access icon free Two-dimension gradient projection method for sparse matrix reconstruction

Sequential order one negative exponential (SOONE) function is used to measure the sparsity of a two-dimensional (2D) signal. A 2D gradient projection (GP) method is developed to solve the SOONE function and thus the 2D-GP-SOONE algorithm is proposed. The algorithm can solve the sparse recovery of 2D signals directly. Theoretical analysis and simulation results show that the 2D-GP-SOONE algorithm has a better performance compared with the 2D smoothed L0 algorithm. Simulation results also show that the proposed algorithm has a better performance and requires less computation time than 2D iterative adaptive approach.

Inspec keywords: sparse matrices; gradient methods

Other keywords: 2D-GP-SOONE algorithm; two dimension gradient projection method; sparse matrix reconstruction; sequential order one negative exponential; sparse recovery; SOONE function

Subjects: Optimisation techniques; Algebra, set theory, and graph theory; Algebra; Optimisation; Optimisation techniques; Algebra; Algebra

References

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http://iet.metastore.ingenta.com/content/journals/10.1049/el.2016.0912
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