In applying neural network to identification of gamma spectra back propagation(BP) algorithm is usually trapped to a local optimum and has a low speed of convergence.

whereas particle swarm optimization(PSO) is ad-vantageous in terms of globe optimal searching.In

this paper

we propose a new algorithm for neural network train-ing

i.e.combined BP and PSO optimization

or PSO-BP algorithm.Practical example shows that the new algorithm can overcome shortcomings of BP algorithm and the neural network trained by it has a high ability of generalization with identification result of 100% correctness.It can be used effectively and reliably to identify gamma spectra.