title: Non-linear transform-based robust adaptive latency change estimation of evoked potentials.
abstract: OBJECTIVE
  To improve the latency change estimation of evoked potentials (EP) under the lower order alpha-stable noise conditions by proposing and analyzing a new adaptive EP latency change detection algorithm (referred to as the NLST).
  
  
  METHODS
  The NLST algorithm is based on the fractional lower order moment and the nonlinear transform for the error function. The computer simulation and data analysis verify the robustness of the new algorithm.
  
  
  RESULTS
  The theoretical analysis shows that the iteration equation of the NLST transforms the lower order alpha-stable process en (k) into a second order moment process by a nonlinear transform. The simulations and the data analysis showed the robustness of the NLST under the lower order alpha-stable noise conditions.
  
  
  CONCLUSIONS
  The new algorithm is robust under the lower order alpha-stable noise conditions, and it also provides a better performance than the DLMS, DLMP and SDA algorithms without the need to estimate the alpha value of the EP signals and noises.
authors.affiliation: Department of Electronic Engineering, Dalian University of Technology, Dalian, China. qiutsh@sohu.com
authors.forename: T
authors.initials: T
authors.lastname: Qiu
authors.forename: H
authors.initials: H
authors.lastname: Wang
authors.forename: Y
authors.initials: Y
authors.lastname: Zhang
authors.forename: H
authors.initials: H
authors.lastname: Bao
mesh_terms: D000465:Algorithms; D002490:Central Nervous System / Q000293:injuries; D005073:Evoked Potentials, Somatosensory / Q000502:physiology*; D006801:Humans; D002534:Hypoxia, Brain / Q000503:physiopathology; D017711:Nonlinear Dynamics; D011930:Reaction Time / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted