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Statistic Feature Extraction

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Data-Driven Technology for Engineering Systems Health Management

Abstract

Feature extraction is a commonly used technique applied before diagnosis and prognosis when a number of measures, or features, have been taken from a set of objects in a typical statistical pattern recognition or trending reasoning task. The goal is to define a mapping from the original representation space into a new space where the classes are more easily separable. This will reduce the classifier or prediction complexity, increasing in most cases accuracy.

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Authors and Affiliations

  1. Institute of Rail Transit, Tongji University, Shanghai, China

    Gang Niu

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  1. Gang Niu
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© 2017 Springer Science+Business Media Singapore and Science Press, Beijing, China

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Niu, G. (2017). Statistic Feature Extraction. In: Data-Driven Technology for Engineering Systems Health Management. Springer, Singapore. https://doi.org/10.1007/978-981-10-2032-2_5

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  • DOI: https://doi.org/10.1007/978-981-10-2032-2_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2031-5

  • Online ISBN: 978-981-10-2032-2

  • eBook Packages: EngineeringEngineering (R0)

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