Patents by Inventor Michael Repucci

Michael Repucci 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).

  • Method and system for analyzing multi-variate data using canonical decomposition
    Patent number: 7409321
    Abstract: A canonical decomposition (CD) method that includes building a multi-variate linear autoregressive (“MLAR”) model from an original data set or from a reduced set derived by data reduction methods from the original data set. The MLAR analysis is followed by seeking a coordinate transformation of the MLAR model to obtain the best possible match with one or more canonical forms representing relationships among components. For multi-variate data with a truly hierarchical structure, CD accurately extracts the underlying sources of the system.
    Type: Grant
    Filed: August 10, 2006
    Date of Patent: August 5, 2008
    Assignee: Cornell Research Foundation, Inc.
    Inventors: Michael Repucci, Jonathan Victor, Nicholas Schiff
  • Method and system for analyzing multi-variate data using canonical decomposition
    Patent number: 7171339
    Abstract: A canonical decomposition (CD) method that includes building a multi-variate linear autoregressive (“MLAR”) model from an original data set or from a reduced set derived by data reduction methods from the original data set. The MLAR analysis is followed by seeking a coordinate transformation of the MLAR model to obtain the best possible match with one or more canonical forms representing relationships among components. For multi-variate data with a truly hierarchical structure, CD accurately extracts the underlying sources of the system.
    Type: Grant
    Filed: July 11, 2001
    Date of Patent: January 30, 2007
    Assignee: Cornell Research Foundation, Inc.
    Inventors: Michael Repucci, Nicholas Schiff, Jonathan Victor
  • METHOD AND SYSTEM FOR ANALYZING MULTI-VARIATE DATA USING CANONICAL DECOMPOSITION
    Publication number: 20070005391
    Abstract: A canonical decomposition (CD) method that includes building a multi-variate linear autoregressive (“MLAR”) model from an original data set or from a reduced set derived by data reduction methods from the original data set. The MLAR analysis is followed by seeking a coordinate transformation of the MLAR model to obtain the best possible match with one or more canonical forms representing relationships among components. For multi-variate data with a truly hierarchical structure, CD accurately extracts the underlying sources of the system.
    Type: Application
    Filed: August 10, 2006
    Publication date: January 4, 2007
    Applicant: Cornell University Research Foundation, Inc.
    Inventors: Michael Repucci, Nicholas Schiff, Jonathan Victor
  • Method and system for analyzing multi-variate data using canonical decomposition
    Publication number: 20050015205
    Abstract: A canonical decomposition (CD) method that includes building a multi-variate linear autoregressive (“MLAR”) model from an original data set or from a reduced set derived by data reduction methods from the original data set. The MLAR analysis is followed by seeking a coordinate transformation of the MLAR model to obtain the best possible match with one or more canonical forms representing relationships among components. For multi-variate data with a truly hierarchical structure, CD accurately extracts the underlying sources of the system.
    Type: Application
    Filed: July 11, 2001
    Publication date: January 20, 2005
    Inventors: Michael Repucci, Nicholas Schiff, Jonathan Victor