Aparametric mean length is defined as the quantity The equation is abbretived where R＞0, 0＜α＜2, R+α≠2,β＞0 and The equation is abbretived. This being the mean length of code words. Lower and upper bounds for ^(α)_(Rβ)＂L＂ are derived in terms of generalized R-norm information measure of type α.

Some More Results on a Generalized Parametric R-Norm Information Measure of Type α

On the quantitative-qualitative measure of relative information

In the present communication, we have discussed Weighted Non- Symmetric JS-AG Divergence Measures of type s,∀s ∈ R . Some bounds have been obtained for this Weighted Non- Symmetric JS-AG Divergence Measures and its particular cases for s=-1, 0, 1/2, 1, 2.Weighted Non- Symmetric Relative J-Divergence of type s, ∀s ∈ R has also been considered for its particular cases for s=0, 1, 2 in section-2. Some mixed bounds- Non-Symmetric and Symmetric have also been presented. “Application in business – Share Market,” to switch over from one share to another share utilizing Weighted Divergence Measure in decision making process, has been exemplified in section-3 via weighted χ 2 -divergence and its adjoint. Analysis for profit maximization has been presented numerically and graphically. Section-4 presents the study of profit maximization through weighted Kullback-Leibler divergence, K(P//Q;W) and its adjoint.

Application of Information Theoretic Divergence Measures- Forecasting Profit Maximation in Share Market

On characterization of some nonadditive measures of “useful” information

Useful information of order α and noiseless coding theorems connected with it have been studied. In this paper some bounds and comparison results for the useful informaton of order α involving power distributions are obtained.

R.K. Tuteja

Papers

Two generalized measures of “useful” information