I. J. Good, D. B. Osteyee

Information, Weight of Evidence. The Singularity Between Probability Measures and Signal Detection

• Broschiertes Buch

Produktbeschreibung

List of symbols.- Information in events and weight of evidence.- Entropy.- Singularity between two probability measures.- Expected mutual information.- Expected weight of evidence.- Divergence.- Expected mutual information, expected weight of evidence, and divergence for random processes.- Relationships between certain random processes and the singularity between probability measures.- Other expressions for expected mutual information.- Expressing expected weight of evidence for gaussian generalized processes in terms of integral operators.- Comparison between I(RT:ST), WT(HN/HS+N), and JT(N, S+N) for gaussian signals and noise.- Expected mutual information rate.- Rate of expected weight of evidence.- Gaussian processes with equal covariance functions including nonrandom signals in gaussian noise.- Summary of the major results in this survey for gaussian processes, including gaussian signals and noise.- Conclusions and areas for additional research.

Produktdetails

• Lecture Notes in Mathematics 376
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-540-06726-9
• 1974.
• Seitenzahl: 176
• Erscheinungstermin: 29. April 1974
• Englisch
• Abmessung: 235mm x 155mm x 10mm
• Gewicht: 290g
• ISBN-13: 9783540067269
• ISBN-10: 3540067264
• Artikelnr.: 23563292

Inhaltsangabe

List of symbols.- Information in events and weight of evidence.- Entropy.- Singularity between two probability measures.- Expected mutual information.- Expected weight of evidence.- Divergence.- Expected mutual information, expected weight of evidence, and divergence for random processes.- Relationships between certain random processes and the singularity between probability measures.- Other expressions for expected mutual information.- Expressing expected weight of evidence for gaussian generalized processes in terms of integral operators.- Comparison between I(RT:ST), WT(HN/HS+N), and JT(N, S+N) for gaussian signals and noise.- Expected mutual information rate.- Rate of expected weight of evidence.- Gaussian processes with equal covariance functions including nonrandom signals in gaussian noise.- Summary of the major results in this survey for gaussian processes, including gaussian signals and noise.- Conclusions and areas for additional research.