Maximin Performance of Binary-Input Channels with Uncertain Noise Distributions

@article{McKellips1998MaximinPO,
  title={Maximin Performance of Binary-Input Channels with Uncertain Noise Distributions},
  author={Andrew L. McKellips and Sergio Verd{\'u}},
  journal={IEEE Trans. Information Theory},
  year={1998},
  volume={44},
  pages={947-972}
}
We consider uncertainty classes of noise distributions defined by a bound on the divergence with respect to a nominal noise distribution. The noise that maximizes the minimum error probability for binary-input channels is found. The effect of the reduction in uncertainty brought about by knowledge of the signal-to-noise ratio is also studied. The particular class of Gaussian nominal distributions provides an analysis tool for nearGaussian channels. Asymptotic behavior of the least favorable… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.

References

Publications referenced by this paper.
Showing 1-10 of 24 references

Verd́u, “Worst case additive noise for binary-input channels and zero-threshold detection under constraints of power and divergence,”IEEE

  • S. A. McKellips
  • Trans. Inform. Theory ,
  • 1997
Highly Influential
7 Excerpts

ú, “Worst case power-constrained noise for binary-input channels,”IEEE

  • S. Shamai Shitz, S. Verd
  • Trans. Inform. Theory ,
  • 1992
Highly Influential
10 Excerpts

Typical sequences and all that: Entropy, pattern matching, and data compression

  • A. Wyner
  • IEEE Inform. Theory Soc. Newslett. ,
  • 1994
1 Excerpt

Multiuser detection

  • S. Verd́u
  • inAdvances in Signal Processing—Vol. 2: Signal…
  • 1993
1 Excerpt

Similar Papers

Loading similar papers…