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InfoResearchPeer-reviewed
A Neural-Network-Assisted Approach to Recursive State Estimation for Energy Harvesting Complex Networks With Unknown Nonlinearities
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Summary
This article studies partial node-based recursive state estimation for complex networks with unknown nonlinearities, where energy harvesting sensors transmit measurements only when their energy suffices for transmission. Neural networks approximate the unknown nonlinearities, and an NN-based recursive algorithm generates state estimates and nonlinearity estimates together. The effectiveness of the algorithm is demonstrated through a simulation example.