DA就是“Denoising Autoencoders”的缩写。继续给yusugomori做注释，边注释边学习。看了一些DA的材料，基本上都在前面“转载”了。学习中间总有个疑问：DA和RBM到底啥区别？（别笑，我不是“学院派”的看Deep Learning理论，如果“顺次”看下来，可能不会有这个问题），现在了解的差不多了，详情见：。之后，又有个疑问，DA具体的权重更新公式是怎么推导出来的？我知道是BP算法，不过具体公示的推导、偏导数的求解，没有看到哪个材料有具体的公式，所以姑且认为yusugomori的代码写的是正确的。

注释后的头文件：

 

// The Class of denoising auto-encoderclass dA {public:	int N;			// the number of training samples	int n_visible;	// the number of visible nodes	int n_hidden;	// the number of hidden nodes	double **W;		// the weight connecting visible node and hidden node	double *hbias;	// the bias of hidden nodes	double *vbias;	// the bias of visible nodespublic:	// initialize the parameters	dA ( int,		// N		 int,		// n_visible		 int ,		// n_hidden		 double**,	// W		 double*,	// hbias		 double*	// vbias		 );	~dA();	// make the input noised	void get_corrupted_input (				int*,		// the original input 0-1 vector			-- input				int*,		// the resulted 0-1 vector gotten noised	-- output				double		// the p probability of noise, binomial test -- input				);	// encode process: calculate the probability output from hidden node	// p(hi|v) = sigmod ( sum_j(vj * wij) + bi), it's same with RBM	// but different from RBM, it dose not generate 0-1 state from Bernoulli distribution	void get_hidden_values (				int*,		// the input from visible nodes				double*		// the output of hidden nodes				);	// decode process: calculate the probability output from visiable node	// p(vi|h) = sigmod ( sum_j(hj * wij) + ci), it's same with RBM	// but different from RBM, it dose not generate 0-1 state from Bernoulli distribution 	void get_reconstructed_input (				double*,	// the input from hidden nodes				double*		// the output reconstructed of visible nodes				);	// train the model by a single sample	void train (				int*,		// the input sample from visiable node				double,		// the learning rate				double		// corruption_level is the probability of noise				);	// reconstruct the input sample	void reconstruct (				int*,		// the input sample		-- input				double*		// the reconstructed value -- output				);};