Hardware implementation of subtractive clustering for radionuclide identification

Authors:
Marcos Santana Farias;Nadia Nedjah;Luiza De Macedo Mourelle
Affiliations:
Department of Instrumentation, Nuclear Engineering Institute, Brazil;Department of Electronics Engineering and Telecommunications, State University of Rio de Janeiro, Brazil;Department of Systems Engineering and Computation, State University of Rio de Janeiro, Brazil
Venue:
Integration, the VLSI Journal
Year:
2013

Citing 2
Cited 0

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Generalized fuzzy c-means clustering strategies using Lp norm distances

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Abstract

Radioactivity is the spontaneous emission of energy from unstable atoms. Radioactive sources have radionuclides. Radionuclide undergoes radioactive decay and emits gamma rays and subatomic particles, constituting the ionizing radiation. The gamma ray energy of a radionuclide is used to determine the identity of gamma emitters present in the source. This paper describes the hardware implementation of subtractive clustering algorithm to perform radionuclide identification. The hardware was proven to be effective for this task, allowing scalability to increase parallelism in the computations.