A Unified Approach with New Algorithms for Adaptive         Recursive (IIR) Digital Filters
{'Code': '05010800', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
{'SignBlockName': 'John R. Lehmann', 'PO_EMAI': None, 'PO_PHON': None}
It is well known that a pole-zero structure which corresponds to an             infinite impulse response (IIR) filter models a physical system better          than an all-zero structure, or a finite impulse response (FIR)                  filtering structure.  However, few adaptive IIR filtering algorithms are        in existence today due to the non-linearity of the problem.  Many issues        such as stability and global convergence are not well-solved.  Besides,         lack of adequate analytic tools makes the analysis of these algorithms a        difficult task.  On the other hand, recursive system identification, as         a well-established subject, has available many well-behaved algorithms.         Although the similarities between these two fields have recently been           realized, only direct application of some system identification                 algorithms to adaptive filtering problems is seen in literature.                                                                                                This research focuses on a new adaptive IIR filtering algorithm and a           unified analytical method which shows some global convergence.  The new         method uses an ordinary differential equation (ODE) approach for                constant-gain adaptive IIR filtering algorithms which is parallel to the        ODE approach in the field of system identification.  Hence further              insight into the connection between constant-gain adaptive IIR                  filtering algortihms and their system identification counterparts can be        gained.  Using this new approach, many existing adaptive IIR                    filtering algorithms are being analyzed and compared in a unified way.          Furthermore, more system identification algorithms are being tailored           for adaptive IIR filtering applications with simplified calculation and         constant gains.  The observed global convergence phenomenon is also             being investigated using the same approach, and should lead to the              development of new globally convergent algorithms for certain classes of        environment.                                                                    Adaptive filers are used in a wide spectrum of applications such as             noise cancellation, channel equalization, spectral estimation, and              antenna array processing.  This proposal focuses research on these              adaptive filters.
{'FirstName': 'H.', 'LastName': 'Fan', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'H. H Fan', 'EmailAddress': 'h.fan@uc.edu', 'NSF_ID': '000309920', 'StartDate': '07/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Cincinnati Main Campus', 'CityName': 'CINCINNATI', 'ZipCode': '452202872', 'PhoneNumber': '5135564358', 'StreetAddress': '2600 CLIFTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'OH01', 'ORG_UEI_NUM': 'DZ4YCZ3QSPR5', 'ORG_LGL_BUS_NAME': 'CINCINNATI UNIV OF', 'ORG_PRNT_UEI_NUM': 'DZ4YCZ3QSPR5'}
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{'Code': '472000', 'Text': 'SIGNAL PROCESSING SYS PROGRAM'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8620147.xml'}