Department of Mathematics and Statistics, Queen’s University, Kingston, ON, Canada; Department of Electrical and Computer Engineering, University of California at Los Angeles, Los Angeles, CA 90095
Paulo Tabuada, Bahman Gharesifard
Deep residual neural networks;universal approximation;nonlinear control theory
Universal approximation power of deep residual neural networks via nonlinear control theory