DiagSign Automatic Feature Generation and the State of the Art

We just published a new white paper in our document library « DiagSign Automatic Feature Generation and the State of the Art ».

This paper summarizes the state of the art in terms of academical methods to solving the problem of feature generation from time series.

These can be classified in two categories :

  • Structured models approaches
  • Dimensionality reduction approaches

DiagSign is a protected invention that was born in the labs of the French National Research Centre (CNRS). It uses a purely mathematical method to automatically generate features from time series that are relevant, highly discriminant, and very adapted to transitional signals.

DiagSign can generate as many features as needed, possibly thousands, in record time and in a massively parallelizable way. In addition, it is agnostic to the type of signal nor does it care what equipment is diagnosed.

The white paper explains why Amiral Techologies’ DiagSign surpasses these academical methods and avoinds their drawbacks :

  • It does not assume an a priori structured model
  • It keeps all the information in the signal
  • It offers tremendous and low cost scalability

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