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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

It is still a challenge to detect the useful signals under chaotic noise background with effective methods. Difficults such as suppression of useful signals, large computation and low sensitivity commonly exist the new method based on the nonlinear characteristics of signals, such as neural network method, and traditional methods. On the contrast, The extreme learning machine has advantages of strong nonlinear approximation, simple structure, high precision, fast learning and training speed, etc. On this basis, this paper proposes a method of utilizing extreme learning machine based on least square to get the output weight, in order to train the model to detect the weak pulse signal.

Detection of pulse signal in chaotic noise background using extreme learning machine