This paper presents novel techniques for the cycle-accurate power macro-modeling of complex RTL components. The proposed techniques are based on the observation that RTL component...
Nachiketh R. Potlapally, Michael S. Hsiao, Anand R...
Artificial neural networks (ANN's) are associated with difficulties like lack of success in a given problem and unpredictable level of accuracy that could be achieved. In eve...
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
A new algorithm for identifying stuck faults in combinational circuits that cannot be detected by a given input sequence is presented. Other than pre and post-processing steps, ce...
Vishwani D. Agrawal, Soumitra Bose, Vijay Gangaram
Grid adaptation in two-point boundary value problems is usually based on mapping a uniform auxiliary grid to the desired nonuniform grid. Here we combine this approach with a new ...