Figure 2.
The general setup of our analysis: an input n is mapped to a representation ψ(n), which may then be corrupted by noise ε. We seek to minimize the amount by which this noise “matters” on the original input scale, given by ψ−1(ψ(n) + ε) – n. We compute ψ−1(n) using a linear approximation (see text).