APPLICATION OF TWO-TERM MODIFIED PRP CONJUGATE GRADIENT ALGORITHMS IN SPARSE OPTIMIZATION
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In recent years,the sparse optimization problem has attracted exten-sive attention in many fields such as scientific research and engineering practice.The conjugate gradient method is suitable for large-scale problems due to its sim-plicity,low memory,and global convergence.We combine two-term modified con-jugate gradient method with a smoothing strategy to solve the sparse optimization problems and establish the global convergence of the algorithm.Finally,we select some representative sparse recovery problems,combine our new algorithm,and design relevant numerical experiments.By comparing with the existing excellent algorithms,it is proved that the new algorithm has better competitiveness.
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