Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or...
In this paper, real-time system identification of an unmanned aerial vehicle (UAV) based on multiple neural networks is presented. The UAV is a multi-input multi-output (MIMO) nonl...
—This paper presents a set of novel physical models for sound synthesis of membrane percussion instruments. First, a model for tension modulation in a struck circular membrane is...
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Abstract—While prior research has extensively evaluated the performance advantage of moving from a 2D to a 3D design style, the impact of process parameter variations on 3D desig...