Adaptive wavelet-based signal dejittering

Abstract

Sampling is commonly retained as a critical step in any mixed-signal system. High-speed analog-to-digital converter sampling jitter limits all-over performance of these systems introducing a signal dependent noise in the sampled signal. In most environments it is desirable to reduce sampling clock jitter, however there are cases where designers are forced to introduce or cope with this undesirable noise effect. This work describes an innovative algorithm based on multiresolution analysis (MRA) which allows for the recovery of the original unjittered sampled signal in environments where clock jitter is unavoidable. We make use of a new versatile signal model and an MSE estimation in the wavelet domain which lead to an adaptive wavelet rescaling technique centered around a fully precalculable rescaling matrix. This technique has been successfully applied to other fields, like extracellular recording (ER) signal denoising, since it can be shown this problem can be reformulated into a signal dejittering problem.