比较而言，学习矢量量化网络和概率神经网络在分类能力方面要比反向传播网络好一些，概率神经网络在计算负载方面比学习矢量量化网络要更胜一筹。
By comparison, LVQ network and PNN network are better than BPN network in classification ability, and PNN network is better than the others in computation load.
在模型构造中，采用小波概率神经网络进行控制图的模式识别和控制图异常模式的参数估计。
In the modeling of the structure, the wavelet probabilistic neural network was used to recognize the control chart patterns and estimate the abnormal patterns parameters.
评述了灰色预测方法，概率统计方法，人工神经网络方法和可靠度函数分析四种国内外正在研究和使用的方法。
A review is made of the four methods being studied and used in China and other countries: gray prediction, probabilistic statistics, artificial nerve network, and functional analysis of reliability.
比较而言，学习矢量量化网络在分类能力和训练成本方面更胜一筹，而概率神经网络则在计算负载和易用性方面更好一些。
By comparison, LVQ network was better than the others in classification ability and training cost, and PNN network in computation load and easy use.
本文应用HMM概率模型和神经网络结合，对联机手写数字和数学符号进行识别。
We recognize on-line handwritten figure and some mathematic characters using the HMM neural networks, and achieve a better result.
该推理模型前级采用神经网络并行子网，用于目标的预分类，后级采用证据理论用于多周期的不确定性推理和概率的全局分配。
The forestage of the fusion model completes target presort and its post-stage is used to multi-period uncertainty inference and the whole set distribution of probability.
该推理模型前级采用神经网络并行子网，用于目标的预分类，后级采用证据理论用于多周期的不确定性推理和概率的全局分配。
The forestage of the fusion model completes target presort and its post-stage is used to multi-period uncertainty inference and the whole set distribution of probability.
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