We propose in this paper a data driven state estimation scheme for generating nonlinear reduced models parametric families of PDEs, directly providing data-to-state maps, represented terms Deep Neural Networks. A major constituent is sensor-induced decomposition model-compliant Hilbert space warranting approximation problem relevant metrics. It plays similar role as Parametric Background Data W...

Abstract In order to reduce the power consumption, Internet of Vehicles (IoV) system mostly adopts modulation method a single parameter such as phase. However, in scenarios that require transmitting large amount information, single-information cannot meet requirements high data rates. To address this problem, paper proposes scheme adding small number full-information channels containing both am...