Srivastava and Maheshwari (Iranian Journal of Fuzzy Systems 13(1)(2016) 25-44) introduced a new divergence measure for intuitionisticfuzzy sets (IFSs). The properties of the proposed divergence measurewere studied and the efficiency of the proposed divergence measurein the context of medical diagnosis was also demonstrated. In thisnote, we point out some errors in ...

In recent times, intuitionistic fuzzy sets introduced by Atanassov has been one of the most powerful and flexible approaches for dealing with complex and uncertain situations of real world. In particular, the concept of divergence between intuitionistic fuzzy sets is important since it has applications in various areas such as image segmentation, decision making, medical diagnosis, pattern reco...

In applications of differential geometry to problems of parametric inference, the notion of divergence is often used to measure the separation between two parametric densities. Among them, in this paper, we will verify measures such as Kullback-Leibler information, J-divergence, Hellinger distance, -Divergence, … and so on. Properties and results related to distance between probability d...

Based on the exponential and trigonometry functions, a new divergence measure is introduced under intuitionistic fuzzy environment. The Intuitionistic Fuzzy Divergence Measure an indispensable instrument to calculate variance between two sets. Many attractive properties are displayed enhance value of measure. existing measures reviewed with their counter-intuitive examples. Finally, invented ap...

Some new inequalities related to Jensen and Ostrowski inequalities for general Lebesgue integral are obtained. Applications for $f$-divergence measure are provided as well.

In this paper, we introduce a goodness of fit test for expo- nentiality based on Lin-Wong divergence measure. In order to estimate the divergence, we use a method similar to Vasicek’s method for estimat- ing the Shannon entropy. The critical values and the powers of the test are computed by Monte Carlo simulation. It is shown that the proposed test are competitive with other tests of exponentia...

We propose a measure of divergence of probability distributions for quantifying the dissimilarity of two chaotic attractors. This measure is defined in terms of a generalized entropy. We illustrate our procedure by considering the effect of additive noise in the well known Hénon attractor. Finally, we show how our approach allows one to detect nonstationary events in a time series.