Abstract—In this work, we propose a framework for supervisory cooperative estimation of multi-agent linear time-invariant (LTI) systems. We introduce a group of sub-observers, ea...
The available rendering performance on current computers increases constantly, primarily by employing parallel algorithms using the newest many-core hardware, as for example multi-...
This paper introduces the software framework MMER Lab which allows an effective assembly of modular signal processing systems optimized for memory efficiency and performance. Our...
Dynamic composition of web services is a promising approach and at the same time a challenging research area for the dissemination of serviceoriented applications. It is widely rec...
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...