Novel RF Spectrum Characterization Using Information Measures

2018 ◽

Vol 6 (8) ◽

pp. 102

Author(s):

Priyanka R. Patil ◽

Shital A. Patil

Keyword(s):

Latent Semantic Analysis ◽

Latent Dirichlet Allocation ◽

Semantic Analysis ◽

Mining Method ◽

Research Papers ◽

Information Measures ◽

Automated Software ◽

Day By Day ◽

Ways Of Life ◽

Dirichlet Allocation

Similarity View is an application for visually comparing and exploring multiple models of text and collection of document. Friendbook finds ways of life of clients from client driven sensor information, measures the closeness of ways of life amongst clients, and prescribes companions to clients if their ways of life have high likeness. Roused by demonstrate a clients day by day life as life records, from their ways of life are separated by utilizing the Latent Dirichlet Allocation Algorithm. Manual techniques can't be utilized for checking research papers, as the doled out commentator may have lacking learning in the exploration disciplines. For different subjective views, causing possible misinterpretations. An urgent need for an effective and feasible approach to check the submitted research papers with support of automated software. A method like text mining method come to solve the problem of automatically checking the research papers semantically. The proposed method to finding the proper similarity of text from the collection of documents by using Latent Dirichlet Allocation (LDA) algorithm and Latent Semantic Analysis (LSA) with synonym algorithm which is used to find synonyms of text index wise by using the English wordnet dictionary, another algorithm is LSA without synonym used to find the similarity of text based on index. LSA with synonym rate of accuracy is greater when the synonym are consider for matching.

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Information Measures for Generalized Order Statistics and Their Concomitants under General Framework from Huang-Kotz FGM Bivariate Distribution

Entropy ◽

10.3390/e23030335 ◽

2021 ◽

Vol 23 (3) ◽

pp. 335

Author(s):

Mohamed A. Abd Elgawad ◽

Haroon M. Barakat ◽

Shengwu Xiong ◽

Salem A. Alyami

Keyword(s):

Order Statistics ◽

General Framework ◽

Bivariate Distribution ◽

Generalized Order Statistics ◽

Information Measures ◽

Progressive Type ◽

Information Number ◽

Fisher Information Number ◽

Dual Generalized Order Statistics ◽

Generalized Order

In this paper, we study the concomitants of dual generalized order statistics (and consequently generalized order statistics) when the parameters γ1,⋯,γn are assumed to be pairwise different from Huang–Kotz Farlie–Gumble–Morgenstern bivariate distribution. Some useful recurrence relations between single and product moments of concomitants are obtained. Moreover, Shannon’s entropy and the Fisher information number measures are derived. Finally, these measures are extensively studied for some well-known distributions such as exponential, Pareto and power distributions. The main motivation of the study of the concomitants of generalized order statistics (as an important practical kind to order the bivariate data) under this general framework is to enable researchers in different fields of statistics to use some of the important models contained in these generalized order statistics only under this general framework. These extended models are frequently used in the reliability theory, such as the progressive type-II censored order statistics.

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