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  • An enduring problem in FDI is that of characterizing the dynamics of complex systems. This is a key step towards feature extraction. The difficulty stems from the fact that in many cases it is not possible to derive a suitable model from the first principles. Given historical data, the typical way to proceed is via data projection into latent structures or by using integral transforms (orthogonal decomposition). Two main topics are addressed within the proposal: (1) Employment of Bayesian framework as systematic approach to feature extraction via exploiting on-line and historical process data available. The considered solution supposes dynamic probabilistic mixture modelling of the underlying process. The probabilistic extraction of information from process data allows us to overcome the dependence on application and does not require detailed knowledge of system dynamics. Furthermore, the related algorithms and used techniques mostly have a long tradition and already proved to be efficient and acc (en)
  • An enduring problem in FDI is that of characterizing the dynamics of complex systems. This is a key step towards feature extraction. The difficulty stems from the fact that in many cases it is not possible to derive a suitable model from the first principles. Given historical data, the typical way to proceed is via data projection into latent structures or by using integral transforms (orthogonal decomposition). Two main topics are addressed within the proposal: (1) Employment of Bayesian framework as systematic approach to feature extraction via exploiting on-line and historical process data available. The considered solution supposes dynamic probabilistic mixture modelling of the underlying process. The probabilistic extraction of information from process data allows us to overcome the dependence on application and does not require detailed knowledge of system dynamics. Furthermore, the related algorithms and used techniques mostly have a long tradition and already proved to be efficient and acc (cs)
Title
  • BAYESIAN DECISION MAKING TO SUPPORT CHANGE DETECTION IN COMPLEX MANUFACTURING SYSTEMS (en)
  • BAYESIAN DECISION MAKING TO SUPPORT CHANGE DETECTION IN COMPLEX MANUFACTURING SYSTEMS (cs)
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  • Modelling of complex systems; Fault detection; Bayesian estimation; Adaptive control (en)
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