Method for segmentation and identification of nonstationary time series
First Claim
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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Abstract
A method, implemented on a computer having a fixed amount of memory and CPU resources, for analyzing a sequence of data units derived from a dynamic system to which new data units may be added by classifying the data units, is disclosed. The method comprises determining the similarity of the data units being part of the sequence of data units by calculating the distance between all pairs of data units in a data space. The method further comprises classifying the data units by assigning labels to the data units such that, if the distance of a data unit which is to be classified to any other data unit exceeds a threshold, a new label is assigned to the data unit to be classified. Also, if the threshold is not exceeded, the label of the data unit being closest to the data unit to be classified is assigned to the data unit to be classified.
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Citations
22 Claims
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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:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 16)
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10. A method, implemented on a computer having a fixed amount of memory and CPU resources, for analyzing a sequence of data units derived from a dynamic system, such as a machine, to which new data units may be added by classifying the data units, said method comprising:
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determining the similarity of the data units being part of the sequence of data units by calculating the distance between all pairs of data units in a data space; and
classifying the data units by assigning labels to the data units such that, if the distance of a data unit which is to be classified to any other data unit exceeds a threshold, a new label is assigned to the data unit to be classified and, if the threshold is not exceeded, the label of the data unit being closest to the data unit to be classified is assigned to the data unit to be classified. - View Dependent Claims (11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22)
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Specification