In this paper, we present a review of Shannon and differential entropy rate estimation
techniques. Entropy rate, which measures the average information gain from a stochastic …

Probabilistic 'distances'(also called divergences), which in some sense assess how
'close'two probability distributions are from one another, have been widely employed in …

Information gathering algorithms play a key role in unlocking the potential of robots for
efficient data collection in a wide range of applications. However, most existing strategies …

The Jensen-variance (JV) information based on Jensen's inequality and variance has been
previously proposed to measure the distance between two random variables. Based on the …

The reliable transmission and processing of information bearing signals over a noisy
communication channel is at the heart of what we call communication. Information theory …

Information theoretic quantities such as entropy, entropy rate, information gain, and relative
entropy are often used to understand the performance of intelligent agents in learning …

This paper presents a new generalized bounded distribution called the Kumaraswamy unit-
Gompertz (KUG) distribution. Some of the Mathematical properties which include; the …

This paper presents a new Marshall-Olkin extended family of distributions with bounded
support. Some of the Mathematical properties of the proposed distribution were studied and …

In this paper, we provide the Rényi entropy and complexity measure for a novel, flexible
class of skew-gaussian distributions and their related families, as a characteristic form of the …

Abstract<? Pub Inc> The idea of'probabilistic distances'(also called divergences), which in
some sense assess how'close'two probability distributions are from one another, has been …