Rate-distortion and a declared fidelity criterion
Research context
postgraduate concept · established · As of 2026-10-10
For an iid source with law p(x) and specified distortion d(x,x-hat), R(D) minimizes mutual information over reconstruction laws meeting expected distortion D.
Key knowledge
For an iid source with law p(x) and specified distortion d(x,x-hat), R(D) minimizes mutual information over reconstruction laws meeting expected distortion D. For a zero-mean Gaussian source of variance sigma² and squared-error distortion, R(D)=one-half log2(sigma²/D) for 0<D<sigma² and zero for D≥sigma². Changing distortion, side information or source memory changes the answer.
Values and equations
R(D)=inf_(p(xhat|x):E d≤D) I(X;Xhat)
- D
- Allowed expected distortion per symbol
- d
- Declared nonnegative distortion measure
- R(D)
- Bits per source symbol
Conditions and scope
- The formula is an asymptotic average-distortion theorem; a maximum per-item error constraint is different.
- For the Gaussian example, D and sigma² have the same squared source units.
Sources · 2
References
Sources retain their recorded scope. A source link alone does not establish verification of every statement.
Evidence and review
Author checked this English statement, displayed equation where present and stated hypotheses against these source locations: Definition R(D), average distortion and Gaussian mean-square example; DM-MAC pp. 28–35, broadcast pp. 38–47, distortion pp. 48–52, Wyner–Ziv/Slepian–Wolf pp. 53–59, relay pp. 78–94, multicast pp. 100–116. The check is bounded to the recorded claims; no complete proof reconstruction, software proof replay or universal literature completeness is claimed.
2026-10-10 · Author source-body/statement/equation/domain check, with graph associations scoped individually. Separate independent content/source/inventory review is required before branch closure.
Entry details
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