The branching property in generalized information theory

1978 ◽  
Vol 10 (4) ◽  
pp. 788-802 ◽  
Author(s):  
Bruce Ebanks

It is shown that every measure of expected information which has the branching property is of the form where J is a given information measure which is compositive under a regular binary operation and the Ψn are antisymmetric, bi-additive functions. In a probability space, such measures (entropies) take the form

1978 ◽  
Vol 10 (04) ◽  
pp. 788-802
Author(s):  
Bruce Ebanks

It is shown that every measure of expected information which has the branching property is of the form 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


Author(s):  
Litegebe Wondie ◽  
Satish Kumar

We presenta relation betweenTsallis’s entropy and generalizedKerridge inaccuracywhich is called generalizedShannon inequalityand is well-known generalization ininformation theoryand then give its application in coding theory. The objective of the paper is to establish a result on noiseless coding theorem for the proposed mean code length in terms of generalized information measure of orderξ.


2013 ◽  
Vol 54 (1) ◽  
pp. 228-251 ◽  
Author(s):  
Marc Pouly ◽  
Juerg Kohlas ◽  
Peter Y A Ryan

Kybernetes ◽  
1996 ◽  
Vol 25 (7/8) ◽  
pp. 50-67 ◽  
Author(s):  
George J. Klir ◽  
David Harmanec

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