提出了一种基于最小分类错误准则的概率神经网络的训练算法。
This paper presents an efficient training algorithm for probabilistic neural networks using the minimum classification error criterion.
提出了一种基于最小分类错误准则的概率神经网络的训练算法。
This paper presents a training algorithm for probabilistic neural networks using the MCE criterion.
特征提取的目的是获取特征数目少且分类错误概率小的特征向量。
The purpose of feature extraction is to obtain feature vectors of few number and low error probability.
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