# Bayesian nonparametric regression using complex wavelets

@article{Remenyi2018BayesianNR, title={Bayesian nonparametric regression using complex wavelets}, author={Norbert Rem'enyi and Brani Vidakovic}, journal={arXiv: Methodology}, year={2018} }

In this paper we propose a new adaptive wavelet denoising methodology using complex wavelets. The method is based on a fully Bayesian hierarchical model in the complex wavelet domain that uses a bivariate mixture prior on the wavelet coefficients. The heart of the procedure is computational, where the posterior mean is computed through Markov chain Monte Carlo (MCMC) simulations. We show that the method has good performance, as demonstrated by simulations on the well-known test functions and by…

## One Citation

### Denoising Non-stationary Signals by Dynamic Multivariate Complex Wavelet Thresholding

- Computer Science
- 2020

A novel continuous wavelet transform (CWT) dynamically-optimized, multivariate thresholding method that shows improved results when compared to well-known methods, especially for high-frequency signal rich time series, typically observed in finance.

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