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Gábor Szederkényi
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2020 – today
- 2024
- [j28]Josef Diblík, Mihály Pituk, Gábor Szederkényi:
Large time behavior of nonautonomous linear differential equations with Kirchhoff coefficients. Autom. 161: 111473 (2024) - [c24]Mihály A. Vághy, Irene Otero-Muras, Gábor Szederkényi:
Analysis and Control of Gene Regulation Network Models Using Kinetic Semi-Discretization. ECC 2024: 1264-1269 - 2023
- [c23]Balázs Csutak, Gábor Szederkényi:
Reference Tracking Control of a Nonlinear Epidemiological Model with State Estimation. CoDIT 2023: 2311-2316 - [c22]Gergely Horváth, Gábor Szederkényi, István Zoltan Reguly:
Quantifying and comparing the impact of combinations of non-pharmaceutical interventions on the spread of COVID-19. MED 2023: 1010-1015 - [i4]Sondre Wiersdalen, Mike Pereira, Annika Lang, Gábor Szederkényi, Jean Auriol, Balázs Kulcsár:
Incremental Exponential Stability of the Unidirectional Flow Model. CoRR abs/2312.11061 (2023) - 2022
- [j27]Tamás Péni
, Balázs Csutak, Ferenc A. Bartha
Optimizing Symptom Based Testing Strategies for Pandemic Mitigation. IEEE Access 10: 84934-84945 (2022) - [j26]Péter Polcz
Lyapunov function computation for autonomous systems with complex dynamic behavior. Eur. J. Control 65: 100619 (2022) - [j25]István Z. Reguly
Microsimulation based quantitative analysis of COVID-19 management strategies. PLoS Comput. Biol. 18(1) (2022) - [c21]Mihály A. Vághy
Hamiltonian representation of generalized ribosome flow models. ECC 2022: 657-662 - 2021
- [j24]Tamas Peni
Convex output feedback model predictive control for mitigation of COVID-19 pandemic. Annu. Rev. Control. 52: 543-553 (2021) - [j23]György Lipták, Katalin M. Hangos, Gábor Szederkényi
Stabilizing feedback design for time delayed polynomial systems using kinetic realizations. Eur. J. Control 57: 163-171 (2021) - [c20]Péter Polcz
Lyapunov function computation for nonlinear systems through dynamical embedding - A case study. ECC 2021: 1869-1874 - [c19]Balázs Csutak, Péter Polcz
Computation of COVID-19 epidemiological data in Hungary using dynamic model inversion. SACI 2021: 91-96 - [i3]György Lipták, Mike Pereira, Balázs Kulcsár, Mihály Kovács
Traffic Reaction Model. CoRR abs/2101.10190 (2021) - [i2]Gábor Szederkényi, Tamás Péni, Gergely Röst:
Control Theoretic Approach for COVID-19 Management. ERCIM News 2021(124) (2021) - 2020
- [j22]Péter Polcz
Induced L2-gain computation for rational LPV systems using Finsler's lemma and minimal generators. Syst. Control. Lett. 142: 104738 (2020)
2010 – 2019
- 2019
- [j21]Gergely Szlobodnyik
Reachability Analysis of Low-Order Discrete State Reaction Networks Obeying Conservation Laws. Complex. 2019: 1035974:1-1035974:13 (2019) - [j20]Alejandro Fernández Villaverde
Computational Methods for Identification and Modelling of Complex Biological Systems. Complex. 2019: 4951650:1-4951650:3 (2019) - [j19]Péter Polcz
Computational method for estimating the domain of attraction of discrete-time uncertain rational systems. Eur. J. Control 49: 68-83 (2019) - [c18]Péter Polcz
Passivity analysis of rational LPV systems using Finsler's lemma. CDC 2019: 3793-3798 - [c17]Nawar Al-Hemeary, Gábor Szederkényi
Power Regulation and Linearization-Based Control Design of a Small Satellite. DeSE 2019: 646-650 - [c16]Lorine Márton, Gábor Szederkényi
Observer-based Diagnosis in Chemical Reaction Networks. ECC 2019: 3120-3125 - [c15]György Lipták, Katalin M. Hangos, Gábor Szederkényi
Stabilization of time delayed nonnegative polynomial systems through kinetic realization. ECC 2019: 3138-3143 - 2018
- [j18]Bernadett Ács, Gergely Szlobodnyik, Gábor Szederkényi
A computational approach to the structural analysis of uncertain kinetic systems. Comput. Phys. Commun. 228: 83-95 (2018) - [j17]Péter Polcz
Improved algorithm for computing the domain of attraction of rational nonlinear systems. Eur. J. Control 39: 53-67 (2018) - [j16]György Lipták, Katalin M. Hangos
Semistability of complex balanced kinetic systems with arbitrary time delays. Syst. Control. Lett. 114: 38-43 (2018) - [c14]Gergely Svab, Gergo Horvath, Gábor Szederkényi
Modeling of the Citric Acid Cycle and its Two Shuttle Systems. MED 2018: 70-77 - 2016
- [j15]Bernadett Ács, Gábor Szederkényi
Computing all possible graph structures describing linearly conjugate realizations of kinetic systems. Comput. Phys. Commun. 204: 11-20 (2016) - 2015
- [j14]György Lipták
Computing zero deficiency realizations of kinetic systems. Syst. Control. Lett. 81: 24-30 (2015) - [c13]Zoltán A. Tuza, Dan Siegal-Gaskins
Analysis-based parameter estimation of an in vitro transcription-translation system. ECC 2015: 1560-1566 - [c12]Zoltán A. Tuza, Gábor Szederkényi
Computing core reactions of uncertain polynomial kinetic systems. MED 2015: 1140-1147 - 2014
- [c11]Dávid Csercsik, Gábor Szederkényi
Parametric analysis of dynamically equivalent reaction network models. MED 2014: 1365-1370 - 2013
- [j13]Ralf Hannemann-Tamás
Model complexity reduction of chemical reaction networks using mixed-integer quadratic programming. Comput. Math. Appl. 65(10): 1575-1595 (2013) - [j12]Zoltán András Tuza, Gábor Szederkényi, Katalin M. Hangos
Computing All Sparse kinetic Structures for a Lorenz System using Optimization. Int. J. Bifurc. Chaos 23(8) (2013) - [j11]József Veres, György Cserey, Gábor Szederkényi:
Bio-inspired backlash reduction of a low-cost robotic joint using closed-loop-commutated stepper motors. Robotica 31(5): 789-796 (2013) - [c10]Attila Magyar
Stabilizing dynamic feedback design of quasi-polynomial systems using their underlying reduced linear dynamics. CDC 2013: 636-641 - [c9]Attila Gábor
On the Verification and Correction of Large-Scale Kinetic Models in Systems Biology. CMSB 2013: 206-219 - [c8]Katalin M. Hangos, Attila Gábor, Gábor Szederkényi:
Model reduction in bio-chemical reaction networks with Michaelis-Menten kinetics. ECC 2013: 4478-4483 - 2012
- [j10]Gábor Szederkényi, Julio R. Banga
CRNreals: a toolbox for distinguishability and identifiability analysis of biochemical reaction networks. Bioinform. 28(11): 1549-1550 (2012) - [j9]Dávid Csercsik, Katalin M. Hangos
Identifiability analysis and parameter estimation of a single Hodgkin-Huxley type voltage dependent ion channel under voltage step measurement conditions. Neurocomputing 77(1): 178-188 (2012) - 2011
- [j8]Gábor Szederkényi, Julio R. Banga
Inference of complex biological networks: distinguishability issues and optimization-based solutions. BMC Syst. Biol. 5: 177 (2011) - [j7]Attila Gábor
Modeling and Identification of a Nuclear Reactor with Temperature Effects and Xenon Poisoning. Eur. J. Control 17(1): 104-115 (2011) - 2010
- [j6]Dávid Csercsik, Imre Farkas, Gábor Szederkényi, Erik Hrabovszky
Hodgkin-Huxley type modelling and parameter estimation of GnRH neurons. Biosyst. 100(3): 198-207 (2010) - [j5]Szabolcs Rozgonyi, Katalin M. Hangos, Gábor Szederkényi:
Determining the domain of attraction of hybrid non-linear systems using maximal Lyapunov functions. Kybernetika 46(1): 19-37 (2010) - [c7]Zoltán A. Tuza, János Rudan, Gábor Szederkényi:
Developing an integrated software environment for mobile robot navigation and control. IPIN 2010: 1-6 - [i1]Dávid Csercsik, Gábor Szederkényi, Katalin M. Hangos:
Modelling of Rapid and Slow Transmission Using the Theory of Reaction Kinetic Networks. ERCIM News 2010(82): 22 (2010)
2000 – 2009
- 2009
- [c6]Dávid Csercsik, Gábor Szederkényi
Model synthesis identification a Hodgkin-Huxley-type neuron model. ECC 2009: 3058-3063 - [c5]Gábor Szederkényi
Identifiability study of a pressurizer in a pressurized water nuclear power plant. ECC 2009: 3503-3508 - 2008
- [j4]Irene Otero-Muras
Dynamic analysis and control of biochemical reaction networks. Math. Comput. Simul. 79(4): 999-1009 (2008) - [j3]Irene Otero-Muras
Local dissipative Hamiltonian description of reversible reaction networks. Syst. Control. Lett. 57(7): 554-560 (2008) - [c4]István Varga
Implementation of dynamic inversion-based control of a pressurizer at the Paks NPP. CCA 2008: 79-84 - 2006
- [j2]Barna Pongrácz, Gábor Szederkényi, Katalin M. Hangos
An algorithm for determining a class of invariants in quasi-polynomial systems. Comput. Phys. Commun. 175(3): 204-211 (2006) - 2004
- [j1]Katalin M. Hangos
The effect of model simplification assumptions on the differential index of lumped process models. Comput. Chem. Eng. 28(1-2): 129-137 (2004) - 2003
- [c3]Gábor Szederkényi, Tamás Schné, Katalin M. Hangos:
Zero dynamics of continuous and FED-batch bioreactors. ECC 2003: 2523-2528
1990 – 1999
- 1999
- [c2]Katalin M. Hangos, Gábor Szederkényi
Grey box process modelling for fault detection and isolation. ECC 1999: 4131-4136 - [c1]L. Tesar, Ludek Berec
A toolbox for model-based fault detection and isolation. ECC 1999: 4149-4154
Coauthor Index
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last updated on 2024-08-07 22:29 CEST by the dblp team
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