Stochastic image modeling based on conventional Markov random fields is extensively discussed in the literature. A new stochastic image model based on Markov random fields is intr...
Large amount of uncertain data is inherent in many novel and important applications such as sensor data analysis and mobile data management. A probabilistic threshold range aggrega...
This paper describes principles of a novel two-level multi-output Boolean minimizer FC-Min, namely its Find Coverage phase. The problem of Boolean minimization is approached in a ...
We are studying long term sequence prediction (forecasting). We approach this by investigating criteria for choosing a compact useful state representation. The state is supposed t...
Most distributed real-time embedded systems are specified combining state diagram and data flow languages. This leads to several real-time codes which together do not necessaril...