Abstract: In this work, we first show that the problem of parameter identification is often ill-conditioned and lacks the persistence of excitation required for the convergence of online learning ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

Abstract: With the large-scale integration of renewables into the power grid, a number of parameters in power systems exhibit time-varying characteristics, posing new challenges for parameter ...