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

This paper introduces the application of predictor-based control principles for the control of human response to a virtual 3D face. A dynamic woman 3D face is observed in virtual reality. We use changing distance-between-eyes in a 3D face as a stimulus – control signal. Human responses to the stimulus are observed using EEG-based excitement signals – output signal. The technique of dynamic systems identification which ensure stability and possible higher gain of the model for building a predictive input-output model of control plant is applied. Three predictor-based control schemes with a minimum variance or a generalized minimum variance control quality and constrained control signal magnitude and change rate are developed. High prediction accuracies and control quality are demonstrated by modelling results.

A Comparison of the Control Schemes of Human Response to a Dynamic Virtual 3D Face