Research Area:  Software Defined Networks

Abstract:

We propose a time-frequency representation based on the ridges of the continuous chirplet transform to identify both fast transients and components with well-defined instantaneous frequency in noisy data. At each chirplet modulation rate, every ridge corresponds to a territory in the time-frequency plane such that the territories form a partition of the time-frequency plane. For many signals containing sparse signal components, ridge length and ridge stability are maximized when the analysis kernel is adapted to the signal content. These properties provide opportunities for enhancing signal in noise and for elementary stream segregation by combining information across multiple analysis chirp rates.

Keywords:  
Chirp
time-frequency
synchrosqueezing
ridges

Author(s) Name:  Mikio Aoi; Kyle Lepage; Yoonsoeb Lim; Uri T. Eden; Timothy J. Gardner

Publisher name:  IEEE

DOI:  10.1109/TSP.2014.2365756

Volume Information:  Volume: 63, Issue: 3, February 2015, Page(s): 699 - 710

Paper Link:   https://ieeexplore.ieee.org/abstract/document/6937207