You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
The Branching Property in Generalized Information Theory
Advances in Applied Probability
Vol. 10, No. 4 (Dec., 1978), pp. 788-802
Published by: Applied Probability Trust
Stable URL: http://www.jstor.org/stable/1426659
Page Count: 15
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
It is shown that every measure of expected information which has the branching property is of the form Cn+∑i=1 nfn,i(J(Ai))+∑i=1 n-1(J(Ai))+∑i=1 n-1Ψ n(J(Ai),J(Ai+1)⚬ J(Ai+2)⚬ ⋯ ⚬ J(An)), where J is a given information measure which is compositive under a regular binary operation ⚬ , and the Ψ n are antisymmetric, bi-additive functions. In a probability space, such measures (entropies) take the form Cn+∑i=1 nfn,i(Pi)+∑i=1 n-1Ψ n(Pi,Pi+1+Pi+2+⋯ +Pn).
Advances in Applied Probability © 1978 Applied Probability Trust