研究表明依据专家知识自动提取方法能够有效解决现有贝叶斯专家系统分类器中存在的瓶颈问题。
According to the knowledge auto-extraction method developed in this study, the bottleneck of knowledge acquirement in Bayesian expert system classifier could be well solved.
该方法不需要构造参数表达的基函数，而是将具有信号先验知识的模板信号通过滤波器组得到一组基函数来提取隐藏在噪声中的信号。
Using a template signal that contains a prior signal information, a set of nonparametric basis functions are obtained by means of a filter bank.
研究中分析了专家知识提取相关过程，并得出现有贝叶斯专家系统分类器应用的瓶颈问题。
Firstly, the bottleneck of actual Bayesian expert system classifier was identified according to the process analysis.
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