The Experts below are selected from a list of 93588 Experts worldwide ranked by ideXlab platform
Konstantinos E Parsopoulos - One of the best experts on this subject based on the ideXlab platform.
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optimal power allocation and joint source channel coding for wireless ds cdma visual sensor networks using the nash bargaining solution
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Katerina Pandremmenou, Lisimachos P Kondi, Konstantinos E ParsopoulosAbstract:We consider the problem of resource allocation for a Direct Sequence Code Division Multiple Access (DS-CDMA) wireless visual sensor network (VSN).We use the Nash Bargaining Solution (NBS) from game theory in order to determine the transmission power and source and channel coding rate for each node. The NBS assumes that the nodes negotiate (using the help of a centralized control unit) in order to jointly determine their transmission parameters. The transmission powers are allowed to take continuous values, whereas the source and channel coding rate combination can only assume discrete values. Thus, the resulting Optimization problem is a mixed-integer Optimization Task and is solved using Particle Swarm Optimization (PSO). Experimental results are provided and conclusions are drawn.
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ICASSP - Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks using the Nash Bargaining Solution
2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011Co-Authors: Katerina Pandremmenou, Lisimachos P Kondi, Konstantinos E ParsopoulosAbstract:We consider the problem of resource allocation for a Direct Sequence Code Division Multiple Access (DS-CDMA) wireless visual sensor network (VSN).We use the Nash Bargaining Solution (NBS) from game theory in order to determine the transmission power and source and channel coding rate for each node. The NBS assumes that the nodes negotiate (using the help of a centralized control unit) in order to jointly determine their transmission parameters. The transmission powers are allowed to take continuous values, whereas the source and channel coding rate combination can only assume discrete values. Thus, the resulting Optimization problem is a mixed-integer Optimization Task and is solved using Particle Swarm Optimization (PSO). Experimental results are provided and conclusions are drawn.
Katerina Pandremmenou - One of the best experts on this subject based on the ideXlab platform.
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optimal power allocation and joint source channel coding for wireless ds cdma visual sensor networks using the nash bargaining solution
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Katerina Pandremmenou, Lisimachos P Kondi, Konstantinos E ParsopoulosAbstract:We consider the problem of resource allocation for a Direct Sequence Code Division Multiple Access (DS-CDMA) wireless visual sensor network (VSN).We use the Nash Bargaining Solution (NBS) from game theory in order to determine the transmission power and source and channel coding rate for each node. The NBS assumes that the nodes negotiate (using the help of a centralized control unit) in order to jointly determine their transmission parameters. The transmission powers are allowed to take continuous values, whereas the source and channel coding rate combination can only assume discrete values. Thus, the resulting Optimization problem is a mixed-integer Optimization Task and is solved using Particle Swarm Optimization (PSO). Experimental results are provided and conclusions are drawn.
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ICASSP - Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks using the Nash Bargaining Solution
2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011Co-Authors: Katerina Pandremmenou, Lisimachos P Kondi, Konstantinos E ParsopoulosAbstract:We consider the problem of resource allocation for a Direct Sequence Code Division Multiple Access (DS-CDMA) wireless visual sensor network (VSN).We use the Nash Bargaining Solution (NBS) from game theory in order to determine the transmission power and source and channel coding rate for each node. The NBS assumes that the nodes negotiate (using the help of a centralized control unit) in order to jointly determine their transmission parameters. The transmission powers are allowed to take continuous values, whereas the source and channel coding rate combination can only assume discrete values. Thus, the resulting Optimization problem is a mixed-integer Optimization Task and is solved using Particle Swarm Optimization (PSO). Experimental results are provided and conclusions are drawn.
Lisimachos P Kondi - One of the best experts on this subject based on the ideXlab platform.
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optimal power allocation and joint source channel coding for wireless ds cdma visual sensor networks using the nash bargaining solution
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Katerina Pandremmenou, Lisimachos P Kondi, Konstantinos E ParsopoulosAbstract:We consider the problem of resource allocation for a Direct Sequence Code Division Multiple Access (DS-CDMA) wireless visual sensor network (VSN).We use the Nash Bargaining Solution (NBS) from game theory in order to determine the transmission power and source and channel coding rate for each node. The NBS assumes that the nodes negotiate (using the help of a centralized control unit) in order to jointly determine their transmission parameters. The transmission powers are allowed to take continuous values, whereas the source and channel coding rate combination can only assume discrete values. Thus, the resulting Optimization problem is a mixed-integer Optimization Task and is solved using Particle Swarm Optimization (PSO). Experimental results are provided and conclusions are drawn.
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ICASSP - Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks using the Nash Bargaining Solution
2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011Co-Authors: Katerina Pandremmenou, Lisimachos P Kondi, Konstantinos E ParsopoulosAbstract:We consider the problem of resource allocation for a Direct Sequence Code Division Multiple Access (DS-CDMA) wireless visual sensor network (VSN).We use the Nash Bargaining Solution (NBS) from game theory in order to determine the transmission power and source and channel coding rate for each node. The NBS assumes that the nodes negotiate (using the help of a centralized control unit) in order to jointly determine their transmission parameters. The transmission powers are allowed to take continuous values, whereas the source and channel coding rate combination can only assume discrete values. Thus, the resulting Optimization problem is a mixed-integer Optimization Task and is solved using Particle Swarm Optimization (PSO). Experimental results are provided and conclusions are drawn.
Mahmut Bayramoglu - One of the best experts on this subject based on the ideXlab platform.
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exergy loss minimization analysis of sugar production process from sugar beet
Food and Bioproducts Processing, 1998Co-Authors: Taner Tekin, Mahmut BayramogluAbstract:Exergy loss or equivalent entropy generation minimization is a powerful tool to design and operate processes which use energy as well as natural resources more efficiently. Two techniques, namely; approximate Optimization analysis and structural analysis may be helpful to simplify the detailed Optimization Task. This study considers the application of these techniques to the process of sugar production from sugar beet.
K Schulz - One of the best experts on this subject based on the ideXlab platform.
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wado water design Optimization methodology and software for the synthesis of process water systems
Journal of Cleaner Production, 2005Co-Authors: C Ullmer, N Kunde, A Lassahn, G Gruhn, K SchulzAbstract:Abstract In this paper, an integrated synthesis strategy for the design of industrial process water systems is presented. The aim is to determine the cost optimal water network considering multiple contaminants and various possibilities of water reuse and regeneration. The approach is based on heuristic rules that assist the formulation of the real world design problem in such a way that a mixed integer nonlinear programming problem can be derived. Mathematical Optimization methods are used to generate the cost optimal solution for this problem. Emphasis is placed on the treatment system including the selection of reasonable treatment operations for regeneration purposes and on the construction of a reasonable superstructure for the final Optimization Task.
