Dragan Obradovic

发表

A method for time synchronization in a communications network having a plurality of network nodes

Michael Armbruster, Michael Buhl, Dragan Obradovic, 2013 .

Clock Synchronization in Industrial Automation Networks - Comparison of Different Syntonization Methods

Dragan Obradovic, Chongning Na, Ruxandra Lupas Scheiterer, 2008, ICINCO-RA.

Nonlinear Feature Extraction: Deterministic Neural Networks

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

Stability and performance in the presence of magnitude bounded real uncertainty: Riccati equation based state space approaches

Dragan Obradovic, Lena S. Valavani, 1992, Autom..

A probabilistic approach to clock synchronization of cascaded network elements

Dragan Obradovic, Chongning Na, Ruxandra Lupas Scheiterer, 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

State Estimation and Branch Current Learning Using Independent Local Kalman Filter With Virtual Disturbance Model

Junqi Liu, Sandra Hirche, Antonello Monti, 2011, IEEE Transactions on Instrumentation and Measurement.

Linear redundancy reduction learning

Gustavo Deco, Dragan Obradovic, 1995, Neural Networks.

Stability and performance robustness issues in neural network feedback linearization

Dragan Obradovic, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Supervised Learning and Statistical Estimation

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

Design of a robust control system for postfailure operation

Dragan Obradovic, 1990 .

Optimal estimation and control of clock synchronization following the Precision Time Protocol

Dragan Obradovic, Chongning Na, Ruxandra Lupas Scheiterer, 2010, 2010 IEEE International Conference on Control Applications.

Fourier density approximation for belief propagation in wireless sensor networks

Hui Wang, Uwe D. Hanebeck, Dragan Obradovic, 2008, 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.

Statistical Physics Theory of Supervised Learning and Generalization

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

State estimation and learning of unknown branch current flows using decentralized Kalman filter with virtual disturbance model

Junqi Liu, Sandra Hirche, Antonello Monti, 2010, 2010 IEEE International Workshop on Applied Measurements for Power Systems.

Complex-valued forecasting of wind profile

Kazuyuki Aihara, Danilo P. Mandic, Dragan Obradovic, 2006 .

Exploiting Signal Nongaussianity and Nonlinearity for Performance Assessment of Adaptive Filtering Algorithms: Qualitative Performance of Kalman Filter

Dragan Obradovic, Danilo Mandic, Temujin Gautama, 2006, 2006 IEEE Nonlinear Statistical Signal Processing Workshop.

Echtzeit-Implementierung von NMPC

Dragan Obradovic, Stefan Löw, 2018 .

Synchronization Performance of the Precision Time Protocol in Industrial Automation Networks

Dragan Obradovic, Chongning Na, Ruxandra Lupas Scheiterer, 2009, IEEE Transactions on Instrumentation and Measurement.

An information theory based learning paradigm for linear feature extraction

Gustavo Deco, Dragan Obradovic, G. Deco, 1996, Neurocomputing.

Fusion of Sensor Data in Siemens Car Navigation System

Dragan Obradovic, Henning Lenz, Markus Schupfner, 2007, IEEE Transactions on Vehicular Technology.

Dynamic signal mixtures and blind source separation

Dragan Obradovic, D. Obradovic, 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

Variable sampling rate in networked control systems

Dragan Obradovic, Da Xu, Chih-Chung Chen, 2007, ALCOSP.

A Novel Tool for Sequential Fusion of Nonlinear Features: A Sleep Psychology Application

Mo Chen, Hui Wang, Danilo P. Mandic, 2006, 2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.

Signal Processing EM based channel estimation method for MIMO-OFDM systems

Andrei Szabo, Dragan Obradovic, Chongning Na, 2008, Eur. Trans. Telecommun..

Gustavo Deco, Dragan Obradovic, 1995, Neural Computation.

Information Theory Based Regularizing Methods

Gustavo Deco, Dragan Obradovic, 1996 .

Troubleshooting in GSM Mobile Telecommunication Networks Based on Domain Model and Sensory Information

Dragan Obradovic, Ruxandra Lupas Scheiterer, 2005, ICANN.

Tailored-to-Fit Bayesian Network Modeling of Expert Diagnostic Knowledge

Dragan Obradovic, Ruxandra Lupas Scheiterer, Volker Tresp, 2007, J. VLSI Signal Process..

Recurrent neural networks with continuous topology adaptation, Kalman filter based training

Dragan Obradovic, 1997, COLT 1997.

Recursive Learning in Recurrent Neural Networks with Varying Architecture

Dragan Obradovic, 1994 .

Data Fusion for Modern Engineering Applications: An Overview

Anthony G. Constantinides, Danilo P. Mandic, Tülay Adali, 2005, ICANN.

Synchronization performance of the Precision Time Protocol in the face of slave clock frequency drift

Dragan Obradovic, Chongning Na, Ruxandra Lupas Scheiterer, 2008, 2008 IEEE International Conference on Automation Science and Engineering.

EM-based enhancement of the Wiener Pilot-Aided Channel Estimation in MIMO-OFDM systems

Andrei Szabo, Dragan Obradovic, Chongning Na, 2006, 2006 14th European Signal Processing Conference.

On-line training of recurrent neural networks with continuous topology adaptation

Dragan Obradovic, D. Obradovic, 1996, IEEE Trans. Neural Networks.

Bayesian Network Modeling Aspects Resulting from Applications in Medical Diagnostics and GSM Troubleshooting

Dragan Obradovic, Ruxandra Lupas Scheiterer, 2005, ICANN.

Fusion of Map and Sensor Data in a Modern Car Navigation System

Dragan Obradovic, Henning Lenz, Markus Schupfner, 2006, J. VLSI Signal Process..

Multimodal Fusion for Car Navigation Systems

Henning Lenz, Dragan Obradovic, Kai Heesche, 2008 .

Linear Feature Extraction: Infomax Principle

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

An algorithm for performance optimization in the presence of norm bounded structured uncertainty and its application to the system recovery after failure

Dragan Obradovic, Decision Systems., Lena Valavani, 1991 .

Preliminaries of Information Theory and Neural Networks

Gustavo Deco, Dragan Obradovic, 1996 .

Nonlinear Feature Extraction: Boolean Stochastic Networks

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

Application of Neural Networks in Pulp Production

Gustavo Deco, Herbert Furumoto, Dragan Obradovic, 1993, KI.

Distribution comparison for site-specific regression modeling in agriculture

Stephen Kwek, Zoran Obradovic, Dragoljub Pokrajac, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Efficient probability density balancing for supporting distributed knowledge discovery in large databases

Zoran Obradovic, Dragan Obradovic, Z. Obradovic, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Quasi-stationarity of electric power grid dynamics based on a spatially embedded Kuramoto model

Sandra Hirche, Dragan Obradovic, Herbert Mangesius, 2012, 2012 American Control Conference (ACC).

Study on the Effect of Time Delay on the Performance of Distributed Power Grids with Networked Cooperative Control

Junqi Liu, Azwirman Gusrialdi, Sandra Hirche, 2009 .

Real-time Implementation of Nonlinear Model Predictive Control for Mechatronic Systems Using a Hybrid Model

Dragan Obradovic, Stefan Löw, 2018, 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE).

Unsupervised learning for blind source separation: an information-theoretic approach

Gustavo Deco, Dragan Obradovic, G. Deco, 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Fourier density approximation for belief propagation in wireless sensor networks

Uwe D. Hanebeck, Dragan Obradovic, Chongning Na, 2008 .

Overview of recent control technologies for future power systems

Thomas Lehmann, Andrei Szabo, Florian Steinke, 2015, Autom..

Supervised Learning for Decorrelated Gaussian Networks

Gustavo Deco, Dragan Obradovic, 1993 .

Real-time, Simulation-based Identification of Cyber-Security Attacks of Industrial Plants

Dragan Obradovic, Heiko Patzlaff, Steffi Knorn, 2021, 2021 IEEE International Conference on Cyber Security and Resilience (CSR).

STABILITY AND PERFORMANCE ANALYSIS IN THE PRESENCE OF MAGNITUDE BOUNDED REAL UNCERTAINTY

Dragan Obradovic, Decision Systems., Lena Valavani, 1991 .

Robust Control of the Chaotic Lorenz System

Henning Lenz, Dragan Obradovic, 1997 .

Analysis of Cometitive Electricity Markets under a New Model of Real-Time Retail Princing with Ex-Post Adjustment

Munther A. Dahleh, Mardavij Roozbehani, Dragan Obradovic, 2011, EEM 2011.

STABILIZING HIGHER PERIODIC ORBITS OF CHAOTIC DISCRETE-TIME MAPS

Henning Lenz, Dragan Obradovic, D. Obradovic, 1999 .

When is OGY Control More Than Just Pole Placement

Henning Lenz, Dragan Obradovic, 1997 .

Blind source separation: are information maximization and redundancy minimization different?

Dragan Obradovic, G. Deco, Gustavo Deco, 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.