{"title":"On Jensen- divergence measure","authors":"Omid Kharazmi, Narayanaswamy Balakrishnan","doi":"10.1017/s0269964823000189","DOIUrl":null,"url":null,"abstract":"Abstract The purpose of this paper is twofold. The first part is to introduce relative- $\\chi_{\\alpha}^{2}$ , Jensen- $\\chi_{\\alpha}^{2}$ and ( p , w )-Jensen- $\\chi_{\\alpha}^2$ divergence measures and then examine their properties. In addition, we also explore possible connections between these divergence measures and Jensen–Shannon entropy measure. In the second part, we introduce $(p,\\eta)$ -mixture model and then show it to be an optimal solution to three different optimization problems based on $\\chi_{\\alpha}^{2}$ divergence measure. We further study the relative- $\\chi_{\\alpha}^{2}$ divergence measure for escort and arithmetic mixture densities. We also provide some results associated with relative- $\\chi_{\\alpha}^{2}$ divergence measure of mixed reliability systems. Finally, to demonstrate the usefulness of the Jensen- $\\chi_{\\alpha}^{2}$ divergence measure, we apply it to a real example in image processing and present some numerical results. Our findings in this regard show that the Jensen- $\\chi_{\\alpha}^{2}$ is an effective criteria for quantifying the similarity between two images.","PeriodicalId":54582,"journal":{"name":"Probability in the Engineering and Informational Sciences","volume":"17 1","pages":"0"},"PeriodicalIF":0.7000,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Probability in the Engineering and Informational Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/s0269964823000189","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The purpose of this paper is twofold. The first part is to introduce relative- $\chi_{\alpha}^{2}$ , Jensen- $\chi_{\alpha}^{2}$ and ( p , w )-Jensen- $\chi_{\alpha}^2$ divergence measures and then examine their properties. In addition, we also explore possible connections between these divergence measures and Jensen–Shannon entropy measure. In the second part, we introduce $(p,\eta)$ -mixture model and then show it to be an optimal solution to three different optimization problems based on $\chi_{\alpha}^{2}$ divergence measure. We further study the relative- $\chi_{\alpha}^{2}$ divergence measure for escort and arithmetic mixture densities. We also provide some results associated with relative- $\chi_{\alpha}^{2}$ divergence measure of mixed reliability systems. Finally, to demonstrate the usefulness of the Jensen- $\chi_{\alpha}^{2}$ divergence measure, we apply it to a real example in image processing and present some numerical results. Our findings in this regard show that the Jensen- $\chi_{\alpha}^{2}$ is an effective criteria for quantifying the similarity between two images.
期刊介绍:
The primary focus of the journal is on stochastic modelling in the physical and engineering sciences, with particular emphasis on queueing theory, reliability theory, inventory theory, simulation, mathematical finance and probabilistic networks and graphs. Papers on analytic properties and related disciplines are also considered, as well as more general papers on applied and computational probability, if appropriate. Readers include academics working in statistics, operations research, computer science, engineering, management science and physical sciences as well as industrial practitioners engaged in telecommunications, computer science, financial engineering, operations research and management science.