Rational approximation and its application in EEG signal classification

Date: Thursday 11 August 2022

Abstract

Rational approximation (that is, approximation by a ratio of two polynomials) is a flexible alternative to polynomial approximation. In particular, rational functions exhibit accurate estimations to nonsmooth and non-Lipschitz functions, where polynomial approximations are not efficient. In this talk, we discuss the quasiconvexity property of the optimisation problems appearing in univariate rational Chebyshev approximation and its generalisation to a ratio of linear combinations of basis functions. This fact can be used in the development of computational methods. Then we apply our approximation as a preprocessing step to classify EEG signals and demonstrate that the classification accuracy is significantly improved compared to the classification of the raw signals.