A convolutional neural network perfoms the same transformation to every small patch duirng image processing or to consecutve tokens in a time series or sequential data. This may be acheived by having lots of different nodes for exach parch, but where the weights are 'clamped' to be the same, or by reusing a small network. In bith cases backpropogatio or otger learning rules have to be modified. The technique derives its name from mathematical {{convolutions]} used in linear time-series analysis.
Used in Chap. 8: page 125; Chap. 12: pages 196, 202; Chap. 19: page 323
Convolutional neural network