Wavelet analysis is a mathematical technique that was presented in the mid-1980s to solve a variety of problems in signal analysis where the signal is aperiodic, noisy, transient, etc. More recently, wavelets have been applied to other problems such as feature detection and localization, making it a very promising tool for the analysis of gamma-ray spectra. Recent results have also shown that this technique has the potential to benefit over other approaches due to the fact that the signal can simultaneously be analyzed over multiple scales by using wavelet analysis, thus eliminating potential false isotope identifications from artifacts such as the Compton edge and backscatter peaks. This implies that this peak localization algorithm is no longer a function of detector resolution, which changes with energy. We will present our results evaluating the technique of wavelet analysis for low-resolution (Nal) gamma-ray spectra. Emphasis will be placed on wavelet selection and the incorporation of a simple algorithm to the problem of isotope identification.
- Gamma-ray spectroscopy
- Isotope identification
- Wavelet analysis
ASJC Scopus subject areas
- Nuclear and High Energy Physics
- Nuclear Energy and Engineering
- Electrical and Electronic Engineering