | 2015
Dávid Szalóki; Sándor Kolumbán; Kristóf Csorba; Gábor Tevesz
This paper focuses on the placement of cameras in order to achieve the highest possible localization accuracy with a multi-camera system. The cameras have redundant fields of view. They have to be placed according to some natural constraints but user defined constraints are allowed as well. A camera model is described and the components causing the localization errors are identified. Some localization accuracy measures are defined for any number of cameras. The multi-camera placement is analytically formulated using the expanded measures for multiple cameras. An example of placing two cameras is shown and the generalizations into higher dimensional parameter spaces are examined. There are publications where camera placement algorithms are formulated or compared. We make an attempt to examine the analytical solution of this problem in case of different objective functions.
international conference on system science and engineering | 2013
István Albert; Sándor Kolumbán; Hassan Charaf; László Lengyel
People use their mobile devices every day to access a wide variety digital content. The diversity of mobile platforms and that of mobile device capabilities requires providing automatic layout solutions for online content. For the purposes of this paper, our solutions focus on online magazines and newspapers. The Content-Driven Template-Based Layout System (CTLS) is a template-based online magazine layout approach, which facilitates in defining hierarchical layouts from basic layout elements and splitter components. The goal is to effectively calculate the resulting adaptation method for a particular layout element at any level of the layout hierarchy. This paper introduces the solution area-based approach of the CTLS. We apply inequalities, represented by solution areas (polygons), to ensure the flexibility of the approach.
Facing the Multicore-Challenge | 2013
Ákos Dudás; Sándor Juhász; Sándor Kolumbán
Mutual exclusion protects data structures in parallel environments in order to preserve data integrity. A lock being held effectively blocks the execution of all other threads wanting to access the same shared resource until the lock is released. This blocking behavior reduces the level of parallelism causing performance loss. Fine grained locking reduces the contention for the locks resulting in better throughput, however, the granularity, i.e. how many locks to use, is not straightforward. In large bucket hash tables, the best approach is to divide the table into blocks, each containing one or more buckets, and locking these blocks independently. The size of the block, for optimal performance, depends on the time spent within the critical sections, which depends on the table’s internal properties, and the arrival intensity of the queries. A queuing model is presented capturing this behavior, and an adaptive algorithm is presented fine-tuning the granularity of locking (the block size) to adapt to the execution environment.
IFAC Proceedings Volumes | 2012
Sándor Kolumbán; István Vajk
Abstract The goal of parametric system identification is to provide estimates for parameters of a certain model structure based on given measurement data. This problem can always be presented as an optimization problem with an appropriate choice of cost and constraint functions. Apart from the simplest cases the resulting optimization problems are nonconvex with multiple local minima. Due to the existence of these, usually there are no guaranties that the model resulting from a given identification method is a global minimizer. This paper applies semidefinite programming (SDP) relaxation techniques to the optimization problem arising in time domain identification. From the solution of the defined sequence of SDPs a sequence of system models can be extracted that converges to the globally optimal system model. We give a short overview of the SDP relaxation technique for polynomial optimization problems (POP), then this technique is applied to the identification problem. The properties of the resulting POP are examined in detail. The solutions of the SDP sequence usually converge to the optimizer only in the limit. Model structures where finite convergence occurs and issues regarding detecting finite convergence are also considered.
international symposium on computational intelligence and informatics | 2010
Sándor Kolumbán; István Vajk
Since system identification is closely related to control theory it is quite convenient that common tools of control may prove to be useful for identification as well. Semidefinite programming is now considered as a standard tool in control theory, however its applications for identification purposes are rare. This paper shows how L1 identification of the ARX model structure can be formulated as a semidefinite program. The way of incorporating a priori information into the identification process is demonstrated which necessitates the usage of semidefinite programming.
arXiv: Applications | 2017
Sándor Kolumbán; Stella Kapodistria; Nazanin Nooraee
Archive | 2017
Sándor Kolumbán; Stella Kapodistria