Entropy Measures, Maximum Entropy Principle and Emerging by Karmeshu (auth.), Professor Karmeshu (eds.)

By Karmeshu (auth.), Professor Karmeshu (eds.)

This ebook is devoted to Prof. J. Kapur and his contributions to the sector of entropy measures and greatest entropy functions. Eminent students in a variety of fields of utilized info thought were invited to give a contribution to this Festschrift, accrued at the get together of his 75th birthday. The articles conceal themes within the components of actual, organic, engineering and social sciences akin to info know-how, delicate computing, nonlinear platforms or molecular biology with a thematic coherence. the quantity can be worthy to researchers operating in those various fields allowing them to determine the underlying solidarity and gear of entropy optimization frameworks.

Show description

Read or Download Entropy Measures, Maximum Entropy Principle and Emerging Applications PDF

Similar nonfiction_7 books

Drugs, Crime, and Other Deviant Adaptations: Longitudinal Studies

This quantity brings jointly a pattern of the simplest of the reports that illustrate contemporary developments in study on deviant habit. the 1st of those traits is the research of deviant habit in longitudinal standpoint. Panels of matters are over lengthy sessions of time to set up temporal relationships be­ tween deviant habit and the antecedents and outcomes of deviant behav­ ior.

A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments

Sloshing motives liquid to differ, making actual point readings tricky to acquire in dynamic environments. The dimension process defined makes use of a single-tube capacitive sensor to acquire a right away point interpreting of the fluid floor, thereby effectively making a choice on the fluid volume within the presence of slosh.

Extra info for Entropy Measures, Maximum Entropy Principle and Emerging Applications

Sample text

He has shown that entropy function appears in the observed stimulus - response relationship describing car following platoon. Consider a platoon of N cars moving along a single-lane highway with no overtaking allowed. u - AO Xj ( t ) - Xj+1(t ) ' j = 1,2,··· ,N. 5 sec. 1 Uncertainty, Entropy and MEP 41 In terms of traffic density Pn at location of the nth car and bumper-tobumper close density Pc (at which Vn = 0), Montroll [118] gives the following expression for the mean flow rate : q = >"0 Pc (-~ t Pn log pn) .

Pb'" ,Pi-b O,PHb'" ,Pn; a) = HOI. (P1 , ... ,Pi-1,PHb ... ,Pn; a) for every i = 1,2, ... (Pb ... (p b .. ·,Pi-1,Pi,PHb .. (~ ~ ) Pi'Pi;a, for every ril + ri2 = Pi > 0, i = 1,2, ... ,n. Havrda - Charvat proved that axioms (a) - (d) determine structural a-entropy unambiguously and it equals HOI. (PbP2, ... 42) 1 Uncertainty, Entropy and MEP and 29 n H 1 (pl,P2, ... ,Pn; 1) = - LPi logpi. , when a ~ 1, and it can be viewed as a generalization of Shannon's entropy. 44) which shows that Ha(p) == Ha(Pl, ...

This entropy measure however does not have additivity, recursivity and sum representation properties and is related to Renyi, and also to Havrda - Charvat entropies. Taneja [57] has given a list of generalized entropies which reduce to Shannon entropy either in the limiting or in particular cases. One may refer to Taneja [57] for mathematical expressions of entropies due to Aczel and Dar6czy (1963), Varma (1966), Kapur (1967), Sharma and Mittal (1975), Sharma and Taneja (1975,1977), Picard (1979), Ferreri (1980), Santanna and Taneja (1983).

Download PDF sample

Rated 4.42 of 5 – based on 11 votes