In this paper we study the identifiability of linear switched systems (LSSs ) in discrete-time. The question of identifiability is central to system identification, as it sets the...
In this work a hybrid training scheme for the supervised learning of feedforward neural networks is presented. In the proposed method, the weights of the last layer are obtained em...
Background traffic has a significant impact on the behavior of network services and protocols. However, a detailed model of the background traffic can be extremely time consuming i...
—Market based spectrum trading has been extensively studied to realize efficient spectrum utilization in cognitive radio networks (CRNs). In this paper, we utilize the concept o...
Abstract. We describe a framework for training-oriented simulation of temporal bone surgery. Bone dissection is simulated visually and haptically, using a hybrid data representatio...
Dan Morris, Christopher Sewell, Nikolas H. Blevins...