说明：  基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。
(GMM based probabilistic neural network PNN good generalization ability, ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, has become a solution as speaker recognition, character recognition, medical imaging identification, satellite image recognition, and many other practical difficulties classification of very effective tool. GMM and PNN only has most of the advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other network other theories seamless integration.)