We propose a deep neural network architecture and associated loss functions for training algorithm computing approximate Lyapunov of systems nonlinear ordinary differential equations. Under the assumption that system admits compositional function, we prove number neurons needed an approximation function with fixed accuracy grows only polynomially in state dimension,...

Abstract Neural networks are computing models that have been leading progress in Machine Learning (ML) and Artificial Intelligence (AI) applications. In parallel, the first small-scale quantum devices become available recent years, paving way for development of a new paradigm information processing. Here we give an overview most proposals aimed at bringing together these ongoing revolutions, pa...

The excavation damaged zone (EDZ) can be defined as a rock zone where the rock properties and conditions have been changed due to the processes related to an excavation. This zone affects the behavior of rock mass surrounding the construction that reduces the stability and safety factor and increase probability of failure of the structure. In this paper, a methodology was examined for computing...

Humanoid robots, intelligent machines resembling the human body in shape and functions, cannot only replace humans to complete services dangerous tasks but also deepen own understanding of mimicking process. Nowadays, attaching a large number sensors obtain more sensory information efficient computation is development trend for humanoid robots. Nevertheless, due constraints von Neumann-based st...