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Local Feedback Multilayered Networks
Neural Computation, 1992In this paper, we investigate the capabilities of local feedback multilayered networks, a particular class of recurrent networks, in which feedback connections are only allowed from neurons to themselves. In this class, learning can be accomplished by an algorithm that is local in both space and time.
FRASCONI, PAOLO, GORI M, SODA, GIOVANNI
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Towards Multilayered Automata Networks
1997In this paper Multilayered Automata Networks are formally defined as a generalization of Cellular Automata Networks. They are hierarchically organized on the basis of nested-graphs,and can show different kinds of dynamics, which allow to use them to model, for example, complex biological systems comprised of different entities organized in a ...
BANDINI, STEFANIA, MAURI, GIANCARLO
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Multilayer networks: an architecture framework
IEEE Communications Magazine, 2011We present an architecture framework for the control and management of multilayer networks and associated advanced network services. This material is identified as an "architecture framework" to emphasize its role in providing guidance and structure to our subsequent detailed architecture, design, and implementation activities. Our work is motivated by
Tom Lehman +6 more
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Synchronization of multilayer networks with stochastic
2017 11th Asian Control Conference (ASCC), 2017This paper is concerned with synchronization in a network with two different types of interactions, formulated by multilayer networks. A switching law between the two layers is proposed, which follows a Bernoulli distribution. An appropriate mathematical model is constructed firstly to describe multilayer networks with stochastic switching layers. Then
Switching Layers +4 more
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Group Consensus in Multilayer Networks
IEEE Transactions on Network Science and Engineering, 2020While there has been considerable work addressing consensus and group consensus in single-layer networks, not much attention has been devoted to consensus in multilayer networks. In this paper, we fill this gap by considering multilayer networks consisting of agents of different types while agents of the same type are arranged in separate layers.
Francesco Sorrentino 0001 +2 more
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STABILITY OF MULTILAYERED NEURAL NETWORKS
International Journal of Neural Systems, 1991Stability of a multilayered neural network architecture against synaptic changes has been studied numerically. We have found that the average change goes to zero as the number N of input neurons is N≫1. If a fixed fraction of output mistakes is allowed, then the synapses may be changed within some limits even for large N.
M. Miller, E. N. Miranda
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On Robustness in Multilayer Interdependent Networks
2016Critical Infrastructures like power and communication networks are highly interdependent on each other for their full functionality. Many significant research have been pursued to model the interdependency and failure analysis of these interdependent networks.
Joydeep Banerjee +3 more
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Multilayer feedbackward neural networks
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991A model for artificial neural networks is introduced. The model consists of a multiple layers of identical feedbackward structures. Both learning and recall algorithms of the model are presented, and simulation results are presented. >
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Multilayer network analysis for improved credit risk prediction
Omega, 2021María Óskarsdóttir, Cristián Bravo
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Evolutionary Multitasking Multilayer Network Reconstruction
IEEE Transactions on Cybernetics, 2022Kai Wu, Chao Wang, Jing Liu
exaly