The mutual information is useful measure of a random vector component dependence. It is important in many technical applications. The estimation methods are often based on the well known relation between the mutual information and the appropriate entropies. In 1999 Darbellay and Vajda proposed a direct estimation methods. In this paper we compare some available estimation methods using different 2-D random distributions
Mutual information is a measurable quantity of particular interest for several applications that int...
Reshef et al. recently proposed a new statistical measure, the “maximal information coefficient ” (M...
MOTIVATION: Mutual information (MI) is a quantity that measures the dependence between two arbitrary...
Abstract: The mutual information is useful measure of a random vector component dependence. It is im...
A new, non–parametric and binless estimator for the mutual information of a d–dimensional random vec...
We present two classes of improved estimators for mutual information M(X,Y), from samples of random ...
International audienceThis paper deals with the control of bias estimation when estimating mutual in...
International audienceThis paper deals with the control of bias estimation when estimating mutual in...
A popular way to measure the degree of dependence between two random objects is by their mutual info...
International audienceThis paper deals with the control of bias estimation when estimating mutual in...
Mutual information is widely used, in a descriptive way, to measure the stochastic dependence of cat...
Mutual information is fundamentally important for measuring statistical dependence between variables...
In the case of two signals with independent pairs of observations (x(n),y(n)) a statistic to estimat...
We propose to measure statistical dependence between two random variables by the mutual information ...
In the case of two signals with independent pairs of observations (x(n),y(n)) a statistic to estimat...
Mutual information is a measurable quantity of particular interest for several applications that int...
Reshef et al. recently proposed a new statistical measure, the “maximal information coefficient ” (M...
MOTIVATION: Mutual information (MI) is a quantity that measures the dependence between two arbitrary...
Abstract: The mutual information is useful measure of a random vector component dependence. It is im...
A new, non–parametric and binless estimator for the mutual information of a d–dimensional random vec...
We present two classes of improved estimators for mutual information M(X,Y), from samples of random ...
International audienceThis paper deals with the control of bias estimation when estimating mutual in...
International audienceThis paper deals with the control of bias estimation when estimating mutual in...
A popular way to measure the degree of dependence between two random objects is by their mutual info...
International audienceThis paper deals with the control of bias estimation when estimating mutual in...
Mutual information is widely used, in a descriptive way, to measure the stochastic dependence of cat...
Mutual information is fundamentally important for measuring statistical dependence between variables...
In the case of two signals with independent pairs of observations (x(n),y(n)) a statistic to estimat...
We propose to measure statistical dependence between two random variables by the mutual information ...
In the case of two signals with independent pairs of observations (x(n),y(n)) a statistic to estimat...
Mutual information is a measurable quantity of particular interest for several applications that int...
Reshef et al. recently proposed a new statistical measure, the “maximal information coefficient ” (M...
MOTIVATION: Mutual information (MI) is a quantity that measures the dependence between two arbitrary...