chainer.functions.local_response_normalization

chainer.functions.local_response_normalization(x, n=5, k=2, alpha=0.0001, beta=0.75)

Local response normalization across neighboring channels.

This function implements normalization across channels. Let \(x\) an input image with \(N\) channels. Then, this function computes an output image \(y\) by following formula:

\[y_i = {x_i \over \left( k + \ \alpha \sum_{j=\max{1, i - n/2}}^{\min{N, i + n/2}} \ x_j^2 \right)^\beta}.\]

Parameters

• x (Variable or N-dimensional array) – Input variable.

• n (int) – Normalization window width.

• k (float) – Smoothing parameter.

• alpha (float) – Normalizer scaling parameter.

• beta (float) – Normalizer power parameter.

Returns

Output variable.

Return type

Variable

See: Section 3.3 of ImageNet Classification with Deep Convolutional Neural Networks