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The exploitation of the dynamics of the multiple equilibria of the network is emphasized through the adaptive shaping of the basins of attraction for each emerged pattern.
Firstly, the conditions for the number and locations of the equilibria of the network were investigated.
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First, it is demonstrated that the set of optima to the problems coincides with the set of equilibria of the neural network models which means the proposed model is complete.
In this paper, the dynamical properties of equilibria of the background neural network (2.2) (i.e., (2.3)) are analyzed, such as the number of equilibria and their locations.
To address this threat, there is a steadily growing literature that analyzes the equilibria of different distributed network resource allocation games[1, 4 13].
In this work, we will focus on the property of stability, which is an important feature for the equilibria of biological networks [ 1, 6, 17].
Eq. (9) describes the locus of equilibria of a reaction network (see Additional file 1 for the detailed derivation of this expression in the protein activation network example).
Additionally, few approaches in that line of work have focused on the dynamics of the network formation process and on the selection between multiple possible equilibria.
We found that while these equilibria are distinct in terms of network topology, it is possible to predict certain properties of the network or of certain classes of nodes with statistical significance.
Swelling and phase equilibria of polymer networks in a low molecular mass liquid crystal (LC) have been investigated as a function of network nematicity.
Now we discuss the equilibria of the system (1) which has three possible biological meaningful equilibria.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com