Minimum Classification Error (MCE) criterion based sub-words weighting parameters estimation algorithm is proposed in which the sub-word weighting parameters are derived by the MCE training.
本文提出了一种基于最小分类错误准则(MCE)的子词权重参数估计算法，通过MCE训练得到子词的权重系数。
An improved design method on pattern classifier based on multi-layer perceptrons (MLP) by means of minimum classification error (MCE) training was proposed.
提出了一种基于最小分类错误(MCE)训练的采用多层感知器(MLP)结构的模式分类器设计方法。
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。
Minimum classification error (MCE) rate method is the most straightforward criterion for HMM training. Inprinciple, it is much better than the maximum likelihood method.
最小错识率(MCE)HMM训练方法是最直接的判决训练方法之一，原理上比最大似然接方法优越得多。
Minimum classification error (MCE) rate method is the most straightforward criterion for HMM training. Inprinciple, it is much better than the maximum likelihood method.
最小错识率(MCE)HMM训练方法是最直接的判决训练方法之一，原理上比最大似然接方法优越得多。
应用推荐