I. Introduction The MATLAB code contained in this directory implements the algorithm derived in the paper [1] using Majorization-Minimization technique. This file describes the details and procedures for the examples contained in [1].
II. Files contained and their description This directory contains the following files-
1. demo.m
This file demonstrates the CNC FLSA [1] for denoising a
sparse piecewise constant signal. This file reproduces example 1
in the paper [1].
3. ECG_demo.m
This file demonstrates the denoising of a synthetic ECG signal,
generated using ECGSYN (see [1] for details).
The synthetic ECG signal is obtained by the following commands
fs = 256;
ecg = ecgsyn(fs, 20); % 20 is the number of beats to be simulated.
5. CNC_FLSA.m
This function minimizes the CNC FLSA objective function
F(x) = 0.5||y-x||_2^2 + lam0*phi(x,a0) + lam1*phi(Dx,a1)
using the majorization-minimization technique, where phi
is a non-convex penalty function. type `help CNC_FLSA' for more details
6. soft.m
This file implements the soft thresholding rule.
type `help soft.m' for more details
7. tvd.c, tvd.mexmaci, tvd.mexmaci64, and tvd.mex64
C++ implementation of TV denoising (see [1] for details)
For questions/comments contact: Ankit Parekh (ankit.parekh@nyu.edu)
Please cite as: [1] Convex fused lasso denoising with non-convex regularization and its use for pulse detection. Ankit Parekh and Ivan W. Selesnick, IEEE SPMB, 2015.