Data processing: artificial intelligence – Knowledge processing system – Knowledge representation and reasoning technique
Reexamination Certificate
2011-06-21
2011-06-21
Sparks, Donald (Department: 2129)
Data processing: artificial intelligence
Knowledge processing system
Knowledge representation and reasoning technique
C706S020000, C706S028000, C706S029000
Reexamination Certificate
active
07966277
ABSTRACT:
Methods, apparatuses and systems directed to pattern identification and pattern recognition. In some particular implementations, the invention provides a flexible pattern recognition platform including pattern recognition engines that can be dynamically adjusted to implement specific pattern recognition configurations for individual pattern recognition applications. In some implementations, the present invention also provides for a partition configuration where knowledge elements can be grouped and pattern recognition operations can be individually configured and arranged to allow for multi-level pattern recognition schemes.
REFERENCES:
patent: 5293457 (1994-03-01), Arima et al.
patent: 5621863 (1997-04-01), Boulet et al.
patent: 5701397 (1997-12-01), Steimle et al.
patent: 5710869 (1998-01-01), Godefroy et al.
patent: 5717832 (1998-02-01), Steimle et al.
patent: 5740326 (1998-04-01), Boulet et al.
patent: 6778704 (2004-08-01), Kawatani
patent: 6892193 (2005-05-01), Bolle et al.
PCT/US 07/75938, International Search Reort, Neural ID, LLC, Nov. 3, 2008.
Abdi, Herve, “A Neural Network Primer”, Journal of Biological Systems, vol. 2(3), pp. 247-283., 1994.
Baker & Botts L.L.P.
Brown, Jr. Nathan H
Neural ID LLC
Sparks Donald
LandOfFree
Partition-based pattern recognition system does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Partition-based pattern recognition system, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Partition-based pattern recognition system will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2701997