  We introduce q-ary compressive sensing, an extension of 1-bit compressive
sensing. We propose a novel sensing mechanism and a corresponding recovery
procedure. The recovery properties of the proposed approach are analyzed both
theoretically and empirically. Results in 1-bit compressive sensing are
recovered as a special case. Our theoretical results suggest a tradeoff between
the quantization parameter q, and the number of measurements m in the control
of the error of the resulting recovery algorithm, as well its robustness to
noise.
