State space techniques have proven to be useful for measuring and improving the coverage of test vectors that are used during functional validation via simulation. By comparing th...
Space time convolutional codes (STCCs) are an effective way to combine transmit diversity with coding. The computational complexity of designing STCCs generally increases exponent...
Kyungmin Kim, Hamid R. Sadjadpour, Rick S. Blum, Y...
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
During the development of car engines, regression models that are based on machine learning techniques are increasingly important for tasks which require a prediction of results i...
Sequential optimal design methods hold great promise for improving the efficiency of neurophysiology experiments. However, previous methods for optimal experimental design have in...
Jeremy Lewi, Robert J. Butera, David M. Schneider,...