Clustering time series is usually limited by the fact that the length of the time series has a significantly negative influence on the runtime. On the other hand, approximative c...
We examine in detail some properties of gesture recognition models which utilize a reduced number of parameters and lower algorithmic complexity compared to traditional hidden Mar...
Discrete-Time Markov Chains (DTMCs) are a widely-used formalism to model probabilistic systems. On the one hand, available tools like PRISM or MRMC offer efficient model checking a...
This paper presents a novel compact passive modeling technique for high-performance RF passives and interconnects modeled as high-order RLCM circuits. The new method is based on a...
Abstract: This paper presents a new net-reduction methodology to facilitate the analysis of large workflow models. We propose an enhanced algorithm based on reducible subnet identi...