The paper describes a method of dividing complex sentences into segments, easily detectable and linguistically motivated units, which may provide a basis for further processing of...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Abstract— Ultra wide band (UWB) impulse radio (IR) technology calls for robust and low-complexity receiver techniques. State-of-the-art proposals are both coherent ML receivers, ...
— Traditional multiple-antenna detectors – which search a tree or a lattice structure – typically apply a metric that requires a preprocessing. Contrary to that, we present a...
: Current learning modelling languages do not allow formalization of scripts where generic tools are required. This limitation is especially relevant on remote courses when using c...