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

SDEs are solved in two steps: (1) for short times by successive approximationin the integral equation, which leads to non-Gaussian increments when the noiseis multiplicative, (2) by summing up these increments in consecutive short timeintervals. This corresponds to a modified anti-Ito integral. That proceduresaves the choice of an integration sense, and it also avoids an intrinsicmismatch between the standard stochastic integrals (with Gaussian increments)and the Fokker-Planck equations (with non-Gaussian solutions). As a further newfeature, the local diffusion parameters (plus a noise-independent drift) aresufficient to specify the SDE. This can simplify the modelling. For the FPE itmeans that the diffusion matrix alone accounts for the noise (the well-knownand valid anti-Ito FPE involves a noise-induced drift part that cancels withsome other term).

Path-wise solution of stochastic differential equations, leading to a new and unique stochastic integral