An Information-Intelligent Recursive Estimation for AdaptiveSignal Processing Networks
{'Code': '05010800', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
{'SignBlockName': 'John Cozzens', 'PO_EMAI': None, 'PO_PHON': None}
The purpose is to investigate a novel recursive estimation                      algorithm whose implementation involves a discerning update                     strategy, as opposed to the continual update of most existing                   algorithms.  Model parameter estimates are determined as the                    center of an optimal bounding ellipsoid (OBE) in parameter space.               A simple test on the model prediction error determines whether                  the OBE needs updating or not.  Most of the time it does not.  By               buffering the inputs from several independent sensors into one                  OBE adaptive signal processor, one could take full advantage of                 the possible computational savings of this new approach.
{'FirstName': 'Yih-Fang', 'LastName': 'Huang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yih-Fang Huang', 'EmailAddress': 'yhuang@nsf.gov', 'NSF_ID': '000294239', 'StartDate': '11/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Notre Dame', 'CityName': 'NOTRE DAME', 'ZipCode': '465565708', 'PhoneNumber': '5746317432', 'StreetAddress': '940 GRACE HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'IN02', 'ORG_UEI_NUM': 'FPU6XGFXMBE9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NOTRE DAME DU LAC', 'ORG_PRNT_UEI_NUM': 'FPU6XGFXMBE9'}
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[{'Code': '145400', 'Text': 'SYSTEMS THEORY'}, {'Code': '472000', 'Text': 'SIGNAL PROCESSING SYS PROGRAM'}]
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