Publications

Publications TU-Biblio

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Number of items at this level: 140.

2019

Linzner, Dominik ; Schmidt, Michael ; Koeppl, Heinz (2019):
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
In: Proceedings of Neural Information Processing Systems, In: 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 09.12.-13.12.2019, [Online-Edition: https://arxiv.org/abs/1909.04570],
[Konferenzveröffentlichung]

Lehr, François-Xavier ; Hanst, Maleen ; Vogel, Marc ; Kremer, Jennifer ; Göringer, H. Ulrich ; Suess, Beatrix ; Koeppl, Heinz
American Chemical Society (Urheber) (2019):
Cell-free prototyping of AND-logic gates based on heterogeneous RNA activators.
In: ACS Synthetic Biology, ACS Publications, 8, (8), ISSN 2161-5063,
DOI: 10.1021/acssynbio.9b00238,
[Online-Edition: https://pubs.acs.org/doi/abs/10.1021/acssynbio.9b00238],
[Article]

Wildner, Christian ; Koeppl, Heinz
PMLR (Urheber) (2019):
Moment-Based Variational Inference for Markov Jump Processes.
In: Proceedings of Machine Learning Research, In: International Conference on Machine Learning, Long Beach, California, USA, June 9-15, 2019, In: PMLR, 97, ISSN 2640-3498,
[Online-Edition: http://proceedings.mlr.press/v97/wildner19a.html],
[Konferenzveröffentlichung]

KhudaBukhsh, W. R. ; Kar, S. ; Koeppl, H. ; Rizk, A. (2019):
Provisioning and Performance Evaluation of Parallel 1 Systems with Output Synchronization.
In: ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), Association for Computing Machinery ACM, S. Art. 6, 4, (1), ISSN 2376-3639,
[Online-Edition: https://dl.acm.org/citation.cfm?id=3300142],
[Article]

Kang, H.-W. ; Khuda Bukhsh, W.R. ; Koeppl, H. ; Rempala, G.A. (2019):
Quasi-steady-state approximations derived from the stochastic model of enzyme kinetics.
In: Bulletin of Mathematical Biology, Springer US, S. 1-34, ISSN 0092-8240,
DOI: 10.1007/s11538-019-00574-4,
[Online-Edition: https://link.springer.com/article/10.1007/s11538-019-00574-4...],
[Article]

Alt, Bastian ; Weckesser, Markus ; Becker, Christian ; Hollick, Matthias ; Kar, Sounak ; Klein, Anja ; Klose, Robin ; Kluge, Roland ; Koeppl, Heinz ; KhudaBukhsh, Wasiur R. ; Luthra, Manisha ; Mousavi, Mahdi ; Mühlhäuser, Max ; Pfannemüller, Martin ; Rizk, Amr ; Schürr, Andy ; Steinmetz, Ralf (2019):
Transitions: A Protocol-Independent View of the Future Internet.
In: Proceedings of the IEEE, S. 835-846, 107, (4), ISSN 0018-9219,
DOI: 10.1109/JPROC.2019.2895964,
[Article]

Falk, J. ; Bronstein, L. ; Hanst, M. ; Drossel, B. ; Koeppl, H. (2019):
Context in Synthetic Biology: Memory Effets of Environments with Mono-molecular Reactions.
In: The Journal of Chemical Physics, American Institute of Physics, 150, (2), ISSN 0021-9606,
DOI: 10.1063/1.5053816,
[Online-Edition: https://aip.scitation.org/doi/10.1063/1.5053816],
[Article]

Alt, Bastian ; Ballard, Trevor ; Steinmetz, Ralf ; Koeppl, Heinz ; Rizk, Amr (2019):
CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming.
In: Proc. of IEEE \textbfINFOCOM - accepted full paper, [Konferenzveröffentlichung]

Hüttenrauch, M. ; Šošić, A. ; Neumann, G. (2019):
Deep Reinforcement Learning for Swarm Systems.
In: Journal of Machine Learning Research, S. 1-31, 20, (54), [Online-Edition: http://jmlr.csail.mit.edu/papers/volume20/18-476/18-476.pdf],
[Article]

2018

Linzner, D. ; Koeppl, H. (2018):
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
In: 32. Conference on Neural Information Processing Systems, Montreal, Canada, December 3-8, 2018, [Konferenzveröffentlichung]

Hofmann, Anja ; Falk, Johannes ; Prangemeier, Tim ; Happel, Dominic ; Köber, Adrian ; Christmann, Andreas ; Koeppl, Heinz ; Kolmar, Harald (2018):
A tightly regulated and adjustable CRISPR-dCas9 based AND gate in yeast.
In: Nucleic Acids Research, Oxford Academic, S. 509-520, 47, (1), ISSN 0305-1048,
DOI: 10.1093/nar/gky1191,
[Online-Edition: https://doi.org/10.1093/nar/gky1191],
[Article]

Yang, S. ; Koeppl, H. (2018):
Collapsed Variational Inference for Nonparametric Bayesian Group Factor Analysis.
In: IEEE International Conference on Data Mining (ICDM'18), Singapore, 17.-20. November 2018, [Konferenzveröffentlichung]

Al-Sayed, S. ; Koeppl, H. (2018):
Network Reconstruction from Time-Course Perturbation Data Using Multivariate Gaussian Processes.
In: IEEE International Workshop on Machine Learning for Signal Processing, In: IEEE International Workshop on Machine Learning for Signal Processing, Aalborg, Denmark, 17.-20. September 2018, [Online-Edition: https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?filter=i...],
[Konferenzveröffentlichung]

Sulaimanov, N. ; Koeppl, H. ; Burdet, F. ; Ibberson, M. ; Pagni, M. ; Kumar, S. (2018):
Inferring gene expression networks with hubs using a degree weighted Lasso approach.
In: Bioinformatics (Oxford, England), Oxford University Press, bty716, ISSN 1367-4803,
DOI: 10.1093/bioinformatics/bty716,
[Online-Edition: https://academic.oup.com/bioinformatics/advance-article/doi/...],
[Article]

Kruk, N. ; Koeppl, H. ; Maistrenko, Y. (2018):
Self-propelled Chimeras.
In: Physical Review E, American Physical Society, ISSN 2470-0045,
[Article]

Yang, S. ; Koeppl, H. (2018):
Dependent Relational Gamma Process Models for Longitudinal Networks.
In: Proceedings of Machine Learning Research (PMLR), In: Thirty-fifth International Conference on Machine Learning, Stockholm, Denmark, July 10-15, 2018, 80, [Online-Edition: https://icml.cc/Conferences/2018/Schedule?showEvent=1942],
[Konferenzveröffentlichung]

Bronstein, L. ; Koeppl, H. (2018):
Marginal process framework: A model reduction tool for Markov jump processes.
In: Physical Review E, American Physical Society, E 97, 062147, ISSN 2470-0045,
DOI: 10.1103/PhysRevE.97.062147,
[Online-Edition: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.97.06...],
[Article]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2018):
A Bayesian Approach to Policy Recognition and State Representation Learning.
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, S. 1295-1308, 40, (6), DOI: 10.1109/TPAMI.2017.2711024,
[Online-Edition: https://doi.org/10.1109/TPAMI.2017.2711024],
[Article]

Alt, Bastian ; Messer, Michael ; Roeper, Jochen ; Schneider, Gaby ; Koeppl, Heinz (2018):
Non-Parametric Bayesian Inference for Change Point Detection in Neural Spike Trains.
Freiburg im Breisgau, Germany, In: 2018 IEEE Statistical Signal Processing Workshop (SSP) (SSP 2018), Freiburg im Breisgau, Germany, [Konferenzveröffentlichung]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2018):
Reinforcement Learning in a Continuum of Agents.
In: Swarm Intelligence, S. 23-51, 12, (1), DOI: 10.1007/s11721-017-0142-9,
[Online-Edition: http://rdcu.be/wKay],
[Article]

Al-Sayed, S. ; Plata-Chaves, J ; Muma, M. ; Moonen, M. ; Zoubir, A. M. (2018):
Node-Specific Diffusion LMS-Based Distributed Detection Over Adaptive Networks.
In: IEEE Transactions on Signal Processing, S. 682-697, 66, (3), ISSN 1053-587X,
[Online-Edition: https:/doi.org/10.1109/TSP.2017.2771731],
[Article]

Bronstein, L. ; Koeppl, H. (2018):
A variational approach to moment-closure approximations for the kinetics of biomolecular reaction networks.
In: The Journal of Chemical Physics, American Institute of Physics (AIP), 148, (1), ISSN 00219606,
DOI: 10.1063/1.5003892,
[Online-Edition: http://aip.scitation.org/doi/10.1063/1.5003892],
[Article]

KhudaBukhsh, Wasiur R. ; Alt, Bastian ; Kar, Sounak ; Rizk, Amr ; Koeppl, Heinz (2018):
Collaborative Uploading in Heterogeneous Networks: Optimal and Adaptive Strategies.
IEEE, In: IEEE International Conference on Computer Communications (INFOCOM), [Konferenzveröffentlichung]

KhudaBukhsh, Wasiur Rahman (2018):
Model reductions for queueing and agent-based systems with applications in communication networks.
Darmstadt, Technische Universität, [Online-Edition: http://tuprints.ulb.tu-darmstadt.de/7588],
[PhD thesis]

Yang, S. ; Koeppl, H. (2018):
A Poisson Gamma Probabilistic Model for Latent Node-group Memberships in Dynamic Networks.
In: AAAI 2018, Association for the Advancement of Artificial Intelligence, New Orleans, 2018, [Konferenzveröffentlichung]

Šošić, A. ; Rueckert, E. ; Peters, J. ; Zoubir, A. M. ; Koeppl, H. (2018):
Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling.
In: Journal of Machine Learning Research, S. 1-45, 19, (69), [Online-Edition: http://www.jmlr.org/papers/volume19/18-113/18-113.pdf],
[Article]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2018):
Inverse Reinforcement Learning via Nonparametric Subgoal Modeling.
In: AAAI Spring Symposium on Data-Efficient Reinforcement Learning, [Online-Edition: https://aaai.org/ocs/index.php/SSS/SSS18/paper/view/17531/15...],
[Konferenzveröffentlichung]

2017

Al-Sayed, S. ; Zoubir, A. M. ; Sayed, A. H. (2017):
Robust Distributed Estimation by Networked Agents.
In: IEEE Transactions on Signal Processing, S. 3909-3921, 65, (15), ISSN 1941-0476,
[Article]

KhudaBukhsh, W. R. ; Rizk, A. ; Froemmgen, A. ; Koeppl, H. (2017):
Optimizing Stochastic Scheduling in Fork-Join Queueing Models: Bounds and Applications.
In: Technical Program of IEEE INFOCOM 2017, IEEE, [Online-Edition: https://arxiv.org/abs/1612.05486],
[Article]

Ruess, J. ; Koeppl, H. ; Zechner, C. (2017):
Sensitivity estimation for stochastic models of biochemical reaction networks in the presence of extrinsic variability.
In: The Journal of Chemical Physics, AIP, 146, (124122), [Online-Edition: http://aip.scitation.org/doi/10.1063/1.4978940],
[Article]

Machkour, J. ; Alt, B. ; Muma, M. ; Zoubir, A. M. (2017):
The Outlier-Corrected-Data-Adaptive Lasso: A New Robust Estimator for the Independent Contamination Model.
In: European Signal Processing Conference 2017 (EUSIPCO 2017), [Online-Edition: http://ieeexplore.ieee.org/document/8081489/],
[Konferenzveröffentlichung]

Bronstein, L. ; Diemer, J. ; Koeppl, H. ; Schneider, C. ; Suess, Beatrix (2017):
ROC'n'Ribo: Characterizing a riboswitching expression system by modeling single-cell data.
In: ACS Synthetic Biology, ACS, S. 1211-1224, (7), ISSN 2161-5063,
[Online-Edition: http://pubs.acs.org/doi/10.1021/acssynbio.6b00322],
[Article]

Sulaimanov, N. ; Klose, M. ; Busch, H. ; Boerries, M. (2017):
Understanding the mTOR signaling pathway via mathematical modeling.
In: WIREs Systems Biology and Medicine, Wiley, (1379), [Online-Edition: http://onlinelibrary.wiley.com/doi/10.1002/wsbm.1379/full],
[Article]

Šošić, A. ; KhudaBukhsh, W. R. ; Zoubir, A. M. ; Koeppl, H. (2017):
Inverse Reinforcement Learning in Swarm Systems.
In: AAMAS Workshop on Transfer in Reinforcement Learning, [Konferenzveröffentlichung]

Šošić, A. ; KhudaBukhsh, W. R. ; Zoubir, A. M. ; Koeppl, H. (2017):
Inverse Reinforcement Learning in Swarm Systems (Best Paper Award Finalist).
In: International Conference on Autonomous Agents and Multiagent Systems, [Online-Edition: http://dl.acm.org/citation.cfm?id=3091320],
[Konferenzveröffentlichung]

2016

Bronstein, L. ; Koeppl, H. (2016):
Scalable inference using PMCMC and parallel tempering for high-throughput measurements of biomolecular reaction networks.
In: 55th IEEE Conference on Decision and Control, Las Vegas, December 2016, [Online-Edition: http://ieeexplore.ieee.org/document/7798361/#full-text-secti...],
[Konferenzveröffentlichung]

Sulaimanov, N. ; Koeppl, H. (2016):
Graph reconstruction using covariance based methods.
In: EURASIP Journal on Bioinformatics and Systems Biology, Springer, [Online-Edition: http://bsb.eurasipjournals.springeropen.com/articles/10.1186...],
[Article]

Bronstein, L. ; Koeppl, H. (2016):
A Diagram Technique for cumulant equations in biomolecular reaction networks with mass-action kinetics.
In: 55th IEEE Conference on Decision and Control, Las Vegas, USA, December 2016, [Online-Edition: http://ieeexplore.ieee.org/document/7799170/?part=1],
[Konferenzveröffentlichung]

Ganguly, A. ; Altintan, D. ; Koeppl, H. (2016):
Efficient Simulation of Multiscale Reaction.
In: American Control Conference, Boston, Juli 2016, [Konferenzveröffentlichung]

Hill, S. M. ; Heiser, L. M. ; Cokalaer, T. ; Unger, M. ; Nesser, N. K. ; Carlin, D. E. ; Zhang, Y. ; Sokolov, A. ; Paull, E. O. ; Wong, C. K. ; Graim, K. ; Bivol, A. ; Wang, H. ; Zhu, F. ; Afsari, B. ; Danilova, L. V. ; Favorov, A. V. ; Lee, W. S. ; Taylor, D. ; Hu, C. W. ; Long, B. L. ; Noren, D. P. ; Bisberg, A. J. ; Mills, G. B. ; Gray, J. W. ; Kellen, M. ; Norman, T. ; Friend, S. ; Qutub, A. A. ; Fertig, E. J. ; Guan, Y. ; Song, M. ; Stuart, J. M. ; Spellman, P. T. ; Koeppl, H. ; Stolovitzky, G. ; Saez-Rodriguez, J. ; Mukherjee, S. (2016):
Interferring causal molecular networks: empirical assessment through a community-based effort.
In: Nature methods, Nature Publishing Group, [Online-Edition: http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth...],
[Article]

Studer, L. ; Paulevé, L. ; Zechner, C. ; Reumann, M. ; Rodriguez Martinez, M. ; Koeppl, H. (2016):
Marginalized Continuous Time Bayesian Networks for Network Reconstruction from Incomplete Observations.
Phoenix, USA, In: AAAI, Association for the Advancement of Artificial Intelligence, Phoenix, USA, 12.-17.02.2016, [Online-Edition: http://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/123...],
[Konferenzveröffentlichung]

Huang, L. ; Hansen, A. S. ; Pauleve, L. ; Unger, M. ; Zechner, C. ; Koeppl, H. (2016):
Reconstructing dynamic molecular states from single-cell time series.
In: Journal of The Royal Society Interface, Royal Society Publishing, ISSN 1742-5689,
[Online-Edition: http://rsif.royalsocietypublishing.org/content/13/122/201605...],
[Article]

KhudaBukhsh, W. R. ; Rueckert, J. ; Wulfheide, J. ; Hausheer, D. ; Koeppl, H. (2016):
Analysing and Leveraging Client Heterogeneity in Swarming-based Live Streaming.
In: IFIP International Conference on Networking (NETWORKING), In: IFIP International Conference on Networking, Wien, Austria, Mai 2016, [Online-Edition: http://dl.ifip.org/db/conf/networking/networking2016/1570236...],
[Konferenzveröffentlichung]

Richerzhagen, B. ; Wulfheide, J. ; Koeppl, H. ; Mauthe, A. U. ; Nahrstedt, K. ; Steinmetz, R. (2016):
Enabling Crowdsourced Live Event Coverage with Adaptive Collaborative Upload Strategies.
In: 2016 IEEE 17th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM), Coimbra, Portugal, [Konferenzveröffentlichung]

Sutter, T. ; Ganguly, A. ; Koeppl, H. (2016):
A variational approach to path estimation and parameter inference of hidden diffusion processes.
In: Journal of Machine Learning Research, [Online-Edition: http://jmlr.org/papers/v17/16-075.html],
[Article]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2016):
Policy Recognition via Expectation Maximization.
In: IEEE International Conference on Acoustics, Speech and Signal Processing, DOI: 10.1109/ICASSP.2016.7472589,
[Online-Edition: https://doi.org/10.1109/icassp.2016.7472589],
[Konferenzveröffentlichung]

2015

Hegemann, B. ; Unger, M. ; Lee, S. S. ; Stoffel-Studer, I. ; van den Heuvel, J. ; Pelet, S. ; Koeppl, H. ; Peter, M. (2015):
A Cellular System for Spatial Signal Decoding in Chemical Gradients.
In: Developmental Cell, Elsevier, S. 458-470, 35, (4), [Online-Edition: http://www.cell.com/developmental-cell/fulltext/S1534-5807%2...],
[Article]

Huang, L. ; Hjalmarsson, H. ; Koeppl, H. (2015):
Almost sure stability and stabilization of discrete-time stochastic systems.
In: Systems & Control Letters, S. 26-32, 82, [Online-Edition: http://www.sciencedirect.com/science/article/pii/S0167691115...],
[Article]

Altintan, D. ; Ganguly, A. ; Koeppl, H. (2015):
Error bound and simulation algorithm for piecewise deterministic approximations of stochastic reaction systems.
In: American Control Conference (ACC), 2015, In: American Control Conference (ACC), 2015, Chicago, 1-3 July 2015, [Online-Edition: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7170830],
[Konferenzveröffentlichung]

Bronstein, L. ; Zechner, C. ; Koeppl, H. (2015):
Bayesian inference of reaction kinetics from single-cell recordings across a heterogeneous cell population.
In: ScienceDirect - Methods, Elsevier, [Online-Edition: http://www.sciencedirect.com/science/journal/aip/10462023],
[Article]

KhudaBukhsh, W. R. ; Rueckert, J. ; Wulfheide, J. ; Hausheer, D. ; Koeppl, H.
KhudaBukhsh W. R. (Urheber) (2015):
A Comprehensive Analysis of Swarming-based Live Streaming to Leverage Client Heterogenieity.
Darmstadt, Technische Universität Darmstadt, In: Technical Report, [Online-Edition: http://www.bcs.tu-darmstadt.de/biocomm/people_1/phdstudents/...],
[Report]

Altintan, D. ; Ganguly, A. ; Koeppl, H. (2015):
Jump-Diffusion Approximation of Stochastic Reaction Dynamics: Error bounds and Algorithms.
In: SIAM Multiscale Modeling and Simulation, SIAM (Society for Industrial and Applied Mathematics), ISSN 1540-3459,
[Online-Edition: http://arxiv.org/abs/1409.4303],
[Article]

2014

Koeppl, H. ; Zechner, C. (2014):
Uncoupled analysis of stochastic reaction networks in fluctuating environments.
In: PLOS Computational Biology, Cornell University, 10, (12), ISSN 1476-928X,
[Online-Edition: http://journals.plos.org/ploscompbiol/article?id=10.1371/jou...],
[Article]

Koeppl, H. ; Hafner, M. ; Lu, J. (2014):
From Specification to Parameters: A Linearization Approach.
In: A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems, Netherlands, Springer, S. 245-256, [Online-Edition: http://link.springer.com/chapter/10.1007/978-94-017-9047-5_1...],
[Book section]

Zechner, C. ; Unger, M. ; Pelet, S. ; Peter, M. ; Koeppl, H. (2014):
Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings.
In: Nature methods, S. 197-202, 11, (2), [Online-Edition: http://www.nature.com/nmeth/journal/v11/n2/full/nmeth.2794.h...],
[Article]

Zechner, C. ; Wadehn, F. ; Koeppl, H. (2014):
Sparse learning of Markovian population models in random environments.
Cornell, In: IFAC 2014, The 19th World Congress of the International Federation of Automatic Control, Promoting automatic control for the benefit of humankind, Cape Town, South Africa, 24-29 August 2014, [Online-Edition: http://arxiv.org/abs/1401.4026],
[Konferenzveröffentlichung]

Geiger, B. C. ; Petrov, T. ; Kubin, G. ; Koeppl, H. (2014):
Optimal Kullback-Leibler Aggregation via Information Bottleneck.
In: IEEE Transactions on Automatic Control, IEEE, ISSN 0018-9286,
[Online-Edition: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6...],
[Article]

2013

Ganguly, A. ; Petrov, T. ; Koeppl, H. (2013):
Markov chain aggregation and its applications to combinatorial reaction networks.
In: Journal of mathematical biology, S. 767-797, 69, (3), [Online-Edition: http://link.springer.com/article/10.1007/s00285-013-0738-7],
[Article]

Tarca, A. L. ; Lauria, M. ; Unger, M. ; Bilal, E. ; Boue, S. ; Kumar Dey, K. ; Hoeng, J. ; Koeppl, H. ; Martin, F. ; Meyer, P. ; Nandy, P. ; Norel, R. ; Peitsch, M. ; Rice, J. ; Romero, R. ; Stolovitzky, G. ; Talikka, M. ; Xiang, Y. ; Zechner, C. (2013):
Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge.
In: Bioinformatics (Oxford, England), S. 2892-2899, 29, (22), [Online-Edition: http://www.ncbi.nlm.nih.gov/pubmed/23966112],
[Article]

de Heras Ciechomski, P. ; Klann, M. ; Mange, R. ; Koeppl, H. (2013):
From biochemical reaction networks to 3D dynamics in the cell: The ZigCell3D modeling, simulation and visualisation framework.
In: IEEE Symposium on Biological Data Visualization (BioVis), IEEE, S. 41-48, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Article]

Klann, M. ; Koeppl, H. (2013):
Reaction schemes, escape times and geminate recombinations in particle-based spatial simulations of biochemical reactions.
In: Physical biology, S. 046005, 10, (4), [Online-Edition: http://iopscience.iop.org/1478-3975/10/4/046005/article],
[Article]

Lu, J. ; August, E. ; Koeppl, H. (2013):
Inverse problems from biomedicine : Inference of putative disease mechanisms and robust therapeutic strategies.
In: Journal of mathematical biology, Springer Verlag, S. 143-168, 67, (1), ISSN 0303-6812,
[Online-Edition: http://link.springer.com/article/10.1007/s00285-012-0523-z],
[Article]

Paulevé, L. ; Craciun, G. ; Koeppl, H. (2013):
Dynamical properties of Discrete Reaction Networks.
In: Journal of mathematical biology, [Online-Edition: http://arxiv.org/abs/1302.3363],
[Article]

Nandy, P. ; Unger, M. ; Zechner, C. ; Dey, K. ; Koeppl, H. (2013):
Learning diagnostic signatures from microarray data using Ll-regularized logistic regression.
In: Systems Biomedicine, Taylor & Francis, 1, (4), [Online-Edition: http://www.tandfonline.com/doi/full/10.4161/sysb.25271?mobil...],
[Article]

Feret, J. ; Koeppl, H. ; Petrov, T. (2013):
Stochastic fragments: A framework for the exact reduction of the stochastic semantics of rule-based models.
In: International Journal of Software and Informatics, S. 527-604, 7, (4), [Online-Edition: http://www.ijsi.org/ch/reader/view_abstract.aspx?file_no=i17...],
[Article]

Klann, M. ; Paulevé, L. ; Petrov, T. ; Koeppl, H. (2013):
Coarse-Grained Brownian Dynamics Simulation of Rule-Based Models.
Springer Berlin Heidelberg, In: 11th International Conference on Computational Methods in Systems Biology (CMSB 2013), 8130, [Online-Edition: http://link.springer.com/chapter/10.1007/978-3-642-40708-6_6...],
[Konferenzveröffentlichung]

Koeppl, H. ; Hafner, M. ; Lu, J. (2013):
Mapping behavioral specifications to model parameters in synthetic biology.
In: BMC Bioinformatics, S. S9, 14, [Online-Edition: http://www.biomedcentral.com/1471-2105/14/S10/S9],
[Article]

Koeppl, H. ; Petrov, T. (2013):
Approximate model reductions for combinatorial reaction systems; European Control Conferenc (ECC 2013).
In: European Control Conferenc (ECC 2013), Zuerich, 17-19 July 2013, [Online-Edition: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6669734...],
[Konferenzveröffentlichung]

Paulevé, L. ; Andrieux, G. ; Koeppl, H. (2013):
Under-approximating cut sets for reachability in large scale automata Networks.
Springer, In: 25th International Conference on Computer Aided Verification (CAV 2013), 8044, [Online-Edition: http://link.springer.com/chapter/10.1007%2F978-3-642-39799-8...],
[Konferenzveröffentlichung]

Zechner, C. ; Deb, S. ; Koeppl, H. (2013):
Marginal dynamics of stochastic biochemical networks in random environments.
IEEE, In: 2013 European Control Conference (ECC), Zürich, 2013, [Online-Edition: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6669606],
[Konferenzveröffentlichung]

2012

August, E. ; Craciun, G. ; Koeppl, H. (2012):
Finding invariant sets for biological systems using monomial domination.
Maui, HI, USA, IEEE, In: 51st IEEE Conference on Decision and Control (CDC), 2012, 2012, [Online-Edition: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6...],
[Konferenzveröffentlichung]

August, E. ; Koeppl, H. (2012):
Computing enclosures for uncertain biochemical systems.
In: IET Systems Biology, S. 232-240, 6, (6), [Online-Edition: http://digital-library.theiet.org/content/journals/10.1049/i...],
[Article]

Petrov, T. ; Feret, J. ; Koeppl, H. (2012):
Reconstructing species-based dynamics from reduced stochastic rule-based models.
In: Proceedings of the 2012 Winter Simulation Conference, Winter Simulation Conference, S. 225, [Online-Edition: http://dl.acm.org/citation.cfm?id=2429759.2430062],
[Article]

Zechner, C. ; Nandy, P. ; Unger, M. ; Koeppl, H. (2012):
Optimal variational perturbations for the inference of stochastic reaction dynamics.
IEEE, In: 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Konferenzveröffentlichung]

Klann, M. ; Ganguly, A. ; Koeppl, H. (2012):
Hybrid spatial Gillespie and particle tracking simulation.
In: Bioinformatics (Oxford, England), S. i549, 28, (18), [Online-Edition: http://bioinformatics.oxfordjournals.org/content/28/18/i549....],
[Article]

Koeppl, H. ; Zechner, C. ; Ganguly, A. ; Pelet, S. ; Peter, M. (2012):
Accounting for extrinsic variability in the estimation of stochastic rate constants.
In: International Journal of Robust and Nonlinear Control, Wiley-Blackwell, S. 1103-1119, 22, (10), [Online-Edition: http://doi.wiley.com/10.1002/rnc.2804],
[Article]

Nandy, P. ; Unger, M. ; Zechner, C. ; Koeppl, H. (2012):
Optimal Perturbations for the Identification of Stochastic Reaction Dynamics.
Elsevier, In: 16th IFAC Symposium on System Identification, [Online-Edition: http://www.ifac-papersonline.net/Detailed/54661.html],
[Konferenzveröffentlichung]

Petrov, T. ; Ganguly, A. ; Koeppl, H. (2012):
Model Decomposition and Stochastic Fragments.
In: Electronic Notes in Theoretical Computer Science, S. 105-124, 284, [Online-Edition: http://linkinghub.elsevier.com/retrieve/pii/S157106611200019...],
[Article]

Pantea, C. ; Koeppl, H. ; Craciun, G. (2012):
Global injectivity and multiple equilibria in uni- and bi-molecular reaction networks.
In: Discrete and Continuous Dynamical Systems - Series B, American Institute of Mathematical Sciences, S. 2153-2170, 17, (6), [Online-Edition: https://aimsciences.org/journals/displayArticlesnew.jsp?pape...],
[Article]

Zechner, C. ; Ruess, J. ; Krenn, P. ; Pelet, S. ; Peter, M. ; Lygeros, J. ; Koeppl, H. (2012):
Moment-based inference predicts bimodality in transient gene expression.
In: Proceedings of the National Academy of Sciences of the United States of America, S. 8340-8345, 109, (21), [Online-Edition: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3361437/?tool=pm...],
[Article]

Feret, J. ; Henzinger, T. ; Koeppl, H. ; Petrov, T. (2012):
Lumpability Abstractions of Rule-based Systems.
In: Journal of Theoretical Comuter Science, S. 137-164, 431, [Online-Edition: http://linkinghub.elsevier.com/retrieve/pii/S030439751101025...],
[Article]

Hafner, M. ; Koeppl, H. ; Gonze, D. (2012):
Effect of network architecture on synchronization and entrainment properties of the circadian oscillations in the suprachiasmatic nucleus.
In: PLoS computational biology, S. e1002419, 8, (3), [Online-Edition: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3297560/?tool=pm...],
[Article]

Hiroi, N. ; Klann, M. ; Iba, K. ; de Heras Ciechomski, P. ; Yamashita, S. ; Tabira, A. ; Okuhara, T. ; Kubojima, T. ; Okada, Y. ; Oka, K. ; Mange, R. ; Unger, M. ; Funahashi, A. ; Koeppl, H. (2012):
From microscopy data to in silico environments for in vivo-oriented simulations.
In: EURASIP Journal on Bioinformatics and Systems Biology, S. 7, 2012, (1), [Online-Edition: http://bsb.eurasipjournals.com/CONTENT/2012/1/7],
[Article]

Klann, M. ; Koeppl, H. (2012):
Spatial simulations in systems biology: from molecules to cells.
In: International journal of molecular sciences, S. 7798-7827, 13, (6), [Online-Edition: http://www.mdpi.com/1422-0067/13/6/7798],
[Article]

Klann, M. ; Koeppl, H. ; Reuss, M. (2012):
Spatial modeling of vesicle transport and the cytoskeleton: the challenge of hitting the right road.
In: PloS one, S. e29645, 7, (1), [Online-Edition: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjourna...],
[Article]

August, E. ; Lu, J. ; Koeppl, H. (2012):
Trajectory enclosures for systems with uncertainties in initial conditions and parameter values.
Fairmont Queen Elizabeth, Montreal, Canada, In: 2012 American Control Conference, Fairmont Queen Elizabeth, Montreal, Canada, 2012, [Online-Edition: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6314741...],
[Konferenzveröffentlichung]

Klann, M. ; Koeppl, H. (2012):
Spatial stochastic simulation of transcription factor binding reveals mechaniscms to control gene activation.
Tampere University of Technology, Tampere International Center for Signal Processing, In: 9th International Workshop on Computational Systems Biology (WCSB 2012), 61, [Online-Edition: http://www.cs.tut.fi/wcsb12/WCSB2012.pdf],
[Konferenzveröffentlichung]

Koeppl, H. ; Petrov, T. (2012):
Reductions of stochastic rule-based models: HOG pathway in yeast.
In: ICSB : The 13th International Conference on Systems Biology, [Online-Edition: http://abstracts.genetics-gsa.org/2012/icsb/book_ICSB_final....],
[Konferenzveröffentlichung]

2011

Zechner, C. ; Pelet, S. ; Peter, M. ; Koeppl, H. (2011):
Recursive Bayesian estimation of stochastic rate constants from heterogeneous cell populations.
In: IEEE Conference on Decision and Control and European Control Conference, IEEE, S. 5837-5843, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Article]

Koeppl, H. ; Hafner, M. ; Ganguly, A. ; Mehrotra, A. (2011):
Deterministic characterization of phase noise in biomolecular oscillators.
In: Physical biology, S. 55008, 8, (5), [Online-Edition: http://iopscience.iop.org/1478-3975/8/5/055008/fulltext/],
[Article]

Meyer, P. ; Alexopoulos, L. G. ; Bonk, T. ; Califano, A. ; Cho, C. R. ; de la Fuente, A. ; de Graaf, D. ; Hartemink, A. J. ; Hoeng, J. ; Ivanov, N. V. ; Koeppl, H. ; Linding, R. ; Marbach, D. ; Norel, R. ; Peitsch, M. C. ; Rice, J. J. ; Royyuru, A. ; Schacherer, F. ; Sprengel, J. ; Stolle, K. ; Vitkup, D. ; Stolovitzky, G. (2011):
Verification of systems biology research in the age of collaborative competition.
In: Nature biotechnology, S. 811-815, 29, (9), [Online-Edition: http://www.nature.com/nbt/journal/v29/n9/abs/nbt.1968.html],
[Article]

Koeppl, H. ; Petrov, T. (2011):
Stochastic Semantics of Signaling as a Composition of Agent-view Automata.
In: Electronic Notes in Theoretical Computer Science, S. 3-17, 272, [Online-Edition: http://linkinghub.elsevier.com/retrieve/pii/S157106611100069...],
[Article]

August, E. ; Wang, Y. ; Doyle, F. J. ; Lu, J. ; Koeppl, H. (2011):
Computationally implementable sufficient conditions for the synchronisation of coupled dynamical systems with time delays in the coupling.
San Francisco, CA, USA, IEEE, In: Proceedings of the 2011 American Control Conference, [Online-Edition: http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=599073...],
[Konferenzveröffentlichung]

Danos, V. ; Koeppl, H. ; Wilson-Kanamori, J. (2011):
Cooperative assembly systems.
In: DNA Computing and Molecular Programming, S. 1-21, [Online-Edition: http://link.springer.com/chapter/10.1007/978-3-642-23638-9_1],
[Article]

Falk, M. ; Ott, M. ; Ertl, T. ; Klann, M. ; Koeppl, H. (2011):
Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology Categories and Subject Descriptors.
In: CMSB '11 Proceedings of the 9th International Conference on Computational Methods in Systems Biology, New York, New York, USA, ACM Press, [Online-Edition: http://dl.acm.org/citation.cfm?doid=2037509.2037521],
[Konferenzveröffentlichung]

Hafner, M. ; Koeppl, H. (2011):
Stochastic Simulations in Systems Biology.
In: Handbook of Research on Computational Science and Engineering: Theory and Practice, IGI Global, S. 267-286, [Online-Edition: http://www.igi-global.com/chapter/handbook-research-computat...],
[Book section]

Hafner, M. ; Lu, J. ; Petrov, T. ; Koeppl, H. (2011):
Rational design of robust biomolecular circuits: From specification to parameters.
In: Analysis and Design of Biomolecular Circuits, New York, NY, Springer, S. 253-281, [Online-Edition: http://link.springer.com/chapter/10.1007/978-1-4419-6766-4_1...],
[Book section]

Klann, M. ; Ganguly, A. ; Koeppl, H. (2011):
Improved Reaction Scheme for Spatial Stochastic Simulations with Single Molecule Detail.
Tampere, Tampere University of Technology, In: Eighth International Workshop on Computational Systems Biology (WCSB 2011), 57, [Online-Edition: http://www.wcsb2011.ethz.ch/programme],
[Konferenzveröffentlichung]

Koeppl, H. ; Andreozzi, S. ; Steuer, R. (2011):
Guaranteed and Randomized Methods for Stability Analysis of Uncertain Metabolic Networks.
In: Lecture notes in control and information sciences, Springer, S. 297-309, 407, [Online-Edition: http://link.springer.com/chapter/10.1007/978-3-642-16135-3_2...],
[Article]

Lu, J. ; Grass, P. ; Koeppl, H. (2011):
Computational identification of optimal multi target drug intervention strategies for combination theory.
Zurich, In: Eighth International Workshop on Computational Systems Biology, WCSB 2011, June 6-8, 2011, Zurich, Switzerland, [Online-Edition: http://www.wcsb2011.ethz.ch/programme],
[Konferenzveröffentlichung]

Unger, M. ; Lee, S.-S. ; Peter, M. ; Koeppl, H. (2011):
Pulse Width Modulation of Liquid Flows.
San Diego, CA, Chemical and Biological Microsystems Society, In: 15th International Conference on Miniaturized Systems for Chemistry and Life Sciences, [Online-Edition: http://e-citations.ethbib.ethz.ch/view/pub:68788],
[Konferenzveröffentlichung]

2010

Camporesi, F. ; Feret, J. ; Koeppl, H. ; Petrov, T. (2010):
Combining Model Reductions.
In: Electronic Notes in Theoretical Computer Science, S. 73-96, 265, [Online-Edition: http://linkinghub.elsevier.com/retrieve/pii/S157106611000085...],
[Article]

Koeppl, H. ; Setti, G. ; Pelet, S. ; Mangia, M. ; Petrov, T. ; Peter, M. (2010):
Probability metrics to calibrate stochastic chemical kinetics.
In: Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on, [Article]

Petrov, T. ; Koeppl, H. (2010):
Maximal reduction of deterministic semantics of rule-based models - Google-Suche.
In: Proceedings of the International Workshop on computational Systems Biology (WCSB) in 2010, [Online-Edition: https://www.google.de/?gfe\_rd=ctrl\&ei=l3o6U7aXG\_Da8geKzYC...],
[Konferenzveröffentlichung]

2009

Hafner, M. ; Koeppl, H. ; Hasler, M. ; Wagner, A. (2009):
'Glocal' robustness analysis and model discrimination for circadian oscillators.
In: PLoS Computational Biology, S. e1000534, 5, (10), [Online-Edition: http://journals.plos.org/ploscompbiol/article?id=10.1371/jou...],
[Article]

Koeppl, H. ; Setti, G. (2009):
Analysis and design of biological circuits and systems.
Taipeh, Taiwan, IEEE, In: 2009 IEEE International Symposium on Circuits and Systems, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Konferenzveröffentlichung]

Rodrigues, A. ; Koeppl, H. ; Ohtsuki, H. ; Satake, A. (2009):
A Game Theoretical Model of deforestation in human-environment relationships.
In: Journal of Theoretical Biology, S. 127-134, 258, (1), [Online-Edition: http://www.sciencedirect.com/science/article/pii/S0022519309...],
[Article]

Koeppl, H. (2009):
A Local Nonlinear Model for the Approximation and Identification of a Class of Systems.
In: IEEE Transactions on Circuits and Systems II: Express Briefs, S. 315-319, 56, (4), [Online-Edition: http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=4801647],
[Article]

Hafner, M. ; Koeppl, H. ; Wagner, A. (2009):
Robustness and evolution in oscillatory systems with feedback loops.
Denver, USA, IEEE, In: Proc. of the Third IEEE International Conference on Foundations of Systems Biology in Engineering (FOSBE), [Online-Edition: http://infoscience.epfl.ch/record/130922?ln=en http://arxiv....],
[Konferenzveröffentlichung]

Parisi, F. ; Koeppl, H. ; Naef, F. (2009):
Network inference by combining biologically motivated regulatory constraints with penalized regression.
In: Annals of the New York Academy of Sciences, S. 114-124, 1158, [Online-Edition: http://onlinelibrary.wiley.com/doi/10.1111/j.1749-6632.2008....],
[Article]

Hafner, M. ; Danos, V. ; Koeppl, H. (2009):
Rule-based modeling for protein-protein interaction networks - the Cyanobacterial circadian clock as a case studyproceedings.
Aarhus, Denmark, In: Proceedings of the International Workshop on Computational Systems Biology (WCSB), [Online-Edition: http://citeseerx.ist.psu.edu/viewdoc/summary;jsessionid=D87D...],
[Konferenzveröffentlichung]

Koeppl, H. ; Haeusler, S. (2009):
Motifs, algebraic connectivity and computational performance of two data- based cortical circuit templates.
In: Proceedings of the sixth International Workshop on Computational Systems Biology, S. 83-86, [Online-Edition: http://infoscience.epfl.ch/record/131569?ln=en],
[Article]

Koeppl, H. ; Hafner, M. ; Steuer, R. (2009):
Semi-quantitative stability analysis constrains saturation levels in metabolic networks.
Aarhus, Denmark, In: Proceedings of the Intenational Workshop on Computational Systems Biology (WCSB), [Online-Edition: http://65.54.113.26/Publication/5234529],
[Konferenzveröffentlichung]

Koeppl, H. ; Schumacher, L. ; Danos, V. (2009):
A Statistical analysis of receptor.
Aarhus, Denmark, In: Proceedings of the International Workshop on Computtional Systmes Biology (WCSB), [Konferenzveröffentlichung]

2008

Krall, C. ; Witrisal, K. ; Leus, G. ; Koeppl, H. (2008):
Minimum Mean-Square Error Equalization for Second-Order Volterra Systems.
In: IEEE Transactions on Signal Processing, IEEE, S. 4729-4737, 56, (10), [Online-Edition: http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=4558047],
[Article]

Murmann, B. ; Vogel, C. ; Koeppl, H. (2008):
Digitally enhanced analog circuits: System aspects.
IEEE, In: 2008 IEEE International Symposium on Circuits and Systems, [Online-Edition: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4541479...],
[Konferenzveröffentlichung]

2007

Singerl, P. ; Koeppl, H. (2007):
A Low-rate identification method for digital predistorters based on Volterra kernel interpolation.
In: Analog Integrated Circuits and Signal Processing, Springer, S. 107-115, 56, (1-2), [Online-Edition: http://link.springer.com/article/10.1007/s10470-007-9074-4/f...],
[Article]

Koeppl, H. (2007):
The Composition Rule for Multivariate Volterra Operators and its Application to Circuit Analysis.
IEEE, In: 2007 IEEE International Symposium on Circuits and Systems, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Konferenzveröffentlichung]

Huang, C.-H. ; Koeppl, H. (2007):
A Bio-inspired Computer Fovea Model based on hexagonal-type cellular neural networks.
In: IEEE Transactions on circuits and systems-I : regular papers, IEEE, 54, (1), [Online-Edition: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4061016],
[Article]

Koeppl, H. ; Chua, L. O. (2007):
An Adaptive Cellular Nonlinear Network and its Application.
In: Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA), pages 15–18, Sept. 16-19, 2007, Vancouver, Canada., [Online-Edition: http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=417672...],
[Article]

Wolkerstorfer, M. ; Koeppl, H. (2007):
On the Projection Dynamic for Selfish Routing.
Dresden, Germany, In: European Complex Systems Conference, [Online-Edition: http://infoscience.epfl.ch/record/112928],
[Konferenzveröffentlichung]

2006

Koeppl, H. ; Singerl, P. (2006):
An Efficient Scheme for Nonlinear Modeling and Predistortion in Mixed-Signal Systems.
In: IEEE Transactions on Circuits and Systems II: Express Briefs, S. 1368-1372, 53, (12), [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Article]

Koeppl, H. (2006):
An Adaptive Cellular Network for Subspace Extraction.
Pacific Grove, CA, USA, IEEE, In: 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, [Online-Edition: http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=417672...],
[Konferenzveröffentlichung]

Koeppl, H. (2006):
Information Rate Maximization over a Resistive Grid.
Vancouver, BC, IEEE, In: The 2006 IEEE International Joint Conference on Neural Network Proceedings, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Konferenzveröffentlichung]

2005

Singerl, P. ; Koeppl, H. (2005):
A Low-rate identification method for digital predistorters based on Volterra kernel interpolation.
In: Circuits and Systems, 2005. 48th Midwest Symposium, IEEE, S. 1533-1536, 2, [Online-Edition: http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=1594406&tag...],
[Article]

Krall, C. ; Witrisal, K. ; Koeppl, H. ; Leus, G. ; Pausini, M. (2005):
Nonlinear equalization for frame-differential IR-UWB receivers.
In: 2005 IEEE International Conference on Ultra-Wideband, IEEE, S. 576-581, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Article]

Schwingshackl, D. ; Koeppl, H. ; Kubin, G. (2005):
Exact discrete-time representation of continuous-time Volterra filters.
In: NSIP 2005. Abstracts. IEEE-Eurasip Nonlinear Signal and Image Processing, 2005., IEEE, S. 11, [Online-Edition: http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=150222...],
[Article]

Singerl, P. ; Koeppl, H. (2005):
Volterra kernel interpolation for system modeling and predistortion purposes.
IEEE, In: International Symposium on Signals, Circuits and Systems, 2005. ISSCS 2005., 1, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Konferenzveröffentlichung]

2004

Shutin, D. ; Koeppl, H. (2004):
Application of the Evidence Procedure to Linear Problems in Signal Processing.
AIP, In: AIP Conference Proceedings, 735, [Online-Edition: http://adsabs.harvard.edu/abs/2004AIPC..735..161S http://sci...],
[Konferenzveröffentlichung]

Koeppl, H. ; Josan, A. S. ; Paoli, G. ; Kubin, G. (2004):
The Cramer-Rao Bound and DMT Signal Optimisation for the Identification of a Wiener-Type Model.
In: EURASIP Journal on Applied Signal Processing, S. 1817-1830, 12, [Online-Edition: http://asp.eurasipjournals.com/content/2004/12/642938],
[Article]

Koeppl, H. (2004):
Nonlinear System Identification for Mixed Signal Processing | Signal Processing and Speech Communication Laboratory.
Graz Universitay of Technology, Graz, Austria, [Online-Edition: http://www.spsc.tugraz.at/PhD_Theses/nonlinear-system-identi...],
[PhD thesis]

Koeppl, H. ; Schwingshackl, D. (2004):
Comparison of discrete-time approximations for continuous-time nonlinear systems.
In: 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, S. ii-881, 2, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Article]

2003

Koeppl, H. ; Kubin, G. ; Paoli, G. (2003):
Bayesian methods for sparse RLS adaptive filters.
Pacific Grove, CA, USA, IEEE, In: The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, 2, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Konferenzveröffentlichung]

Koeppl, H. ; Paoli, G. ; Kubin, G. (2003):
The Cramer-Rao bound for a factorizable Volterra system.
Grado, Italy, IEEE, In: IEEE Workshop on Nonlinear Signal and Image Processing, [Konferenzveröffentlichung]

Vogel, C. ; Koeppl, H. (2003):
Behavioral Modeling of Time-Interleaved ADCs using MATLAB.
In: October, S. 45-48, [Online-Edition: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.212....],
[Article]

2002

Koeppl, H. ; Paoli, G. (2002):
Non-Linear System Identification of a Broadband Subscriber Line Interface Circuitry Using the Volterra Approach.
In: Mathematics in Signal Processing V, Oxford University Press, V, (Chapter 13), [Online-Edition: http://ukcatalogue.oup.com/product/9780198507345.do],
[Article]

Koeppl, H. ; Paoli, G. (2002):
Non-linear modeling of a broadband SLIC for ADSL-Lite-over-POTS using harmonic analysis.
Scottsdale, Arizona, USA, IEEE, In: 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353), 2, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],
[Konferenzveröffentlichung]

2001

Koeppl, H. (2001):
Identification of a non-linear analog circuitry for an ADSL application.
Karl-Franzens-Universität, Graz, Austria, [Online-Edition: http://search.obvsg.at/primo_library/libweb/action/dlDisplay...],
[Master thesis]

Paoli, G. ; Koeppl, H. (2001):
Non-linear identification and modeling of large scale analog integrated circuitties for DMT based applications.
Bratislava, Slovakia, In: Proc. of the Electronic Circuits and Systems Conference, [Online-Edition: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.9...],
[Konferenzveröffentlichung]

2000

Koeppl, H. ; Paoli, G.
The Institute of Mathematics and its Applications (IMA) (Urheber) (2000):
Non-Linear System Identification of a Broadband Subscriber Line Interface Circuit for ADSL-Lite Using the Volterra Approach.
In: 5th IMA International Conference on Mathematics in Signal Processing, Warwick, United Kingdom, [Konferenzveröffentlichung]

This list was generated on Fri Sep 20 01:54:29 2019 CEST.