6533b828fe1ef96bd1287be7
RESEARCH PRODUCT
Dynamical attractors of memristors and their networks
Valeriy A. SlipkoYuriy V. Pershinsubject
State variableIdeal (set theory)Condensed Matter - Mesoscale and Nanoscale PhysicsComputer scienceFOS: Physical sciencesGeneral Physics and AstronomyFunction minimizationMemristorFunction (mathematics)State (functional analysis)Nonlinear Sciences - Chaotic DynamicsTopologyNonlinear Sciences - Adaptation and Self-Organizing Systemslaw.inventionParameter identification problemComputer Science::Emerging TechnologieslawMesoscale and Nanoscale Physics (cond-mat.mes-hall)AttractorChaotic Dynamics (nlin.CD)Adaptation and Self-Organizing Systems (nlin.AO)description
It is shown that the time-averaged dynamics of memristors and their networks periodically driven by alternating-polarity pulses may converge to fixed-point attractors. Starting with a general memristive system model, we derive basic equations describing the fixed-point attractors and investigate attractors in the dynamics of ideal, threshold-type and second-order memristors, and memristive networks. A memristor potential function is introduced, and it is shown that in some cases the attractor identification problem can be mapped to the problem of potential function minimization. Importantly, the fixed-point attractors may only exist if the function describing the internal state dynamics depends on an internal state variable. Our findings may be used to tune the states of analog memristors, and also be relevant to memristive synapses subjected to forward- and back-propagating spikes.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-08-14 | EPL (Europhysics Letters) |