This paper presents a training algorithm for probabilistic neural networks using the MCE 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。
When applied to the Probabilistic Neural Networks, the approach improves its two inherent shortcomings.
当应用在概率神经网络分类时，可对其固有的两个缺点都有所改善。
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。
A novel graphic symbol recognition approach of engineering drawings based on radial basis probabilistic neural networks (RBPNN) is proposed.
基于径向基概率神经网络，提出一种扫描工程图纸图像分割后的图形符号识别方法。
Probabilistic neural network (PNN) model is a kind of artificial neural network, which is simple in structure, easy for training and widely used.
概率神经网络(PNN)是一种训练速度快、结构简洁明了、应用广泛的人工神经网络。
Secondly, the profile and layer of the damaged member is also determined by probabilistic neural network with input of the normalized damage-signal index.
然后将构件损伤引起的标准化的损伤信号指标输入概率神经网络，进行损伤构件所在侧面及所在层的判定；
Using an example, a method based on probabilistic neural network technique is introduced, which aims at prediction of petrophysical parameters for reservoir.
通过实例介绍了利用一种概率神经网络技术预测储层物性参数的方法。
Probabilistic Neural Networks (PNN) is improved and used on line to estimate the states of singular perturbed systems, especially to the fast states of the systems.
将改进的概率神经网络(PNN)用于奇异摄动系统的实时状态估计，注重针对系统快变部分的滤波。
The result indicates that probabilistic neural networks can localize the single damage correctly, and the networks with the compounded index show better effectiveness.
发现基于概率神经网络的结构损伤定位方法能够正确识别单一位置损伤，且组合参数作为输入指标时的识别效果更好。
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.
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 order to validate character validity, use NearestNeighbor (NN) and probabilistic neural network (PNN) classification identify target, gain content identification probability.
为了验证特征的有效性，使用最近邻及概率神经网络分类器进行了目标识别，得到满意的识别率。
The generalization error of Support Vector Machine is approximately equal to that of Probabilistic Neural Network. And Support Vector Machine is easier to use than Neural Networks.
支持向量机的分类误差与概率神经网络相近，但支持向量机的使用较概率神经网络简单。
Furthermore, on the basis of feature extraction, by utilizing the Radial basis Probabilistic Neural Networks (RBPNN), the palmprint recognition task could be implemented automatically.
在特征提取的基础上，进一步利用径向基概率神经网络(RBPNN)分类器，实现了掌纹的自动识别。
Probabilistic neural network is good at classifying, we proposed a new method for aeroengine fault diagnosis based on PNN, and it can diagnose three typical aeroengine rotor fault accurately.
鉴于概率神经网络良好的分类性能，提出一种基于PNN的飞机发动机故障诊断方法，成功对三种典型飞机发动机转子故障做出了正确诊断。
Make use of available experimental data of LY12CZ aluminum alloy, a probabilistic neural network was developed to classify the maximum corrosion depth ranges based on the material failure mode.
运用LY12CZ的腐蚀实验数据，根据高强铝合金的失效模式（点蚀-晶间腐蚀-剥蚀），建立了对最大腐蚀深度分类的概率神经网络模型，输出结果与实验数据比较吻合。
Their success sparked a renewed interest in learning AI methods such as decision trees, neural networks, genetic algorithms, and probabilistic methods.
这些游戏的成功从新燃起了对游戏ai方法的热情，比如：决定树，神经元网络，遗传算法，和盖然论。
The structure and parameters of the flexible neural tree model are optimized by probabilistic incremental program evolution and simulation annealing, respectively.
柔性神经树模型的结构和参数优化分别由概率增强式程序进化和模拟退火算法完成。
The structure and parameters of the flexible neural tree model are optimized by probabilistic incremental program evolution and simulation annealing, respectively.
柔性神经树模型的结构和参数优化分别由概率增强式程序进化和模拟退火算法完成。
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