Update DNN_Specification.md

Author: abilng

config_doc/DNN_Specification.md

@@ -2,17 +2,19 @@ DNN Specification
 =================
 
 * `hidden_layers` : (Mandatory) An Array contain size of hidden RBM layer.
-* `activation` : Activation function used by layers.
 * `pretrained_layers` : Number of layers to be pre-trained.(Default Value = Size of `hidden_layers`)
 
 * `max_col_norm` : The max value of norm of gradients; usually used in dropout and maxout.(Default Value = null)
 * `l1_reg` : l1 norm regularization weight.(Default Value = 0)
 * `l2_reg` : l2 norm regularization weight.(Default Value = 0)
 
-* `do_maxout` : whether to use max-out or not. (Default Value = false)
-* `do_pnorm`  : whether to use p-norm (Default Value = false)
-* `pool_size` : The number of units in each max-pooling(or pnorm) group for maxout/pnorm(Default Value = 1)
-* `pnorm_order` : The norm order for pnorm.(Default Value = 1)
+* `adv_activation`: if maxout/pnorm is used. It contains 
+
+> * `method` : Either 'maxout','pnorm'. In `maxout`, a pooling of neuron o/p is done based on poolsize. But in `pnorm` output is normalized after pooling. 
+> * `pool_size`:  The number of units in each max-pooling(or pnorm) group for maxout/pnorm (Default Value = 1)
+> * `pnorm_order`: The norm order for pnorm.(Default Value = 1)
+
+* `activation`    : Activation function used by layers. (if adv_activation is used, it sholud be either 'linear','relu' or 'cappedrelu')
 
 * `do_dropout` : whether to use dropout or not. (Default Value =false)
 * `dropout_factor` : the dropout factors for DNN layers.(One for each hidden layer)(Default Value =[0.0])