多重ANN/HMM混合模型在时序模式识别中的应用

The Application of Multiple ANN/HMM Hybrid Models in Times Series Recognition

针对样本集上样本之间存在较大差异的问题,提出了基于人工神经网络的隐马尔可夫(多重ANN/HMM)混合模型的思想,每重子模型能够自动聚合差异性较小的样本,最终各个子模型通过竞争的方式优胜的子模型作为该模型的最终结果.

In view of the issue that the samples in sample sets have many differences,this paper comes up with the idea of multiple ANN/HMM hybrid models on the basis of artificial neural network.Each sub-model can automatically assemble the samples that have little differences,and in the process of training and recognizing,the sub-models that can win the samples are the winners in the completions.