An iterative data-consistent inversion procedure converges to a measure satisfying multiple push-forward constraints, minimizing cumulative f-divergence and yielding the maximum-entropy solution under uniform initialization.
and Byrne, W., Convergence theorems for generalized alternating minimization pro- cedures,J
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Iterative Data-Consistent Inversion with Multiple Push-forward Constraints
An iterative data-consistent inversion procedure converges to a measure satisfying multiple push-forward constraints, minimizing cumulative f-divergence and yielding the maximum-entropy solution under uniform initialization.