Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2006-02-25
2009-11-24
Vincent, David R (Department: 2129)
Data processing: artificial intelligence
Neural network
Learning task
C706S022000, C706S025000, C706S061000
Reexamination Certificate
active
07624080
ABSTRACT:
As the present invention's adaptation process is typically practiced, an observation made by one or more sensing element(s) is classified as being either recognized or unrecognized in the context of a knowledge base. If the observation is classified as being recognized and consistent, then the observation is assimilated into the knowledge base; otherwise, it is not assimilated. If the observation is classified as being unrecognized, then the observation is classified as being uncorroborated in the context of the knowledge base. Prior to being classified as being uncorroborated, the unrecognized observation is categorized in the context of the knowledge base and is associated with an outcome in terms of relationship between/among physical parameters. At the time that corroboration is determined, the observation (originally unrecognized) and its categorization-related and association-related information are assimilated into the knowledge base.
REFERENCES:
patent: 4586403 (1986-05-01), Lee et al.
patent: 5005142 (1991-04-01), Lipchak et al.
patent: 5056360 (1991-10-01), Dosdall et al.
patent: 5158062 (1992-10-01), Chen
patent: 5392599 (1995-02-01), Hamburg et al.
patent: 5469369 (1995-11-01), Rose-Pehrsson et al.
patent: 5627465 (1997-05-01), Alfors et al.
patent: 5748847 (1998-05-01), Lo
patent: 5751609 (1998-05-01), Schaefer, Jr. et al.
patent: 5819007 (1998-10-01), Elghazzawi
patent: 5857160 (1999-01-01), Dickinson et al.
patent: 5875108 (1999-02-01), Hoffberg et al.
patent: 5890101 (1999-03-01), Schaefer, Jr. et al.
patent: 5901246 (1999-05-01), Hoffberg et al.
patent: 5901272 (1999-05-01), Schaefer, Jr. et al.
patent: 5948030 (1999-09-01), Miller et al.
patent: 5978025 (1999-11-01), Tomasini et al.
patent: 5987397 (1999-11-01), McCool et al.
patent: 6039144 (2000-03-01), Chandy et al.
patent: 6081750 (2000-06-01), Hoffberg et al.
patent: 6088661 (2000-07-01), Poublon
patent: 6263325 (2001-07-01), Yoshida et al.
patent: 6314329 (2001-11-01), Madau et al.
patent: 6400996 (2002-06-01), Hoffberg et al.
patent: 6418424 (2002-07-01), Hoffberg et al.
patent: 6437936 (2002-08-01), Chen et al.
patent: 6466888 (2002-10-01), McCool et al.
patent: 6473524 (2002-10-01), Reda et al.
patent: 6546342 (2003-04-01), Dougherty et al.
patent: 6564125 (2003-05-01), Pattok et al.
patent: 6574271 (2003-06-01), Mesecher et al.
patent: 6690660 (2004-02-01), Kim et al.
patent: 6747481 (2004-06-01), Pitts
patent: 6795794 (2004-09-01), Anastasio et al.
patent: 6889165 (2005-05-01), Lind et al.
patent: 6898584 (2005-05-01), McCool et al.
patent: 6944244 (2005-09-01), Belotserkovsky et al.
patent: 6947855 (2005-09-01), Verbrugge et al.
patent: 6970804 (2005-11-01), Siegel et al.
patent: 6988056 (2006-01-01), Cook
patent: 01010307 (1989-01-01), None
Schecke et al., “A Knowledge-Based Approachto Intelligent Alarms in Anesthesia”, 1991.
Miguel A. Morales and David J. Haas, “Adaptive Sensors for Aircraft Operational Monitoring,” AIAA 2004-1892, 12 pages, 45thAIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Apr. 19-22, 2004, Palm Springs, California.
Miguel A. Morales and David J. Haas, “Adaptive Sensors for Aircraft Operational Monitoring,” Computer Sciences Corporation (CSC), Falls Church, Virginia, Leading Edge Forum Technology Programs, CSC Papers 2005; available on the CSC website at http://www.csc.com/aboutus/lef/mds67—off/uploads/CSCPaper2005—AdaptiveSensors.pdf, 21 pages printed out on or about Feb. 2006.
R. G. Adams, K. Butchart, and N. Davey, “Hierarchical Classification with a Competitive Evolutionary Neural Tree,”Neural Networks, vol. 12, No. 3, pp. 541-551 (Apr. 1999).
Paul Rigby and Stefan B. Williams, Adaptive Sensing for Localisation of an Autonomous Underwater Vehicle, Australasian Conference on Robotics and Automation (ACRA), Dec. 5-7, 2005, Sydney, Australia; available on the Australian Robotics and Automation Association Inc. (ARAA) website at http://www.araa.asn.au/acra/acra2005/papers/rigby.pdf, 7 pages printed out on or about Feb. 2006.
Haas David J.
Morales Miguel A.
Brown, Jr Nathan H
Kaiser Howard
The United States of America as represented by the Secretary of
Vincent David R
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