205 research outputs found

    Observability and Synchronization of Neuron Models

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    Observability is the property that enables to distinguish two different locations in nn-dimensional state space from a reduced number of measured variables, usually just one. In high-dimensional systems it is therefore important to make sure that the variable recorded to perform the analysis conveys good observability of the system dynamics. In the case of networks composed of neuron models, the observability of the network depends nontrivially on the observability of the node dynamics and on the topology of the network. The aim of this paper is twofold. First, a study of observability is conducted using four well-known neuron models by computing three different observability coefficients. This not only clarifies observability properties of the models but also shows the limitations of applicability of each type of coefficients in the context of such models. Second, a multivariate singular spectrum analysis (M-SSA) is performed to detect phase synchronization in networks composed by neuron models. This tool, to the best of the authors' knowledge has not been used in the context of networks of neuron models. It is shown that it is possible to detect phase synchronization i)~without having to measure all the state variables, but only one from each node, and ii)~without having to estimate the phase

    Symbolic computations of non-linear observability

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    Date of Acceptance: 22/05/2015 ACKNOWLEDGEMENTS E.B.M. and M.S.B. acknowledge the Engineering and Physical Sciences Research Council (EPSRC), Grant No. EP/I032608/1. This work was done during a stay of E.B.M. at CORIA (Rouen) and a stay of C.L. at ICSMB (Aberdeen).Peer reviewedPublisher PD

    A symbolic network-based nonlinear theory for dynamical systems observability

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    EBM and MSB acknowledge the Engineering and Physical Sciences Research Council (EPSRC), grant Ref. EP/I032608/1. ISN acknowledges partial support from the Ministerio de Economía y Competitividad of Spain under project FIS2013-41057-P and from the Group of Research Excelence URJC-Banco de Santander.Peer reviewedPublisher PD
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