AbstractThe statistical entropy is shown to increase due to information loss introduced by a substitution of the total distribution function of a given system by (i) a product of distribution functions of lower orders and by (ii) a new distribution function transformed from the original one by an integral equation such as appearing in the theory of stochastic processes
There are at least three distinct ways to conceptualize entropy: entropy as an extensive thermodynam...
A probabilistic description is essential for understanding the dynamics of stochastic systems far fr...
We provide a stochastic extension of the Baez–Fritz–Leinster characterization of the Shannon informa...
AbstractThe statistical entropy is shown to increase due to information loss introduced by a substit...
This paper is part of a general study of efficient information selection, storage and processing. It...
In (1) it is suggested that Shannon’s entropy - Sum over i P(i) ln(P(i)) be thought of as the averag...
There are numerous characterizations of Shannon entropy and Tsallis entropy as measures of informati...
There are numerous characterizations of Shannon entropy and Tsallis entropy as measures of informati...
A characterization of the entropy —∫ f log f dx of a random variable is provided. If X is a random v...
Rényi entropy was originally introduced in the field of information theory as a parametric relaxatio...
Entropy is ubiquitous in physics, and it plays important roles in numerous other disciplines ranging...
In this paper, we analyze the relationship between entropy and information in the context of the mix...
An expression for the entropy of a random variable whose probability density function is reported as...
Burg’s entropy plays an important role in this age of information euphoria, particularly in understa...
We give a survey of the basic statistical ideas underlying the definition of entropy in information...
There are at least three distinct ways to conceptualize entropy: entropy as an extensive thermodynam...
A probabilistic description is essential for understanding the dynamics of stochastic systems far fr...
We provide a stochastic extension of the Baez–Fritz–Leinster characterization of the Shannon informa...
AbstractThe statistical entropy is shown to increase due to information loss introduced by a substit...
This paper is part of a general study of efficient information selection, storage and processing. It...
In (1) it is suggested that Shannon’s entropy - Sum over i P(i) ln(P(i)) be thought of as the averag...
There are numerous characterizations of Shannon entropy and Tsallis entropy as measures of informati...
There are numerous characterizations of Shannon entropy and Tsallis entropy as measures of informati...
A characterization of the entropy —∫ f log f dx of a random variable is provided. If X is a random v...
Rényi entropy was originally introduced in the field of information theory as a parametric relaxatio...
Entropy is ubiquitous in physics, and it plays important roles in numerous other disciplines ranging...
In this paper, we analyze the relationship between entropy and information in the context of the mix...
An expression for the entropy of a random variable whose probability density function is reported as...
Burg’s entropy plays an important role in this age of information euphoria, particularly in understa...
We give a survey of the basic statistical ideas underlying the definition of entropy in information...
There are at least three distinct ways to conceptualize entropy: entropy as an extensive thermodynam...
A probabilistic description is essential for understanding the dynamics of stochastic systems far fr...
We provide a stochastic extension of the Baez–Fritz–Leinster characterization of the Shannon informa...
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