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An RBF Neural Network Approach in Radionuclide Identification of Unknown Sources Utilizing gamma-Ray Spectra
Title:
An RBF Neural Network Approach in Radionuclide Identification of Unknown Sources Utilizing gamma-Ray Spectra
Author:
Lagari, Pola-Lydia, author.
ISBN:
9780438029132
Personal Author:
Physical Description:
1 electronic resource (68 pages)
General Note:
Source: Masters Abstracts International, Volume: 57-06M(E).
Advisors: Lefteri H. Tsoukalas Committee members: Miltiadis Alamaniotis; Chan K. Choi; Mary Comer.
Abstract:
At first, simulated ?gamma-ray spectra for a set of 25 radionuclides, have been produced using the "Gamma Detector Response and Analysis Software (GADRAS)". For each of these profiles (counts/kev vs energy), a Gaussian "Radial Basis Function" (RBF) network has been trained to represent it by an analytic closed form expression. Hence a library consisting of 25 RBF-networks, for the corresponding radionuclides, has been built. Secondly, a method for identifying the presence of radionuclides in the spectrum of an unknown source has been developed, assuming that the source contains a mixture of the considered radionuclides only. A linear combination of the library profiles is compared to the actual spectrum, and constrained optimization techniques are applied to minimize the deviation in a least squares sense.
Local Note:
School code: 0183
Added Corporate Author:
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Shelf Number | Item Barcode | Shelf Location | Status |
|---|---|---|---|
| XX(688115.1) | 688115-1001 | Proquest E-Thesis Collection | Searching... |
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