Estimation for Stochastic Inverse Problems
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{'SignBlockName': 'John Cozzens', 'PO_EMAI': None, 'PO_PHON': None}
Stochastic inverse problems arise when a blurred version of a                   desired signal or image influences the statistics of a random                   process that models measured data.  Examples include the quantum-               limited imaging of radioactive tracers in the body, imaging                     gamma-ray sources in astronomy, and forming images in low-light                 photography.  A joint group research program is being pursued                   with Alan Karr at the Johns Hopkins University to investigate new               algorithms for these problems.  Identifying algorithms which map                onto highly parallel computational architectures is an important                objective of the research.
{'FirstName': 'Donald', 'LastName': 'Snyder', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Donald L Snyder', 'EmailAddress': 'dls@ee.wustl.edu', 'NSF_ID': '000458181', 'StartDate': '08/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
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