Checked by the experiments, the improved RBF network has less hidden neural units than before, at the same time keep the accurate of RBF based classifier.

经实验证明，基于改进后的RBF网络具有更少的隐含神经元，但仍然保持了基于RBF网络分类器的准确率。

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Here, the HMM is employed to produce a best speech state sequence which is warped to a fixed dimension vector and the RBF neural network is used as classifier.

该方法首先利用HMM生成最佳语音状态序列，然后用函数逼近技术产生对最佳状态序列进行时间规正，最后通过RBF神经网络进行分类识别。

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