Despite the sophistication of today''s radiochemical separation techniques, it often occurs that the peaks in the spectra of α-emitting radioactive samples partially overlap. We here demonstrate the usefulness of a procedure based on a neural network, a multilayer perceptron with backpropagation training method, trained with isolated alpha peaks of environmental samples in resolving such partially overlapping alpha peaks and in predicting the activities of the α-emitters detected.
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