Feature extraction

This dataset is associated with the paper, Jackson & Hall 2016, which is open source, and can be found here: http://ieeexplore.ieee.org/document/7742994/

The DataPort Repository contains the data used primarily for generating Figure 1.

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  • Biomedical and Health Sciences
  • Last Updated On: 
    Sat, 06/16/2018 - 23:05

    To obtain the prices of parts from the manufacturing characteristics and other manufacturing processes, feature quantity expression is innovatively applied. By identifying manufacturing features and calculating the feature quantities, the feature quantities are described in the form of assignments as data. To obtain the prices of parts intelligently, the most widely used and mature deep-learning method is adopted to realize the accurate quotation of parts

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  • Computational Intelligence
  • Last Updated On: 
    Tue, 05/21/2019 - 21:42

    Electroencephalography (EEG) signal data was collected from twelve healthy subjects with no known musculoskeletal or neurological deficits (mean age 25.5 ± 3.7, 11 male, 1 female, 1 left handed, 11 right handed) using an EGI Geodesics© Hydrocel EEG 64-Channel spongeless sensor net. All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of the University of Wisconsin-Milwaukee (17.352).

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  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34

    This is the source code (MATLAB) of the LTMBMCR feature.

     

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  • Signal Processing
  • Last Updated On: 
    Sat, 06/16/2018 - 23:19