Convergence and Robustness Studies of Sign-Sign Adaptive    Identifiers
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Radhakisan Baheti', 'PO_EMAI': None, 'PO_PHON': None}
The sign-sign adaptive identifier is a computationally efficient        variant of the standard identifier, in which the regressor and                  prediction error multiplicands of the update term of the LMS are                replaced by their respective signum functions.  Despite its wide use in         a host of communications and signal processing applications, theoretical        investigations into its properties are very few.  Accordingly, the              proposed project will conduct a theoretical study of convergence and            robustness properties of this algorithm.  The proposal outlines a number        of performance differences between the sign-sign and the standard LMS.          It emphasizes certain robustness enhancements enjoyed by the sign-sign          relative to the standard LMS.  It also demonstrates potential                   instability mechanisms within the sign-sign and highlights the need for         developing excitation conditions for arresting such mechanisms and for          ensuring the convergence of parameter estimates to their desired values.        The non-gradient based nature of this algorithm, together with its              intrinsic nonlinearity are expected to make its convergence and                 robustness analysis substantially different from those for traditional          gradient based algorithms.  The expected strategies for conducting such         analyses are outlined, as also are the potential theoretical and                practical benefits which this study is expected to carry.                               This research will attempt to derive a well founded theoretical         basis for the sign-sign adaptive identifier which is an algorithm used          to identity unknown signals.  It is expected that such a theoretical            basis will allow variations of the algorithm which can be employed in           both signal processing and adaptive control.
{'FirstName': 'Soura', 'LastName': 'Dasgupta', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Soura Dasgupta', 'EmailAddress': 'soura-dasgupta@uiowa.edu', 'NSF_ID': '000387312', 'StartDate': '06/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Iowa', 'CityName': 'IOWA CITY', 'ZipCode': '522421316', 'PhoneNumber': '3193352123', 'StreetAddress': '105 JESSUP HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Iowa', 'StateCode': 'IA', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IA01', 'ORG_UEI_NUM': 'Z1H9VJS8NG16', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF IOWA', 'ORG_PRNT_UEI_NUM': None}
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[{'Code': '1454', 'Text': 'SYSTEMS THEORY'}, {'Code': '1459', 'Text': 'COMMUNICATIONS SYSTEMS'}, {'Code': '4720', 'Text': 'SIGNAL PROCESSING SYS PROGRAM'}]
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