An extension of entropy power inequality for dependent random variables

DOI10.1080/03610926.2020.1813305OpenAlexW3082700798MaRDI QIDQ5092675

Fatemeh Asgari, Mohammad Hossein Alamatsaz

Publication date: 22 July 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2020.1813305

zbMATH Keywords

Fisher informationdifferential entropyentropy power inequalityadditive noise channels

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Costa’s concavity inequality for dependent variables based on the multivariate Gaussian copula ⋮ Differential entropy of induced random state ensemble

Cites Work

• Unnamed Item
• A Mathematical Theory of Communication
• Entropy and the central limit theorem
• Fisher information inequalities and the central limit theorem
• On the Equivalence Between Stein and De Bruijn Identities
• Extension of de Bruijn's identity to dependent non-Gaussian noise channels
• Some inequalities satisfied by the quantities of information of Fisher and Shannon
• A Conditional Entropy Power Inequality for Dependent Variables
• A simple proof of the entropy-power inequality
• The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
• An Extremal Inequality Motivated by Multiterminal Information-Theoretic Problems
• Generalized Entropy Power Inequalities and Monotonicity Properties of Information
• A new entropy power inequality
• A simple converse for broadcast channels with additive white Gaussian noise (Corresp.)
• Variants of the Entropy Power Inequality
• INEQUALITIES FOR THE DEPENDENT GAUSSIAN NOISE CHANNELS BASED ON FISHER INFORMATION AND COPULAS
• Information Theoretic Proofs of Entropy Power Inequalities
• The convolution inequality for entropy powers
• Yet Another Proof of the Entropy Power Inequality

This page was built for publication: An extension of entropy power inequality for dependent random variables