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Dragan Obradovic
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Books and Theses
- 1996
- [b1]Gustavo Deco, Dragan Obradovic:
An information-theoretic approach to neural computing. Perspectives in neural computing, Springer 1996, ISBN 978-0-387-94666-5, pp. I-XIII, 1-261
Journal Articles
- 2015
- [j14]Ulrich Münz, Michael Metzger, Andrei Szabo, Markus Reischböck, Florian Steinke, Philipp Wolfrum, Rudolf Sollacher, Dragan Obradovic, Michael Buhl, Thomas Lehmann, Mathias Duckheim, Stefan Langemeyer:
Overview of recent control technologies for future power systems. Autom. 63(11): 869-882 (2015) - 2011
- [j13]Junqi Liu, Andrea Benigni, Dragan Obradovic, Sandra Hirche, Antonello Monti:
State Estimation and Branch Current Learning Using Independent Local Kalman Filter With Virtual Disturbance Model. IEEE Trans. Instrum. Meas. 60(9): 3026-3034 (2011) - 2009
- [j12]Ruxandra Lupas Scheiterer, Chongning Na, Dragan Obradovic, Günter Steindl:
Synchronization Performance of the Precision Time Protocol in Industrial Automation Networks. IEEE Trans. Instrum. Meas. 58(6): 1849-1857 (2009) - 2008
- [j11]Chongning Na, Dragan Obradovic, Andrei Szabo:
Signal Processing EM based channel estimation method for MIMO-OFDM systems. Eur. Trans. Telecommun. 19(8): 907-916 (2008) - [j10]Dragan Obradovic, Chongning Na, Ruxandra Lupas Scheiterer, Andrei Szabo:
EM-based semi-blind channel estimation method for MIMO-OFDM communication systems. Neurocomputing 71(10-12): 2388-2398 (2008) - 2007
- [j9]Dragan Obradovic, Henning Lenz, Markus Schupfner:
Fusion of Sensor Data in Siemens Car Navigation System. IEEE Trans. Veh. Technol. 56(1): 43-50 (2007) - [j8]Ruxandra Lupas Scheiterer, Dragan Obradovic, Volker Tresp:
Tailored-to-Fit Bayesian Network Modeling of Expert Diagnostic Knowledge. J. VLSI Signal Process. 49(2): 301-316 (2007) - 2006
- [j7]Dragan Obradovic, Henning Lenz, Markus Schupfner:
Fusion of Map and Sensor Data in a Modern Car Navigation System. J. VLSI Signal Process. 45(1-2): 111-122 (2006) - 1998
- [j6]Dragan Obradovic, Gustavo Deco:
Information Maximization and Independent Component Analysis: Is There a Difference? Neural Comput. 10(8): 2085-2101 (1998) - 1996
- [j5]Dragan Obradovic, Gustavo Deco:
An information theory based learning paradigm for linear feature extraction. Neurocomputing 12(2-3): 203-221 (1996) - [j4]Dragan Obradovic:
On-line training of recurrent neural networks with continuous topology adaptation. IEEE Trans. Neural Networks 7(1): 222-228 (1996) - 1995
- [j3]Gustavo Deco, Dragan Obradovic:
Decorrelated Hebbian Learning for Clustering and Function Approximation. Neural Comput. 7(2): 338-348 (1995) - [j2]Gustavo Deco, Dragan Obradovic:
Linear redundancy reduction learning. Neural Networks 8(5): 751-755 (1995) - 1992
- [j1]Dragan Obradovic, Lena S. Valavani:
Stability and performance in the presence of magnitude bounded real uncertainty: Riccati equation based state space approaches. Autom. 28(4): 827-830 (1992)
Conference and Workshop Papers
- 2021
- [c24]Abhi Patel, Tim Schenk, Steffi Knorn, Heiko Patzlaff, Dragan Obradovic, Andrés Botero Halblaub:
Real-time, Simulation-based Identification of Cyber-Security Attacks of Industrial Plants. CSR 2021: 267-272 - 2020
- [c23]Stefan Löw, Dragan Obradovic, Abhinav Anand, Andrei Szabo:
Stage Cost Formulations of Online Rainflow-counting for Model Predictive Control of Fatigue. ECC 2020: 475-482 - 2019
- [c22]Jingjie Jiang, Dragan Obradovic:
Optimal Control of a Fleet of AGVs on a Rectangular Grid: a MILP-based Approach. CASE 2019: 1054-1059 - [c21]Stefan Löw, Dragan Obradovic, Carlo L. Bottasso:
Direct Online Rainflow-counting and Indirect Fatigue Penalization Methods for Model Predictive Control. ECC 2019: 3371-3376 - 2018
- [c20]Stefan Löw, Dragan Obradovic:
Real-time Implementation of Nonlinear Model Predictive Control for Mechatronic Systems Using a Hybrid Model. CASE 2018: 164-167 - 2012
- [c19]Herbert Mangesius, Sandra Hirche, Dragan Obradovic:
Quasi-stationarity of electric power grid dynamics based on a spatially embedded Kuramoto model. ACC 2012: 2159-2164 - 2010
- [c18]Chongning Na, Philipp Wolfrum, Dragan Obradovic, Ruxandra Lupas Scheiterer:
Optimal Estimation and Control of Clock Synchronization Following the Precision Time Protocol. CCA 2010: 1767-1772 - [c17]Junqi Liu, Andrea Benigni, Dragan Obradovic, Sandra Hirche, Antonello Monti:
State estimation and learning of unknown branch current flows using decentralized Kalman filter with virtual disturbance model. AMPS 2010: 31-36 - 2009
- [c16]Chongning Na, Dragan Obradovic, Ruxandra Lupas Scheiterer:
A probabilistic approach to clock synchronization of cascaded network elements. ICASSP 2009: 1793-1796 - 2008
- [c15]Ruxandra Lupas Scheiterer, Chongning Na, Dragan Obradovic, Günter Steindl, Dragan Goetz:
Synchronization performance of the Precision Time Protocol in the face of slave clock frequency drift. CASE 2008: 554-559 - [c14]Dragan Obradovic, Ruxandra Lupas Scheiterer, Chongning Na, Günter Steindl, Franz-Josef Goetz:
Clock Synchronization in Industrial Automation Networks - Comparison of Different Syntonization Methods. ICINCO-RA (1) 2008: 85-92 - [c13]Chongning Na, Hui Wang, Dragan Obradovic, Uwe D. Hanebeck:
Fourier density approximation for belief propagation in wireless sensor networks. MFI 2008: 290-295 - 2007
- [c12]Da Xu, Chih-Chung Chen, Dragan Obradovic, Bernhard Lang:
Variable sampling rate in networked control systems. ALCOSP 2007: 441-446 - 2006
- [c11]Dragan Obradovic, Andrei Szabo, Chongning Na:
EM-based enhancement of the Wiener Pilot-Aided Channel Estimation in MIMO-OFDM systems. EUSIPCO 2006: 1-5 - [c10]Mo Chen, David Sommer, Su Lee Goh, Temujin Gautama, Dragan Obradovic, Martin Golz, Mary J. Morrell, Hui Wang, Danilo P. Mandic:
A Novel Tool for Sequential Fusion of Nonlinear Features: A Sleep Psychology Application. MFI 2006: 474-478 - 2005
- [c9]Danilo P. Mandic, Dragan Obradovic, Anthony Kuh, Tülay Adali, Udo Trutschel, Martin Golz, Philippe De Wilde, Javier A. Barria, Anthony G. Constantinides, Jonathon A. Chambers:
Data Fusion for Modern Engineering Applications: An Overview. ICANN (2) 2005: 715-721 - [c8]Dragan Obradovic, Ruxandra Scheiterer:
Troubleshooting in GSM Mobile Telecommunication Networks Based on Domain Model and Sensory Information. ICANN (2) 2005: 729-734 - [c7]Ruxandra Scheiterer, Dragan Obradovic:
Bayesian Network Modeling Aspects Resulting from Applications in Medical Diagnostics and GSM Troubleshooting. ICANN (2) 2005: 747-752 - 2000
- [c6]Dragan Obradovic:
Stability and Performance Robustness Issues in Neural Network Feedback Linearization. IJCNN (1) 2000: 248-253 - 1999
- [c5]Dragan Obradovic:
Dynamic signal mixtures and blind source separation. ICASSP 1999: 1441-1444 - [c4]Dragan Obradovic, Zoran Obradovic:
Efficient probability density balancing for supporting distributed knowledge discovery in large databases. IJCNN 1999: 2535-2538 - [c3]Dragoljub Pokrajac, Tim Fiez, Dragan Obradovic, Stephen Kwek, Zoran Obradovic:
Distribution comparison for site-specific regression modeling in agriculture. IJCNN 1999: 3937-3941 - 1997
- [c2]Dragan Obradovic, Gustavo Deco:
Unsupervised learning for blind source separation: an information-theoretic approach. ICASSP 1997: 127-130 - 1993
- [c1]Dragan Obradovic, Gustavo Deco, Herbert Furumoto, C. Fricke:
Application of Neural Networks in Pulp Production. KI 1993: 376-383
Coauthor Index
aka: Ruxandra Scheiterer
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