Budgeted Kernel Restructuring

Abstract: BKR-CL describes an adaptive control technique employing machine learning tools and analysis to prove stabilization of a neuro-adaptive control system that learns the network structure online and in real-time. As part of the analysis, we observe that persistent excitation of the neural network is not equivalent to persistent excitation of the states. The observation is used to define an online network restructuring technique that ensure good approximation capabilities given an upper bound on the network size.
Proof of stabilization for the neuroadaptive control technique relies on Lyapunov stability theory.

More to be written soon.

The abstract and paper can be found on IEEE Xplore.