1) Evolution Probabilistic Neural Network
进化概率神经网络
1.
Texture Image Recognition Based on Evolution Probabilistic Neural Network;
基于进化概率神经网络的纹理图像识别
2) probabilistic neural network
概率神经网络
1.
Application of probabilistic neural network in recognizing coalmine infrared monitoring images;
概率神经网络在矿井红外监控图像识别中的应用
2.
Application of probabilistic neural network technique in lithology inversion of seismic data;
概率神经网络技术在地震岩性反演中应用
3.
Fuzzy Probabilistic Neural Network Water Quality Evaluation Model and Its Application;
模糊概率神经网络水质评价模型及其应用
3) probabilistic neural network(PNN)
概率神经网络(PNN)
4) probability neural network
概率神经网络
1.
The diagnosis of misfire degree in engines based on probability neural network;
基于概率神经网络的发动机失火程度诊断
2.
Traffic condition recognition based on probability neural network
城市道路状况概率神经网络判别方法
5) probabilistic neural networks
概率神经网络
1.
Auto recognition of power quality disturbance based on probabilistic neural networks and double wavelet;
基于概率神经网络和双小波的电能质量扰动自动识别
2.
Application of Ambiguity Function Images and Probabilistic Neural Networksto Fault Diagnosis of Diesel Valve Train;
模糊函数图像与概率神经网络在柴油机气阀故障诊断中的应用
3.
According to transient property of ultrasonic signal,the discriminant pursuit method was proposed to extract local time-frequency features of defect signal and the features were fed to a probabilistic neural networks to classify the defects.
根据超声检测信号的瞬变特性,针对焊缝检测的缺陷分类问题,提出用判别追踪算法提取缺陷信号的局部时频判别特征,并结合概率神经网络实现了焊缝超声检测信号的缺陷分类。
6) Probabilistic neural network(PNN)
概率神经网络
1.
Aimed at the problem of electroencephalography(EEG) pattern recognition in brain computer interfaces(BCIs),a classification method based on probabilistic neural network(PNN) with supervised learning was presented.
针对脑机接口(BCI)研究中脑电信号(EEG)的模式识别问题,提出了一种基于有监督学习的概率神经网络(PNN)的分类方法。
2.
An distributed intelligent fire alarm system based on probabilistic neural network(PNN) was put forth and designed in order to avoid the low sensitivity and bad reliability of present fire alarm system.
针对目前火灾报警系统灵敏度低、可靠性差等不足,提出和设计了基于概率神经网络(PNN)的分布智能型火灾报警系统。
3.
From the result of prediction,which is based on Probabilistic Neural Network(PNN), the histogram method has a good ability to distinguish the different structure type of PPI,which may have a potential value for some bioinforma.
提出了一种新的、基于统计直方图提取蛋白质作用面特征的方法,并且利用提取出的作用面特征,结合概率神经网络,实现了对作用面结构类型的分类预测。
补充资料：神经系统的进化水螅的神经网
李瑞端绘
[图]
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条