Holographic, Nonlinear Optical Implementations of Neural    Network Models
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Dov Jaron', 'PO_EMAI': None, 'PO_PHON': None}
This work relates to optical implementation of associative memory and           as such is within the area of neuro-engineering.  The basic associative         memory has been demonstrated although there is a certain amount of              controversy surrounding this particular approach.  The princial                 investigator has nonetheless shown that optical techniques can be used          to extract a full image from a portion of that image and uses                   nonlinearity and feedback to do that.  The work will also address the           possibility of designing a novelty filter.  This is a content                   addressable processor which is sensitive to the motion of the object            addressed.
{'FirstName': 'Dana', 'LastName': 'Anderson', 'PI_MID_INIT': 'Z', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dana Z Anderson', 'EmailAddress': 'dana@infleqtion.com', 'NSF_ID': '000317578', 'StartDate': '08/15/1986', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Colorado at Boulder', 'CityName': 'Boulder', 'ZipCode': '803090001', 'PhoneNumber': '3034926221', 'StreetAddress': '3100 MARINE ST', 'StreetAddress2': 'STE 481 572 UCB', 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CO02', 'ORG_UEI_NUM': 'SPVKK1RC2MZ3', 'ORG_LGL_BUS_NAME': 'THE REGENTS OF THE UNIVERSITY OF COLORADO', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8614273.xml'}