Düşük iletişim yüklü olay-tetikli dağıtık kestirim

We propose a novel algorithm for distributed processing applications constrained by the available communication resources using diffusion strategies that achieves up to a 10^3 fold reduction in the communication load over the network, while delivering a comparable performance with respect to the state of the art. After the computation of the local estimates, the information is diffused among the processing elements (or nodes) non-uniformly in time by conditioning the information transfer on level-crossings of the diffused parameter, resulting in a greatly reduced communication requirement. We provide the mean and mean-square stability analyses of the proposed algorithm, and illustrate the gain in communication efficiency compared to other reduced-communication distributed estimation schemes.