IC manufacturing process variations are typically expressed in terms of joint probability density functions (jpdf’s) or as worst case combinations/corners of the device model pa...
The problem of designing the regularization term and regularization parameter for linear regression models is discussed. Previously, we derived an approximation to the generalizat...
In order to obtain better learning results in supervised learning, it is important to choose model parameters appropriately. Model selection is usually carried out by preparing a ...
One approach to facilitate statistical multiplexing of bursty sources in ATM networks is dispersion of the traffic over independent paths. It has been shown within the literature ...
Two approaches are proposed for the design of tied-mixture hidden Markov models (TMHMM). One approach improves parameter sharing via partial tying of TMHMM states. To facilitate ty...