Christian Gruhl

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After data selection, pre-processing, transformation, and feature extraction, knowledge extraction is not the final step in a data mining process. It is then necessary to understand this knowledge in order to apply it efficiently and effectively. Up to now, there is a lack of appropriate techniques that support this significant step. This is partly due to(More)
! Abstract— In this article, we propose CANDIES (Combined Approach for Novelty Detection in Intelligent Embedded Systems), a new approach to novelty detection in technical systems. We assume that in a technical system several processes interact. If we observe these processes with sensors, we are able to model the observations (samples) with a probabilistic(More)
—Hidden Markov Models (HMM) have been used for several years in many time series analysis or pattern recognitions tasks. HMM are often trained by means of the Baum-Welch algorithm which can be seen as a special variant of an expectation maximization (EM) algorithm. Second-order training techniques such as Variational Bayesian Inference (VI) for(More)
Self-adaptive and self-organising (SASO) systems are one promising approach to counter the raising interconnectedness and complexity in technical systems [1]. In particular, decisions about parametrisation, behaviour, and even structure are moved into the responsibility of the systems themselves: from design-time to runtime. This means that hardly all(More)
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