神经网络向量化
From Ufldl
(→Forward propagation) |
(→Forward propagation) |
||
| Line 8: | Line 8: | ||
Consider a 3 layer neural network (with one input, one hidden, and one output layer), and suppose <tt>x</tt> is a column vector containing a single training example <math>x^{(i)} \in \Re^{n}</math> . Then the forward propagation step is given by: | Consider a 3 layer neural network (with one input, one hidden, and one output layer), and suppose <tt>x</tt> is a column vector containing a single training example <math>x^{(i)} \in \Re^{n}</math> . Then the forward propagation step is given by: | ||
| - | |||
==正向传导== | ==正向传导== | ||
