ICASSP 2019accepted0 citations
Frequency Separation Method Based on Sparse Coding
El-Hadji Samba Diop, Karl Skretting
Abstract
The paper presents a sparse coding method that models a signal with amplitude modulation (AM) and frequency modulation (FM) functions. Indeed, the proposed sparse coding frequency separation (SCFS) approach is based on a mutli-component AM-FM modeling where each monocomponent counterpart is obtained by sparse coding using orthogonal matching pursuits, and sorted from fine to coarse depending on its frequency content. SCFS appears to be an efficient tool to properly separate the frequency content of signals, and behaves like the empirical mode decomposition. Results show neat improvements in terms of frequency separation, tone separation capability, and robustness against noise.
BibTeX
@inproceedings{icassp2019_frequencyseparat,
title = {Frequency Separation Method Based on Sparse Coding},
author = {El-Hadji Samba Diop and Karl Skretting},
booktitle = {ICASSP 2019},
year = {2019}
}