几种神经网络类型

卷积神经网络概率神经网络

Convolutional Neural Networks are are a special kind of multi-layer neural networks. Like almost every other neural networks they are trained with a version of the back-propagation algorithm. Where they differ is in the architecture.  
Convolutional Neural Networks are designed to recognize visual patterns directly from pixel images with minimal preprocessing. 
They can recognize patterns with extreme variability (such as handwritten characters), and with robustness to distortions and simple geometric transformations.  

LeNet-5 is our latest convolutional network designed for handwritten and machine-printed character recognition.  Here is an example of LeNet-5 in action. 

尤其适合于从图像中识别出模式，典型案例：

http://yann.lecun.com/exdb/lenet/index.html

 

概率神经网络

 

模糊神经网络

混沌神经网络

小波神经网络

混合神经网络

 

分析神经网络的工作机制与优势特长，并将其组合，构成混合神经网络，才能达到林火运用的目的。