Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past ...
Power System,Distributed Energy Resources,Electric Vehicles,Load Shedding,Actor Network,Critic Network,Greenhouse Gas,Operational Costs,Market Power,Multi-agent Reinforcement Learning,Renewable Energy ...
The rapid growth of high-speed semiconductor and communication technologies has helped make phase-locked loops (PLLs) an essential part of memories, microprocessors, radio-frequency (RF) transceivers, ...
Fan Liu (Member, IEEE) received the B.Eng. and Ph.D. degrees from the Beijing Institute of Technology (BIT), Beijing, China, in 2013 and 2018, respectively. He is currently an Assistant Professor with ...
System identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Used for prediction, control, physical interpretation, and ...
Also published under: J. Rodriguez, José Rodríguez, José Rodriguez, Jose Rodríguez, JosÉ Rodriguez, J. R. Rodríguez-Rodríguez, JosÉ RodrÍguez, Jose R ...
Abstract: Two machine-learning procedures have been investigated in some detail using the game of checkers. Enough work has been done to verify the fact that a computer can be programmed so that it ...
Abstract: Performance and functional requirements for a communications-based train control (CBTC) system are established in this standard. A CBTC system is a continuous, automatic train control system ...