Dynamic time warping based on modified alignment costs for evoked potentials averaging

Abstract

Averaging of time-warped signal cycles is an important tool for suppressing noise of quasi-periodic or event related signals. However, in the paper we show that the operation of time warping introduces unfavorable correlation among the noise components of the summed cycles. Such correlation violates the requirements necessary for effective averaging and results in poor suppression of noise. To limit these effects, we redefine the matrix of the alignment costs. The proposed modifications result in significant increase of the noise reduction factor in the experiments on different types and levels of noise.