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Condition monitoring is an important and challenging task actual for many areas of industry, medicine and economics. Nowadays it is necessary to provide on-line monitoring of the complex systems status, e.g. the steel production, in order to avoid faults, breakdowns or wrong diagnostics. In the present paper a novel machine learning method for the automated(More)
We present a data-driven modelling approach for detection of anomalies in flood defences (levees, dykes, dams, embankments) equipped with sensors. An auto-regressive linear model and feed-forward neural network were applied for modelling a transfer function between the sensors. This approach has been validated on a dike in Boston, UK—one of the pilot sites(More)
A new non-coherent sequential code acquisition scheme is proposed based on the joint detection of correct cells (H<sub>1</sub> cells). The comparisons of the ASN with that of the conventional cell-by-cell sequential detection code acquisition system show that at almost the same cost a significant improvement can be achieved and a much more robust mean(More)
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