Let be a least-squares solution and . For a minimizer of , expand the objective about . The normal equation for a linear inverse problem removes the data-residual cross term, while the Bregman distance definition gives
Compare the minimizer with , where the square vanishes, and divide by . The bound is informative when that comparator has finite penalty.

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