Add to ORKGInformation and Divergence measures deals with the study of problems concerning information processing, information storage, information retrieval and decision making. The purpose of this paper is to find a new series of divergence measures and their applications, discuss the mathematical tools for finding convexity of the functions. Applications of convex functions in information theory, relationship between new and well-known divergence measures are discussed. Also some new bounds have been established for divergence measures using new f divergence measures and its properties
Inequalities which connect information divergence with other measures of discrimination or distance ...
In this work, we introduce new information inequalities on new generalized f-divergence in terms of ...
Some new inequalities for the well-known Jeffreys divergence measure in Information Theory are given
In this work, we introduce new series of divergence measures as a family of Csiszar’s functional div...
Data science, information theory, probability theory, statistical learning and other related discipl...
Abstract Divergence measures are useful for comparing two probability distributions. Depending on th...
There are many types of information divergences with used two probability distributions. A new infor...
There are many types of information divergences with used two probability distributions. A new infor...
A general divergence measure for monotonic functions is introduced.\ud Its connections with the f−di...
AbstractA symmetric measure of information divergence is proposed. This measure belongs to the class...
Abstract: Inequalities are playing a fundamental role in the area of Information Theory and Statisti...
A double Jensen type inequality for 2n-convex functions is obtained and applied to establish upper ...
A double Jensen type inequality for 2n-convex functions is obtained\ud and applied to establish uppe...
Data science, information theory, probability theory, statistical learning, statistical signal proce...
[[abstract]]The problem of choosing a proper divergence measure is an important one. We provide new ...
Inequalities which connect information divergence with other measures of discrimination or distance ...
In this work, we introduce new information inequalities on new generalized f-divergence in terms of ...
Some new inequalities for the well-known Jeffreys divergence measure in Information Theory are given
In this work, we introduce new series of divergence measures as a family of Csiszar’s functional div...
Data science, information theory, probability theory, statistical learning and other related discipl...
Abstract Divergence measures are useful for comparing two probability distributions. Depending on th...
There are many types of information divergences with used two probability distributions. A new infor...
There are many types of information divergences with used two probability distributions. A new infor...
A general divergence measure for monotonic functions is introduced.\ud Its connections with the f−di...
AbstractA symmetric measure of information divergence is proposed. This measure belongs to the class...
Abstract: Inequalities are playing a fundamental role in the area of Information Theory and Statisti...
A double Jensen type inequality for 2n-convex functions is obtained and applied to establish upper ...
A double Jensen type inequality for 2n-convex functions is obtained\ud and applied to establish uppe...
Data science, information theory, probability theory, statistical learning, statistical signal proce...
[[abstract]]The problem of choosing a proper divergence measure is an important one. We provide new ...
Inequalities which connect information divergence with other measures of discrimination or distance ...
In this work, we introduce new information inequalities on new generalized f-divergence in terms of ...
Some new inequalities for the well-known Jeffreys divergence measure in Information Theory are given