Online tracking of the degree of nonlinearity within complex signals

Danilo P. Mandic, Phebe Vayanos, Soroush Javidi, Beth Jelfs, Kazuyuki Aihara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)


A novel method for online tracking of the changes in the non-linearity within complex-valued signals is introduced. This is achieved by a collaborative adaptive signal processing approach by means of a hybrid filter. By tracking the dynamics of the adaptive mixing parameter within the employed hybrid filtering architecture, we show that it is possible to quantify the degree of nonlinearity within complex-valued data. Simulations on both benchmark and real world data support the approach.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Number of pages4
Publication statusPublished - 2008
Externally publishedYes


  • Adaptive signal processing
  • Complex LMS
  • Convex optimisation
  • Machine learning
  • Wind modelling

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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