A signal recovery algorithm based on linear programming

The non-uniqueness of non-stationary signals is a difficult problem in the restoration of communication signals. We propose a piecewise smooth signal restoration algorithm based on linear programming. By constructing a total smooth bounded variation model of piecewise smooth signal restoration, the optimization process of the non-differentiable constraint problem is transformed into a nonlinear programming problem with constraints, and the complexity of solving the variation parameter is reduced. Simulation results show that the proposed algorithm is better than the traditional Wiener and Richardson-Lucy restoration methods in signal restoration. In the case of low signal-to-noise ratio (SNR), the algorithm can also reflect the basic information of the original signal.