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- W2896475700 abstract "Particle may sometimes have energy outside the range of radiation detection hardware so that the signal is saturated and useful information is lost. We have therefore investigated the possibility of using an Artificial Neural Network (ANN) to restore the saturated waveforms of $gamma$ signals. Several ANNs were tested, namely the Back Propagation (BP), Simple Recurrent (Elman), Radical Basis Function (RBF) and Generalized Radial Basis Function (GRBF) neural networks (NNs) and compared with the fitting method based on the Marrone model. The GBRFNN was found to perform best." @default.
- W2896475700 created "2018-10-26" @default.
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- W2896475700 date "2018-10-18" @default.
- W2896475700 modified "2023-09-27" @default.
- W2896475700 title "Recovery of Saturated $gamma$ Signal Waveforms by Artificial Neural Networks" @default.
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