Compressed-sensing capacity bounds

Proves matching upper and lower bounds on how many k-sparse features m a d-dimensional linear representation can store such that a second linear map can recover them, using incoherent-matrix constructions for the upper bound and a rank/Turán-theorem argument for the lower bound.