A fast radionuclide identification algorithm applicable in spectroscopic portal monitors is presented.

The proposed algorithm combines a Bayesian sequential approach and a spiking neural network.

The algorithm was validated using the mixture of γ-emitter spectra provided by a well-type NaI(Tl) detector.

The radionuclide identification process is implemented using the whole γ-spectrum without energy calibration.