Patents by Inventor Abdul Saboor Sheikh

Abdul Saboor Sheikh has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Segment-based change detection method in multivariate data stream
    Patent number: 8005771
    Abstract: A method and framework are described for detecting changes in a multivariate data stream. A training set is formed by sampling time windows in a data stream containing data reflecting normal conditions. A histogram is created to summarize each window of data, and data within the histograms are clustered to form test distribution representatives to minimize the bulk of training data. Test data is then summarized using histograms representing time windows of data and data within the test histograms are clustered. The test histograms are compared to the training histograms using nearest neighbor techniques on the clustered data. Distances from the test histograms to the test distribution representatives are compared to a threshold to identify anomalies.
    Type: Grant
    Filed: September 24, 2008
    Date of Patent: August 23, 2011
    Assignee: Siemens Corporation
    Inventors: Terrence Chen, Chao Yuan, Abdul Saboor Sheikh, Claus Neubauer
  • Segment-Based Change Detection Method in Multivariate Data Stream
    Publication number: 20090091443
    Abstract: A method and framework are described for detecting changes in a multivariate data stream. A training set is formed by sampling time windows in a data stream containing data reflecting normal conditions. A histogram is created to summarize each window of data, and data within the histograms are clustered to form test distribution representatives to minimize the bulk of training data. Test data is then summarized using histograms representing time windows of data and data within the test histograms are clustered. The test histograms are compared to the training histograms using nearest neighbor techniques on the clustered data. Distances from the test histograms to the test distribution representatives are compared to a threshold to identify anomalies.
    Type: Application
    Filed: September 24, 2008
    Publication date: April 9, 2009
    Applicant: Siemens Corporate Research, Inc.
    Inventors: Terrence Chen, Chao Yuan, Abdul Saboor Sheikh, Claus Neubauer