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Compressed sensing data reconstruction using a modified subspace pursuit algorithm under the condition of unknown sparsity

This paper introduces the fundamental knowledge of compressed sensing theory, and analyzes the important reconstruction algorithms such as orthogonal matching pursuit, subspace pursuit, but we should know the sparse degree. The sparsity adaptive matching pursuit algorithm can be terminated by setting the conditions to make adaptive sparse degree. This paper puts forward a modified sparsity adaptive algorithm based on those three algorithms. The simulation results show that new algorithm can accurately reconstruct the original signal, and has better results than SAMP.