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Method for segmentation and identification of nonstationary time series

  • US 6,915,241 B2
  • Filed: 04/19/2002
  • Issued: 07/05/2005
  • Est. Priority Date: 04/20/2001
  • Status: Expired due to Fees
First Claim
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1. A method, implemented on a computer having a fixed amount of memory and CPU resources, for analyzing a sequence of measured or output data from a dynamic system, such as a machine, to categorize various parts of the sequence, said method comprising:

  • generating a partial data sequence, which comprises a plurality of successive data from an original sequence of said measured or output data, and which defines a data window;

    shifting the data window from data to data over the original sequence, wherein one data point of the partial data sequence forming the data window at its respective position is used as a reference point characterizing each individual respective position of the data window in relation to the original sequence of data, whereby the partial data sequence forming the data window at the respective position comprises the reference point and neighboring data;

    determining a characteristic function for each position of the data window such that the characteristic function is characteristic for the partial data sequence forming the data window at the respective position, and assigning each characteristic function to a respective position of the data window and to the original sequence of data by the way of the respective reference point; and

    forming thereby a sequence of characteristic functions which is related to the original sequence of data by way of each individual reference point.

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