Performance analysis of multi-hop wireless packet networks.
Lim, J.-T., Meerkov, S.M. (1996)
Mathematical Problems in Engineering
Similarity:
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
Lim, J.-T., Meerkov, S.M. (1996)
Mathematical Problems in Engineering
Similarity:
Guo, Qin, Luo, Mingxing, Li, Lixiang, Yang, Yixian (2010)
Mathematical Problems in Engineering
Similarity:
Miloš Kudělka, Šárka Zehnalová, Zdeněk Horák, Pavel Krömer, Václav Snášel (2015)
International Journal of Applied Mathematics and Computer Science
Similarity:
Many real world data and processes have a network structure and can usefully be represented as graphs. Network analysis focuses on the relations among the nodes exploring the properties of each network. We introduce a method for measuring the strength of the relationship between two nodes of a network and for their ranking. This method is applicable to all kinds of networks, including directed and weighted networks. The approach extracts dependency relations among the network's nodes...
Margaris, Athanasios, Kotsialos, Efthymios, Styliadis, Athansios, Roumeliotis, Manos (2004)
Acta Universitatis Apulensis. Mathematics - Informatics
Similarity:
M. Sysło (1972)
Applicationes Mathematicae
Similarity:
Dong, Chengdong (2010)
Mathematical Problems in Engineering
Similarity:
Jin Wang, Tinghuai Ma, Jinsung Cho, Sungoung Lee (2011)
Computer Science and Information Systems
Similarity:
Daduna, Hans (1991)
Journal of Applied Mathematics and Stochastic Analysis
Similarity:
Maciej Huk (2012)
International Journal of Applied Mathematics and Computer Science
Similarity:
In this paper the Sigma-if artificial neural network model is considered, which is a generalization of an MLP network with sigmoidal neurons. It was found to be a potentially universal tool for automatic creation of distributed classification and selective attention systems. To overcome the high nonlinearity of the aggregation function of Sigma-if neurons, the training process of the Sigma-if network combines an error backpropagation algorithm with the self-consistency paradigm widely...
Alfred Aanu Akinsete (2001)
Kragujevac Journal of Mathematics
Similarity: