English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Within the framework of linear vector Gaussian channels with arbitrarysignaling, closed-form expressions for the Jacobian of the minimum mean squareerror and Fisher information matrices with respect to arbitrary parameters ofthe system are calculated in this paper. Capitalizing on prior research wherethe minimum mean square error and Fisher information matrices were linked toinformation-theoretic quantities through differentiation, closed-formexpressions for the Hessian of the mutual information and the differentialentropy are derived. These expressions are then used to assess the concavityproperties of mutual information and differential entropy under differentchannel conditions and also to derive a multivariate version of the entropypower inequality due to Costa.

Hessian and concavity of mutual information, differential entropy, and entropy power in linear vector Gaussian channels