Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Abstract. It is natural to present subtyping for recursive types coinductively. However, Gapeyev, Levin and Pierce have noted that there is a problem with coinductive definitions ...
We present a formal semantics for a subset of Verilog, commonly used to describe cell libraries, in terms of transition systems. Such transition systems can serve as input to symb...
In this paper, we propose a method for the derivation of an adaptive diagnostic test suite when the system specification and implementation are given in the form of an extended fin...
The aim of the paper is to revisit the model of Biological Regulatory Networks (BRN) which was proposed by René Thomas to model the interactions between a set of genes. We give a...