Om Parkash

New measures of weighted fuzzy entropy and their applications for the study of maximum weighted fuzzy entropy principle

Keeping in view the non-probabilistic nature of experiments, two new measures of weighted fuzzy entropy have been introduced and to check their authenticity, the essential properties of these measures have been studied. Under the fact that measures of entropy can be used for the study of optimization principles when certain partial information is available, we have applied the existing as well as the newly introduced weighted measures of fuzzy entropy to study the maximum entropy principle.

Noiseless coding theorems corresponding to fuzzy entropies

Noiseless coding theorems connected with fuzzy entropies corresponding to Shannon, Renyi and Havrda and Charvat are established. The upper bounds of these entropies in terms of mean code-word lengths are provided, and some interesting properties of these codeword lengths are studied.

Characterization of the quantitative-qualitative measure of inaccuracy for discrete generalized probability distributions

A characterization of the quantitative-qualitative measure of inaccuracy depending upon the additivity postulate and the mean value property for discrete generalized probability distribution has been provided.

Contribution of maximum entropy principle in the field of queueing theory

ABSTRACT In the literature of information theory, there exist many well known measures of entropy suitable for entropy optimization principles towards applications in different disciplines of science and technology. The object of this article is to develop a new generalized measure of entropy and to establish the relation between entropy and queueing theory. To fulfill our aim, we have made use of maximum entropy principle which provides the most uncertain probability distribution subject to some constraints expressed by mean values.

Some generalized information theoretic measures based upon probability distributions

Shannon entropy is the key concept in the literature of information theory and has found wide applications in different disciplines of science and technology. The various researchers have generalized this entropy measure with different approaches. The object of the present paper is to stress the importance of the property of concavity. Thus based mainly on the postulate of concavity of entropy function, we have introduced and investigated two new generalized measures of probabilistic entropy and studied their important and interesting properties.