Abstract--We introduce a stochastic extension of CCS endowed with structural operational semantics expressed in terms of measure theory. The set of processes is organised as a meas...
This paper extends the application of the Cantor metric as a mathematical tool for defining causalities from pure discrete models to mixed-signal and hybrid models. Using the Cant...
This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
Polymorphous computer-based systems are systems in which the CPU architecture “morphs” or changes shape to meet the requirements of the application. Optimized and efficient de...
Brandon Eames, Ted Bapty, Ben Abbott, Sandeep Neem...
One of central topics of kernel machines in the field of machine learning is a model selection, especially a selection of a kernel or its parameters. In our previous work, we dis...