Literature DB >> 16599735

Transmitting a signal by amplitude modulation in a chaotic network.

B Cessac1, J A Sepulchre.   

Abstract

We discuss the ability of a model of network with nonlinear units and chaotic dynamics to transmit signals, on the basis of a linear response theory developed by Ruelle [D. Ruelle, J. Stat. Phys. 95, 393 (1999)] for dissipative systems. We discuss in particular how the dynamics may interfere with the graph topology to produce an effective transmission network, whose topology depends on the signal, and cannot be directly read on the "wired" network. Then, we show examples where, with a suitable choice of the carrier frequency (resonance), one can transmit a signal from a node to another one by amplitude modulation, in spite of chaos. Also, we give an example where a signal, transmitted to any node via different paths, can only be recovered by a couple of specific nodes. This opens up the possibility for encoding data in a way such that the recovery of the signal requires the knowledge of the carrier frequency and can be performed only at some specific node.

Year:  2006        PMID: 16599735     DOI: 10.1063/1.2126813

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  4 in total

1.  A discrete time neural network model with spiking neurons: II: dynamics with noise.

Authors:  B Cessac
Journal:  J Math Biol       Date:  2010-07-24       Impact factor: 2.259

2.  A discrete time neural network model with spiking neurons. Rigorous results on the spontaneous dynamics.

Authors:  B Cessac
Journal:  J Math Biol       Date:  2007-09-14       Impact factor: 2.259

3.  On dynamics of integrate-and-fire neural networks with conductance based synapses.

Authors:  Bruno Cessac; Thierry Viéville
Journal:  Front Comput Neurosci       Date:  2008-07-04       Impact factor: 2.380

4.  Retinal Processing: Insights from Mathematical Modelling.

Authors:  Bruno Cessac
Journal:  J Imaging       Date:  2022-01-17
  4 in total

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