Markus Borschbach - Academia.edu (original) (raw)
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
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.
Proceedings of the 10th annual conference on Genetic and evolutionary computation - GECCO '08, 2008
The solution for the Max-2SAT is the starting point for a selection of these strategies by a brie... more The solution for the Max-2SAT is the starting point for a selection of these strategies by a brief review. 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 and to compare it to the computational complexity of existing local search solutions.
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
This work outlines the incorporation of human strategies in a genetic algorithm. Human competence... more This work outlines the incorporation of human strategies in a genetic algorithm. Human competence and machine intelligence are merged creating symbiotic human-machine intelligence, which is called HuGO!, the Human strategy based Genetic Optimizer. HuGO! emerged from and is applied to the restoration problem of Rubik's Cube and successfully solves this task. A competition between HuGO! and human Rubik's Cube contestants demonstrates that the incorporated human strategies improved the genetic solver's performance to become human-competitive.
According to the common underlying mathematical model for Independent Component Analysis (ICA), t... more According to the common underlying mathematical model for Independent Component Analysis (ICA), the fulfillment of a BSS for either a linear and scalar type of composition, a convolutive and linear type or a nonlinear type has different conditions. So far, several approaches have been developed in the last decades for stationary and non-stationary data. To identify key research priorities, the different origins of neural network approaches for BSS are briefly reviewed and divided by classes of specific theoretical and application features. A principal guideline for the design of reference data sets for the comparison of all the existing ICA methods by its individual strengths and weaknesses for performing BSS is developed.
Prediction of biological and chemical features of a given chemical structure is a challenging pro... more Prediction of biological and chemical features of a given chemical structure is a challenging problem for the existing nonlinear mapping performed by neural networks. In combinatorial chemistry, computational approaches are capable to significantly decrease the necessary amounts of synthesis for the development of a specific chemical or biological drug. Therefore, the main goal is to distinguish appropriate descriptors from insignificant ones. The experimental design for the classical nonlinear neural network mapping for the approximation of five descriptors and the corresponding reaction of the immune system for the drug development are reported briefly. The results for the different descriptors are presented in comparison.
Applying a decentralized selection scheme gives the opportunity for a physically optimized ad hoc... more Applying a decentralized selection scheme gives the opportunity for a physically optimized ad hoc connectivity structure. Therefore, the prerequisites for successful wireless ad hoc networking are analyzed. Due to a specific physical layer ratio of wireless capacity utilization and the average number of independent paths, a condition of isolation gives the opportunity to maintain isolated areas in any given ad hoc network distribution. According to the common underlying mathematical model of ad hoc networks, a selective network model is used to analyze local node connectivity. 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 topology is compared to pure range controlled topology.
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.
International Journal on Wireless & Optical Communications, 2006
The major prerequisites for successfull wireless ad hoc networking are an almost homogeneous dist... more The major prerequisites for successfull wireless ad hoc networking are an almost homogeneous distribution of a nontrivial number of nodes and the determination of an almost ideal selective connectivity of the nodes in the network. To give a basic characterization of network connectivity, an ad hoc network model based on planar graphs is introduced. According to this underlying mathematical network description, the features of homogeneous connectivity for ad hoc networks are defined. Due to a specific physical layer ratio of wireless capacity utilization, a condition of isolation gives the opportunity to maintain isolated areas in any given ad hoc network distribution. To support identified isolated regions is a main goal of a hybrid transfer network. 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 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.
wseas.us
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 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.
2007 IEEE International Conference on Signal Processing and Communications, 2007
ABSTRACT
International Journal of Software Engineering and Knowledge Engineering, 2003
The localization of intracerebral dipole sources in order to detect pathological events is one pu... more The localization of intracerebral dipole sources in order to detect pathological events is one purpose of magnetoencephalography (MEG). Another aspect is the analysis of brain processes and brain structures. A system consisting of two different types of Artificial Neural Networks is presented. The structure of a feed forward neural network with two layers and a learning rule designed for the task of Blind Signal Separation (BSS) is used to separate temporarily overlapping neuron activities in the brain. Based on the separated signals, the task of the second type of neural network is to determine the position and strength of the different, underlying magnetic dipoles. Several concepts of neural networks, their limits and potentials concerning both tasks of mining medical data are discussed briefly.
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. ...
Lecture Notes in Computer Science, 2007
ABSTRACT
In this paper, a two-layer neural network is presented that organizes itself to perform blind sou... more In this paper, a two-layer neural network is presented that organizes itself to perform blind source separation. A nonlinear learning rule is proposed which allows to extract the unknown independent source signals out of their linear mixtures. The convergence behaviour of the network is investigated empirically. It is demonstrated that the network is capable of performing blind source separation for a set of acoustic signals, including sounds of a train, a rooster, a chirp and laughter.
In this paper we present a bandwith reserving load driven routing concept for a channel switched ... more In this paper we present a bandwith reserving load driven routing concept for a channel switched wireless network, based on the principle of self-organization. We describe the planar structure of the network, the relaying principle of the nodes and the details of the routing algorithm based on a specified load profile. In particular, we discuss the resource utilization, simulation results and make a performance comparison with a simple shortest distance to target routing algorithm. Both protocols are especially designed and implemented for the kind of wireless channel switched ad hoc communication network introduced.
The major prerequisites for successful wireless ad hoc networkingare an almost homogeneous distri... more The major prerequisites for successful wireless ad hoc networkingare an almost homogeneous distribution of a nontrivial number of nodes and the determination of an almost ideal selective connectivity of the nodes in the network. To give a basic characterization of network connectivity, an ad hoc network model based on planar graphs is introduced. According to this underlying mathematical network description, the features of homogeneous connectivity for ad hoc networks are defined. Due to a specific physical layer ratio of wireless capacity utilization, a condition of isolation gives the opportunity to maintain isolated areas in any given ad hoc network distribution. To support identified isolated regions is a main goal of a successfully operating hybrid transfer network.
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
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.
Proceedings of the 10th annual conference on Genetic and evolutionary computation - GECCO '08, 2008
The solution for the Max-2SAT is the starting point for a selection of these strategies by a brie... more The solution for the Max-2SAT is the starting point for a selection of these strategies by a brief review. 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 and to compare it to the computational complexity of existing local search solutions.
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
This work outlines the incorporation of human strategies in a genetic algorithm. Human competence... more This work outlines the incorporation of human strategies in a genetic algorithm. Human competence and machine intelligence are merged creating symbiotic human-machine intelligence, which is called HuGO!, the Human strategy based Genetic Optimizer. HuGO! emerged from and is applied to the restoration problem of Rubik's Cube and successfully solves this task. A competition between HuGO! and human Rubik's Cube contestants demonstrates that the incorporated human strategies improved the genetic solver's performance to become human-competitive.
According to the common underlying mathematical model for Independent Component Analysis (ICA), t... more According to the common underlying mathematical model for Independent Component Analysis (ICA), the fulfillment of a BSS for either a linear and scalar type of composition, a convolutive and linear type or a nonlinear type has different conditions. So far, several approaches have been developed in the last decades for stationary and non-stationary data. To identify key research priorities, the different origins of neural network approaches for BSS are briefly reviewed and divided by classes of specific theoretical and application features. A principal guideline for the design of reference data sets for the comparison of all the existing ICA methods by its individual strengths and weaknesses for performing BSS is developed.
Prediction of biological and chemical features of a given chemical structure is a challenging pro... more Prediction of biological and chemical features of a given chemical structure is a challenging problem for the existing nonlinear mapping performed by neural networks. In combinatorial chemistry, computational approaches are capable to significantly decrease the necessary amounts of synthesis for the development of a specific chemical or biological drug. Therefore, the main goal is to distinguish appropriate descriptors from insignificant ones. The experimental design for the classical nonlinear neural network mapping for the approximation of five descriptors and the corresponding reaction of the immune system for the drug development are reported briefly. The results for the different descriptors are presented in comparison.
Applying a decentralized selection scheme gives the opportunity for a physically optimized ad hoc... more Applying a decentralized selection scheme gives the opportunity for a physically optimized ad hoc connectivity structure. Therefore, the prerequisites for successful wireless ad hoc networking are analyzed. Due to a specific physical layer ratio of wireless capacity utilization and the average number of independent paths, a condition of isolation gives the opportunity to maintain isolated areas in any given ad hoc network distribution. According to the common underlying mathematical model of ad hoc networks, a selective network model is used to analyze local node connectivity. 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 topology is compared to pure range controlled topology.
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.
International Journal on Wireless & Optical Communications, 2006
The major prerequisites for successfull wireless ad hoc networking are an almost homogeneous dist... more The major prerequisites for successfull wireless ad hoc networking are an almost homogeneous distribution of a nontrivial number of nodes and the determination of an almost ideal selective connectivity of the nodes in the network. To give a basic characterization of network connectivity, an ad hoc network model based on planar graphs is introduced. According to this underlying mathematical network description, the features of homogeneous connectivity for ad hoc networks are defined. Due to a specific physical layer ratio of wireless capacity utilization, a condition of isolation gives the opportunity to maintain isolated areas in any given ad hoc network distribution. To support identified isolated regions is a main goal of a hybrid transfer network. 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 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.
wseas.us
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 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.
2007 IEEE International Conference on Signal Processing and Communications, 2007
ABSTRACT
International Journal of Software Engineering and Knowledge Engineering, 2003
The localization of intracerebral dipole sources in order to detect pathological events is one pu... more The localization of intracerebral dipole sources in order to detect pathological events is one purpose of magnetoencephalography (MEG). Another aspect is the analysis of brain processes and brain structures. A system consisting of two different types of Artificial Neural Networks is presented. The structure of a feed forward neural network with two layers and a learning rule designed for the task of Blind Signal Separation (BSS) is used to separate temporarily overlapping neuron activities in the brain. Based on the separated signals, the task of the second type of neural network is to determine the position and strength of the different, underlying magnetic dipoles. Several concepts of neural networks, their limits and potentials concerning both tasks of mining medical data are discussed briefly.
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. ...
Lecture Notes in Computer Science, 2007
ABSTRACT
In this paper, a two-layer neural network is presented that organizes itself to perform blind sou... more In this paper, a two-layer neural network is presented that organizes itself to perform blind source separation. A nonlinear learning rule is proposed which allows to extract the unknown independent source signals out of their linear mixtures. The convergence behaviour of the network is investigated empirically. It is demonstrated that the network is capable of performing blind source separation for a set of acoustic signals, including sounds of a train, a rooster, a chirp and laughter.
In this paper we present a bandwith reserving load driven routing concept for a channel switched ... more In this paper we present a bandwith reserving load driven routing concept for a channel switched wireless network, based on the principle of self-organization. We describe the planar structure of the network, the relaying principle of the nodes and the details of the routing algorithm based on a specified load profile. In particular, we discuss the resource utilization, simulation results and make a performance comparison with a simple shortest distance to target routing algorithm. Both protocols are especially designed and implemented for the kind of wireless channel switched ad hoc communication network introduced.
The major prerequisites for successful wireless ad hoc networkingare an almost homogeneous distri... more The major prerequisites for successful wireless ad hoc networkingare an almost homogeneous distribution of a nontrivial number of nodes and the determination of an almost ideal selective connectivity of the nodes in the network. To give a basic characterization of network connectivity, an ad hoc network model based on planar graphs is introduced. According to this underlying mathematical network description, the features of homogeneous connectivity for ad hoc networks are defined. Due to a specific physical layer ratio of wireless capacity utilization, a condition of isolation gives the opportunity to maintain isolated areas in any given ad hoc network distribution. To support identified isolated regions is a main goal of a successfully operating hybrid transfer network.