PNN

By comparison , LVQ network was better than the others in classification ability and training cost , and PNN network in computation load and easy use .

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。

Pulse neutron-neutron ( PNN ) oil well logging technology and its application effect analysis

脉冲中子-中子（PNN）测井技术及应用效果分析

A novel PNN model with training algorithms is proposed for class conditional density estimation .

提出了一种新的类条件密度函数估计的PNN模型及其算法。

A mobile pilot neural networks ( PNN ) for intelligent underwater vehicle is presented .

本文描述了利用人工神经网络对智能水下机器人进行运动引导的研究。

A Deep Level Buffer Layer Analysis on the Gallium Arsenic p ~ + pnn ~ + structure

砷化镓P~+Pnn~+结构缓冲层的深能级分析

Fault Diagnosis Based on Probabilistic Neural Network ( PNN ) for Glue Dosage of Particleboard

基于概率神经网络的刨花板施胶故障诊断

Process neural network ( PNN ) can well embody this time accumulation effect , but its generalization ability is poor .

过程神经网络虽能很好地体现这种时间累积效应，但其泛化能力不强。

Probabilistic neural network ( PNN ) is a classification network , which is based on Bayesian decision theory and probability function estimation theory .

F.Specht提出的概率神经网络（ProbabilisticNeuralNetwork，PNN）是基于密度函数估计和贝叶斯决策理论而建立的一种分类网络。

Application of avalanche noise detection as a criterion for surface breakdown mechanism of high & voltage silicon p + pnn + junctions

雪崩噪声鉴别法在高压硅P~+PNN~+结表面击穿机理判定中的应用

A adaptive PNN is presented to improve the basic PNN and to compare with the basic PNN .

针对基本PNN的不足之处，提出了自适应PNN，并将其损伤识别精度与基本的PNN进行比较。

The heteroscedastic PNN model with training algorithms that is a mixture of Gaussian basis functions having different variances is considered .

提出了一种基于高斯核函数有不同协方差的混合模型的异方差PNN模型及其算法。

Four patterns set up for interpretation platform , process mode of SIGMA curve and four quantitative interpretation modules have formed specific characteristics of PNN logging interpretation .

PNN解释测井解释平台设置的四种模式SIGMA曲线处理方式和四种定量解释模块形成了PNN测井解释的独到之处。

So in this paper a recognition algorithm of heart sound based on probabilistic neural networks ( PNN ) is proposed to improve the accuracy of heart sound recognition .

在综合分析以前各种心音识别算法的基础上，本文提出了一种基于概率神经网络PNN的心音信号识别算法，将概率神经网络作为心音信号分类器，取得了较好的识别效果。

Process Neural Networks ( PNN ) are a type of novel Artificial Neural Networks models , which can be seen as the Artificial Neural Networks in time domain .

过程神经元网络（PNN，ProcessNeuralNetworks）是传统神经元网络扩展到时间域上的一种新型人工神经网络模型。

Based on the online inspection data of various soluble gases , an integrated technology of GM ( 1,1 ) and PNN is introduce into the online fault diagnosis .

根据各溶解气体的在线监测数据，采用灰色GM（1，1）和PNN融合技术进行在线故障诊断。

Process Neural Networks ( PNN ) is a kind of new ANN based on Process Neuron , its inputs and weights are all functions associated with ' time ' .

过程神经网络是一种基于过程神经元的新型神经网络，其输入及权值皆为时序函数。

Procedure Neural Networks ( PNN ) is a novel artificial neuron Networks model . It is based on information processing pattern of biological neural system and application background of practical matters .

过程神经元网络是根据生物神经系统信息处理机制并结合实际问题的应用背景提出的一种新的人工神经网络模型。

Based on this ideal , this paper presents the concept and model of high power neural network . With high power neural network ( PNN ) neural network transformer etc can be designed .

出于这一考虑，该文提出了功率神经网络的概念，基于功率神经网络，可以设计出神经变压器等全新的功率仪器设备。

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。

Convolution of probability distribution Principal Component Analysis ( PCA ), Cluster Analysis ( CA ) and Probabilistic Neural Network ( PNN ) were used in the data analysis and pattern recognition .

概率分布的卷积；概率分布的褶积；概率分布卷积并通过主元分析、聚类分析和概率神经网络对数据进行了分析和识别。

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。

As a kind of local-approaching network , probabilistic neural network ( PNN ) is suitable for identification and classification of patterns , owe to its simple structure and arithmetic .

概率神经网络作为一种局部逼近网络，结构简单，容易设计算法，特别适合进行模式识别及模式分类。

Probabilistic neural network ( PNN ) has been extensively adopted in fault diagnosis due to its features of simple network learning process and quick training . It has become an important method for fault diagnosis .

概率神经网络因其学习过程简单、训练速度快等特点被广泛应用于故障诊断领域，已经成为故障诊断技术的一种重要手段。

A probabilistic neural network ( PNN ) model is employed in order to recognize the nonlinear fluorescence spectrum of 3 impurities in the air , and satisfied experiment results have been acquired .

采用概率神经网络（PNN），对3种污染气体的非线性荧光光谱进行识别，获得了满意的实验结果。

By combining wavelet energy feature vectors with probabilistic neural network ( PNN ) in noisy conditions , a new damage identification method called wavelet probabilistic neural network ( WPNN ) was proposed .

以小波能量特征向量作为概率神经网络（PNN）的输入向量集，提出了小波概率神经网络（WPNN）的损伤识别方法。

A procedure for multilevel structural identification based on a PNN and MDLAC is described and applied to the damage detection of a cantilever structure and a single-span simply supported beam .

本文以一个悬臂梁结构和一个单跨简支梁结构为算例，对基于概率神经网络和多损伤定位确信准则的分级结构损伤检测方法进行了讨论。

The PNN applies the linear nodes and threshold nodes to make the modes assortment , and converts the exact variates in input analytical space to variates in output FUZZY space .

利用线性节点及阈值节点进行模式分类，将输入空间的精确变量转换为输出模糊空间的变量。

In this paper new positioning techniques for the intelligent underwater vehicle are presented . The system composition and the positioning model are described . A mobile pilot neural networks ( PNN ) for intelligent underwater vehicle is presented .

讨论了智能水下机器人水声定位技术，给出系统的组成、定位教学模型。本文描述了利用人工神经网络对智能水下机器人进行运动引导的研究。

Based on the essence of dynamic evolution of equipment condition , according to probabilistic neural networks ( PNN ), a probability model of equipment condition is adopted to describe the whole process of equipment evolution from normal to fault in the paper .

从设备状态动态变化的本质出发，采用概率神经网络方法构建设备状态概率模型，描述设备从正常到故障的全过程。

Three types of artificial neural networks were investigated including back propagation network ( BPN ), probabilistic neural network ( PNN ) and learning vector quantization network ( LVQ ) on the performance of a hydroelectric generator set 's fault diagnosis .

文章研究了3种人工神经网络，即反向传播网络（BPN）、概率神经网络（PNN）和学习矢量量化网络（LVQ）对水电机组振动故障诊断性能的影响。