updated_readme

README.md

@@ -36,12 +36,12 @@ adagrad: implementation of the Adagrad algorithm.
 adam: implementation of the Adam algorithm. 
 bnorm: implementation of the batch normalization layer. 
 conv_layer_2d: implementation of the convolution layer. (CUDNN enabled) 
-dropout: implementation of the dropout layer. 
+dropout: implementation of the dropout layer.  
 generate_output_filename: generate output filename based on the current parameter settings. 
-im2col_ln: customized im2col function used in the pooling layer. linear_layer: implementation of linear perceptron layer. 
-Main_Template: a template script used to train CNN and MLP networks.
-linear_layer: implementation of the (fully connected) linear layer. (CUDNN enabled) 
+im2col_ln: customized im2col function used in the pooling layer. 
+linear_layer: implementation of (fully-connected) linear layer. (CUDNN enabled) 
 lrn: implementation of the local response normalization layer. (CUDNN enabled) 
+Main_Template: a template script used to train CNN and MLP networks. 
 maxpool: implementation of the max-pooling layer. (CUDNN enabled) 
 net_bp: implementation of the back propagation process which is used in CNN and MLP networks. 
 net_ff: implementation of the feed forward process which is used in CNN and MLP networks.