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 Tusn´ ady, G., Information geometry and alternating minimization procedures,Statistics and Decisions, Supplemental Issue Number 1:205–237
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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.