A hybrid conjugate gradient algorithm for constrained monotone equations with application in compressive sensing
Abdulkarim Hassan Ibrahim, Poom Kumam, Auwal Bala Abubakar, Wachirapong Jirakitpuwapat, Jamilu Abubakar
Abstract
-norm regularized problems to restore sparse signal and image in compressive sensing. Numerical comparisons of the proposed algorithm versus some other conjugate gradient algorithms on a set of benchmark test problems, sparse signal reconstruction and image restoration in compressive sensing show that the proposed scheme is computationally more efficient and robust than the compared schemes.
Topics & Concepts
Conjugate gradient methodCompressed sensingAlgorithmNonlinear conjugate gradient methodDerivation of the conjugate gradient methodMathematicsNorm (philosophy)Sparse approximationBenchmark (surveying)Gradient methodConjugate residual methodConvergence (economics)Mathematical optimizationComputer scienceGradient descentArtificial intelligenceArtificial neural networkEconomic growthLawGeographyGeodesyPolitical scienceEconomicsSparse and Compressive Sensing TechniquesNumerical methods in inverse problemsPhotoacoustic and Ultrasonic Imaging