The theory of intuitionistic fuzzy set (IFS) is well suitable to deal with vagueness and hesitancy. In this study, we propose a new fuzzy TOPSIS decision making model using entropy weight for dealing with multiple criteria decision making (MCDM) problems under intuitionistic fuzzy environment. This model allows measuring the degree of satisfiability and the degree of non-satisfiability, respect...

rapid technological and economic growth over the last several decades has changed human lives and made modern society face complex decision making problems. these kinds of problems are characterized by incommensurate and conflicting criteria or objectives such as cost, reliability, performance, safety and productivity. multi criteria decision making is an approach that can be used to deal compl...

This paper outlines an adaptive wavelet-based perceptual audio coding scheme attending to various entropy-type criteria. Its performance using some different wavelet families and various filter lengths and decomposition depths has also been investigated. An optimal choice of these parameters is accomplished in order to evaluate both quality and bit rate of compressed signals for four different ...

Abstract. Estimating the entropy of a sample set is required in solving numerous learning scenarios involving information theoretic optimization criteria. A number of entropy estimators are available in the literature; however, these require a batch of samples to operate on in order to yield an estimate. In this paper, we derive a recursive formula to estimate Renyi’s quadratic entropy on-line,...

Abstract: Fuzzy multiple criteria decision-making (FMCDM) methods are techniques of finding the trade-off option out of all feasible alternatives that are characterized by multiple criteria and where data cannot be measured precisely, but can be represented, for instance, by ordered fuzzy numbers (OFNs). One of the main steps in FMCDM methods consist in finding the appropriate criteria weights....

Sparsity and entropy are pillar notions of modern theories in signal processing and information theory. However, there is no clear consensus among scientists on the characterization of these notions. Previous efforts have contributed to understand individually sparsity or entropy from specific research interests. This paper proposes a mathematical formalism, a joint axiomatic characterization, ...

We find that the standard relative entropy and the Umegaki entropy are designed for the 1 purpose of inferentially updating probability and density matrices respectively. From the same set of 2 inferentially guided design criteria, both of the previously stated entropies are derived in parallel. 3 This formulates a quantum maximum entropy method for the purpose of inferring density matrices 4 i...

We consider the generation of entropy when particle pairs are created at a cosmological level. Making a reduction via the particle number basis, we compute the classical limit for the entropy generation due to the evolution of the matter field fluctuations (squeeze transformation), obtaining that it is linear in the squeeze parameter for a general class of initial states. We also discuss the de...

The grading entropy concept can be adapted to the field of geotechnics, to establish criteria for phenomena such as particle packing, particle migration and filtering, through a quantified expression of the order/disorder in the grain size distribution, in terms of two entropy-based parameters. In this paper, the grading entropy theory is applied in some geotechnical case studies, which serve a...