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

Semantic communications represent a significant breakthrough with respect tothe current communication paradigm, as they focus on recovering the meaningbehind the transmitted sequence of symbols, rather than the symbols themselves.In semantic communications, the scope of the destination is not to recover alist of symbols symbolically identical to the transmitted ones, but rather torecover a message that is semantically equivalent to the semantic messageemitted by the source. This paradigm shift introduces many degrees of freedomto the encoding and decoding rules that can be exploited to make the design ofcommunication systems much more efficient. In this paper, we present anapproach to semantic communication building on three fundamental ideas: 1)represent data over a topological space as a formal way to capture semantics,as expressed through relations; 2) use the information bottleneck principle asa way to identify relevant information and adapt the information bottleneckonline, as a function of the wireless channel state, in order to strike anoptimal trade-off between transmit power, reconstruction accuracy and delay; 3)exploit probabilistic generative models as a general tool to adapt thetransmission rate to the wireless channel state and make possible theregeneration of the transmitted images or run classification tasks at thereceiver side.

Semantic Communications Based on Adaptive Generative Models and Information Bottleneck