ebl::nn_layer_convolution Class Reference

#include <EblLayers.h>

Inheritance diagram for ebl::nn_layer_convolution:

ebl::module_1_1< Tin, Tout >

List of all members.

Public Member Functions

 nn_layer_convolution (parameter &p, intg kerneli, intg kernelj, intg ri, intg rj, Idx< intg > &tbl, intg thick)
void fprop (state_idx &in, state_idx &out)
 fprop from in to out
void bprop (state_idx &in, state_idx &out)
 bprop
void bbprop (state_idx &in, state_idx &out)
 bbprop
void forget (forget_param_linear &fp)
 initialize the weights to random values
void display_fprop (state_idx &in, state_idx &out, unsigned int &h0, unsigned int &w0, double zoom, bool show_out=false)
 display fprop at (h0, w0)

Public Attributes

convolution_module_2D_replicable convol
 < convolution module
addc_module adder
 bias vector
tanh_module sigmoid
 the non-linear function
state_idxsum
 convolution result


Detailed Description

a convolution neural net layer: convolution + tanh non-linearity.

Constructor & Destructor Documentation

ebl::nn_layer_convolution::nn_layer_convolution ( parameter p,
intg  kerneli,
intg  kernelj,
intg  ri,
intg  rj,
Idx< intg > &  tbl,
intg  thick 
)

constructor. Arguments are a pointer to a parameter in which the trainable weights will be appended, the number of inputs, and the number of outputs.


The documentation for this class was generated from the following files:

Generated on Mon Mar 30 18:15:26 2009 for libeblearn by  doxygen 1.5.6