This is the IEEE SPL presentation of the author's paper:
M. Nagahara, "Discrete Signal Reconstruction by Sum of Absolute Values," in IEEE Signal Processing Letters, vol. 22, no. 10, pp. 1575-1579, Oct. 2015.
doi: 10.1109/LSP.2015.2414932
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7064695&isnumber...

The abstract reads:
In this letter, we consider a problem of reconstructing an unknown discrete signal taking values in a finite alphabet from incomplete linear measurements. The difficulty of this problem is that the computational complexity of the reconstruction is exponential as it is. To overcome this difficulty, we extend the idea of compressed sensing, and propose to solve the problem by minimizing the sum of weighted absolute values. We assume that the probability distribution defined on an alphabet is known, and formulate the reconstruction problem as linear programming. Examples are shown to illustrate that the proposed method is effective.