Ensemble Average Propagator Reconstruction Via Compressed Sensing: Discrete or Continuous Bases ?

Keywords

absolute abstract accurate adequately advantage advantages among analytical angular another apply approximation atoms authors available basis behavior best better blue built cells choose classes coefficients compressed compute conclude conditions considering continuous contributing correctly cosine course crossing cube cumulative dealing degree degrees denoted depending details diffusion discrete done enable ensemble error estimation evaluate exists expresses fair fast features fiber fibers firstly five formula function furthermore give gives gray ground handle hence idea important inferred infinite ingredient insight instead larger lead least looked loss lowest make many measures medium model modeling models moreover mother necessary need never normalized obviously ordinary orientation orthonormal others overall percentage phenomenon prior problem propagator properties proposed pulse real reconstruct reconstruction regularization represent representation representations represents required respective respectively richer scale science search sensing shore smallest solves space sparse sparsity spherical square squares studies suitable system table take term thanks transform transforms truncation truth want wavelet wavelets wise workshop