Hopfield-Like Neural Nets and Sensor Networks

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Abstract

The transformation of a sensor network (SN) into a neural Hopfield-like network (HLN) is proposed. The SN of interest is a nonlinear non-reciprocal population of coupled oscillators. The proposed transformation is useful for investigating the relation between the structure of the SN and its capability of arriving to a global consensus. The case of a 3-SN is developed in detail for illustrating the advantages of the suggested transformation. Both the structural conditions necessary for achieving in this case the consensus and its relation to local measurements are presented.

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