Mathematical model

The output $y$ is produced via the activation function $f$

$$y = f\left(\sum_{i=1}^n w_ix_i + b_i\right) = f(z),$$

This function receives $x_i$ as inputs. Here the activation $z=(\sum_{i=1}^n w_ix_i+b_i)$. In an FFNN of such neurons, the inputs $x_i$ are the outputs of the neurons in the preceding layer. Furthermore, an MLP is fully-connected, which means that each neuron receives a weighted sum of the outputs of all neurons in the previous layer.

• «
• 1
• ...
• 52
• 53
• 54
• 55
• 56
• 57
• 58
• 59
• 60
• 61
• 62
• 63
• 64
• 65
• 66
• 67
• 68
• 69
• »