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

We propose a multi-dimensional (M-D) sparse Fourier transform inspired by theidea of the Fourier projection-slice theorem, called FPS-SFT. FPS-SFT extractssamples along lines (1-dimensional slices from an M-D data cube), which areparameterized by random slopes and offsets. The discrete Fourier transform(DFT) along those lines represents projections of M-D DFT of the M-D data ontothose lines. The M-D sinusoids that are contained in the signal can bereconstructed from the DFT along lines with a low sample and computationalcomplexity provided that the signal is sparse in the frequency domain and thelines are appropriately designed. The performance of FPS-SFT is demonstratedboth theoretically and numerically. A sparse image reconstruction applicationis illustrated, which shows the capability of the FPS-SFT in solving practicalproblems.

FPS-SFT: A Multi-dimensional Sparse Fourier Transform Based on the Fourier Projection-slice Theorem