Steffen Limmer
Title
Cited by
Cited by
Year
Noise cancelling algorithms for FPGA-based time-domain EMI measurements in real-time
A Frech, S Limmer, P Russer
2011 IEEE International Symposium on Electromagnetic Compatibility, 484-488, 2011
92011
A simple algorithm for approximation by nomographic functions
S Limmer, J Mohammadi, S Stańczak
2015 53rd Annual Allerton Conference on Communication, Control, and …, 2015
72015
Towards optimal nonlinearities for sparse recovery using higher-order statistics
S Limmer, S Stanczak
2016 IEEE 26th International Workshop on Machine Learning for Signal …, 2016
52016
A neural architecture for bayesian compressive sensing over the simplex via laplace techniques
S Limmer, S Stańczak
IEEE Transactions on Signal Processing 66 (22), 6002-6015, 2018
42018
Distributed machine learning in the context of function computation over wireless networks
M Raceala-Motoc, S Limmer, I Bjelakovic, S Stanczak
2018 52nd Asilomar Conference on Signals, Systems, and Computers, 291-297, 2018
22018
Optimal deep neural networks for sparse recovery via Laplace techniques
S Limmer, S Stanczak
arXiv preprint arXiv:1709.01112, 2017
22017
Exploiting interference for efficient distributed computation in cluster-based wireless sensor networks
S Limmer, S Stańczak, M Goldenbaum, RLG Cavalcante
2013 IEEE Global Conference on Signal and Information Processing, 933-936, 2013
22013
On ℓp-norm computation over multiple-access channels
S Limmer, S Stańczak
2014 IEEE Information Theory Workshop (ITW 2014), 351-355, 2014
12014
A novel real-time ambient noise cancellation system for EMI measurements in time-domain
A Frech, S Limmer, P Russer
10th International Symposium on Electromagnetic Compatibility, 41-45, 2011
12011
Interpretable Control by Reinforcement Learning
D Hein, S Limmer, TA Runkler
arXiv preprint arXiv:2007.09964, 2020
2020
Distributed and Sparse Signal Processing: Architectures, Algorithms and Nonlinear Estimators
S Limmer
Technische Universität Berlin, 2019
2019
Distributed and sparse signal processing
S Limmer
2019
A Decentralized Eigenvalue Computation Method for Spectrum Sensing Based on Average Consensus
J Mohammadi, S Limmer, S Stańczak
Frequenz 70 (7-8), 309-318, 2016
2016
The system can't perform the operation now. Try again later.
Articles 1–13