VLSI Implementation of Neural - Type Cells
{'Code': '05010600', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
{'SignBlockName': 'Robert B Grafton', 'PO_EMAI': None, 'PO_PHON': None}
This research addresses the theoretical design, analysis and                    implementation of a VLSI chip for a neural-type cell.  The                      neural-type cell has a number of properties that make it suitable               for inclusion in a neural network;  for example, an output pulse                repetition rate controlled by input amplitude.  The research is                 to:  first, design, study and analyze the equations for the                     neural-type cell and obtain the device parameters which allow                   optimal size of hysteresis.  Second, the VLSI layout for the                    circuit is being made and simulated to verify circuit                           characteristics.  Plans include fabricating a VLSI chip based on                the design, and integrating it into a neural network for                        performance measurement.  This work is being done in conjunction                with neural-net research at the University of Maryland.
{'FirstName': 'Mona', 'LastName': 'Zaghloul', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mona E Zaghloul', 'EmailAddress': 'zaghloul@gwu.edu', 'NSF_ID': '000234933', 'StartDate': '11/15/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'George Washington University', 'CityName': 'WASHINGTON', 'ZipCode': '200520042', 'PhoneNumber': '2029940728', 'StreetAddress': '1918 F ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'ECR5E2LU5BL6', 'ORG_LGL_BUS_NAME': 'GEORGE WASHINGTON UNIVERSITY (THE)', 'ORG_PRNT_UEI_NUM': None}
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[{'Code': '4710', 'Text': 'DES AUTO FOR MICRO & NANO SYS'}, {'Code': '9120', 'Text': 'CROSS-DIRECTORATE PROGRAMS'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8808292.xml'}