Sparse signal reconstruction performed by two different algorithms is considered. First algorithm is the ISTA algorithm for LASSO minimization, while the second one is the gradient-based descent algorithm. Algorithms perform signal reconstruction in a completely different way. The ISTA algorithm reconstructs signals in the sparsity transformation domain. The gradient descent algorithm performs reconstruction in time/measurements domain, considering the missing samples as variables. Both of them use the l1-norm in minimization. Computational time and mean absolute error are used in comparison analysis presented in this paper.