A cost-effective framework for distributed filtering of α-stable signals over sensor networks is proposed. To this end, the problem of filtering α-stable signals through multiple observations made over a network of sensors is revisited and an optimal solution is formulated. Then, an adaptive gradient descent based algorithm for distributed real-time filtering of α-stable signals via multi-agent networks is derived. The derived algorithm not only gives an approximation of the formulated optimal solution, but is also cost-effective and scalable with the size of the network. Moreover, performance of the derived algorithm is analyzed and convergence conditions are established.
SormenjälkiSukella tutkimusaiheisiin 'Distributed Adaptive Filtering of α-Stable Signals'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.
- 1 Päättynyt
01/09/2016 → 31/12/2020
Projekti: Academy of Finland: Other research funding