← Search

Data · dataset · 2025

OTFS AWCNNdataset

Listed in Teesside University Research Data Repository

The dataset approach replaces the first convolutional layer of a standard CNN with an adaptive wavelet layer, which leverages the time-frequency localization properties of Sym4 wavelet kernels along with learnable scaling and translation factors.

Description

This enhances the network's ability to extract sparse features from OTFS signals. Additionally, the model incorporates both the original received signal and preliminary estimates from the Message Passing (MP) algorithm as input features, enriching the dataset and further improving detection performance.

Links

Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 6 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/gp5hht8gys.18 h agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
licensesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/rights
publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title