Papers by Markus Borschbach
According to the common underlying mathematical model of ad hoc networks introduced, a selective ... more According to the common underlying mathematical model of ad hoc networks introduced, a selective network model is defined to analyze local node connectivity. Based on a system architecture with a predetermined number of independent and simultaneous links of each network node, the different opti- mization degrees of the selection of neighbors are presented. A higher relaying efficiency gives the main
Bookmarks Related papers MentionsView impact
The 11th IEEE International Conference on Networks, 2003. ICON2003., 2003
According to the common underlying mathematical model of ad hoc networks introduced elsewhere, a ... more According to the common underlying mathematical model of ad hoc networks introduced elsewhere, a selective network model is defined to analyze local node connectivity. Based on a system architecture with a predetermined number of independent and simultaneous links of each network node, the different optimization degrees of the selection of neighbors are presented. A higher relaying efficiency gives the main opportunity for an ad hoc net to be an essential part of a future networking system. The efficiency of a selective network connectivity is compared to pure range controlled connectivity.
Bookmarks Related papers MentionsView impact
Proceedings of the 10th annual conference on Genetic and evolutionary computation - GECCO '08, 2008
Bookmarks Related papers MentionsView impact
1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227), 1998
In this paper, a two-layer neural network is presented, which organizes itself to perform blind s... more In this paper, a two-layer neural network is presented, which organizes itself to perform blind source separation. The inputs to the network are prewhitened linear mixtures of unknown independent source signals. An unsupervised nonlinear Hebbian learning rule is used for training the network. After convergence, the network is able to extract the source signals from the mixtures, provided that the
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Various algorithms have been suggested for the Max-SAT problem. The solution for the Max-2SAT is ... more Various algorithms have been suggested for the Max-SAT problem. The solution for the Max-2SAT is the starting point for a selection of these approximation algorithms. This paper aims at introducing approaches for Max-2SAT by a brief review of the basic ideas. Moreover, a memetic algorithm for Max-2SAT problems based on a specific crossover operator and an improved tabu search stage is presented. Simulation performed on several instances of Max-2SAT reference problems are used to evaluate the different memetic algorithm strategies applied in our approach. The overall performance is verified by empirical simulation and is used to compare the developed approach to other state up-to-date and of the art algorithms.
Bookmarks Related papers MentionsView impact
International Journal on Wireless & Optical Communications, 2006
Bookmarks Related papers MentionsView impact
wseas.us
Bookmarks Related papers MentionsView impact
2007 IEEE International Conference on Signal Processing and Communications, 2007
ABSTRACT
Bookmarks Related papers MentionsView impact
International Journal of Software Engineering and Knowledge Engineering, 2003
Bookmarks Related papers MentionsView impact
Proceedings 10th IEEE International Conference on Networks (ICON 2002). Towards Network Superiority (Cat. No.02EX588), 2002
... (1) Anode E V A nodei,node, t LA ILI = I{nodei,nodej}/} From the transmission range of the no... more ... (1) Anode E V A nodei,node, t LA ILI = I{nodei,nodej}/} From the transmission range of the node model dj = distance,i,,~., the number of possible links ILI = I{nodei,nodej}/ with a formal description based on the link model L (2) can be determined. ...
Bookmarks Related papers MentionsView impact
Lecture Notes in Computer Science, 2007
ABSTRACT
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Uploads
Papers by Markus Borschbach