In this paper, we consider the mixture of sparse linear regressions model.
Let ${\beta}^{(1)},\ldots,{\beta}^{(L)}\in\mathbb{C}^n$ be $ L $ unknown sparse
parameter vectors with a total of $ K $ non-zero coefficients. Noisy linear
measurements are obtained in the form $y_i={x}_i^H {\beta}^{(\ell_i)} + w_i$,
each of which is generated randomly from one of the