Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=18 ...

Autonomous Vehicles,Neural Network,Prediction Error,Ablation Experiments,Actual Trajectory,Affine Transformation,Automated Guided Vehicles,Axis Length,Batch ...

Department of Electrical and Electronic Engineering, Imperial College London, London, U.K. Bruno Clerckx is a senior lecturer at Imperial College London. His area of expertise is communication theory ...

Abstract: Measurements of the equivalent parallel conductance of metal-insulator-semiconductor (MIS) capacitors are shown to give more detailed and accurate information about interface states than ...

Optimal Control,Nonlinear Systems,Optimization Problem,Control Input,Control Design,Neural Network,Tracking Error,Adaptive Control,Control Method,Cost Function,Multi ...

Zhong Tang (Member, IEEE) received the B.S. and Ph.D. degrees in electrical engineering from Zhejiang University, Hangzhou, China, in 2015 and 2020, respectively. From 2019 to 2020, he was a Visiting ...

Abstract: Maxwell's equations are replaced by a set of finite difference equations. It is shown that if one chooses the field points appropriately, the set of finite difference equations is applicable ...

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6731005 ...

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 ...

Department of Geography and Resource Management, Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China Peifeng Ma (Member, IEEE) received the M.S.

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it ...