The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jan. 29, 2013
Filed:
Oct. 12, 2009
James M. Lewis, Austin, TX (US);
Michael D. Cerna, Austin, TX (US);
Kyle P. Gupton, Austin, TX (US);
James C. Nagle, Austin, TX (US);
Yong Rao, Round Rock, TX (US);
Subramanian Ramamoorthy, Edinburgh, GB;
Darren R. Schmidt, Cedar Park, TX (US);
Bin Wang, Shanghai, CN;
Benjamin R. Weidman, Austin, TX (US);
Lothar Wenzel, Round Rock, TX (US);
Naxiong Zhang, Shanghai, CN;
James M. Lewis, Austin, TX (US);
Michael D. Cerna, Austin, TX (US);
Kyle P. Gupton, Austin, TX (US);
James C. Nagle, Austin, TX (US);
Yong Rao, Round Rock, TX (US);
Subramanian Ramamoorthy, Edinburgh, GB;
Darren R. Schmidt, Cedar Park, TX (US);
Bin Wang, Shanghai, CN;
Benjamin R. Weidman, Austin, TX (US);
Lothar Wenzel, Round Rock, TX (US);
Naxiong Zhang, Shanghai, CN;
National Instruments Corporation, Austin, TX (US);
Abstract
System and method for approximating a system. A multi-parameter representation of a family of systems is stored. An embedding of the family into an abstract geometrical continuous space with a metric and defined by the parameters is determined. Coordinates of the space specify values for the parameters of systems of the family. The space includes a grid of points representing respective discrete approximations of the systems. A first point corresponding to a desired instance of a system is determined. The first point's coordinates specify values for the parameters of the instance. The space is sampled using a mapping of a well-distributed point set from a Euclidean space of the parameters to the abstract space. A nearest discrete point to the first point is determined which specifies values for parameters for an optimal discrete approximation of the desired instance, which are useable to implement the discrete approximation of the desired instance.