We introduce a deep scattering network, which computes invariants with iterated contractions adapted to training data. It defines a deep convolution network model, whose contraction properties can be analyzed mathematically. A cascade of wavelet transform convolutions are computed with a multirate filter bank, and adapted with permutations. Unsupervised lear