Nonlinear Filtering Methods  - Chapter 6

P. E. McSharry & G. D. Clifford

This page provides supplementary information and relevant links for Chapter 6 in Advanced Methods for ECG Analysis, which is co-edited by Francisco Azuaje and Patrick McSharry, and is published by Artech House. The main URL for this book can be found here, together with ordering information. Much of the software associated with this book can be found here.

Links:

• ECGSYN - Realistic artificial ECG, BP and Respiratory waveform generation, written in Matlab, C and Java. Various versions exist, more numerous that the one found on PhysioNet.
• PhysioNet - A collection of C code libs and routines for biomedical signal processing. 
• ECGSYN - Realistic artificial ECG, BP and Respiratory waveform generation, written in Matlab, C and Java. Various versions exist, more numerous that the one found on PhysioNet. 
• Tisean - Free C code for Nonlinear Time Series Analysis, based on the theory of nonlinear deterministic dynamical systems, (or chaos theory), by Rainer Hegger, Holger Kantz & Thomas Schreiber. 
• Danny Kaplan's Matlab code for Nonlinear Time Series Analysis
• Danny Kaplan's Electronic Supplement to Understanding Nonlinear Dynamics
• Artificial Noise Generators in Matlab (white, pink and brown noise). 

Contents:

6.1 Introduction

6.2 Nonlinear Signal Processing

6.2.1 State Space Reconstruction

6.2.2 Lyapunov Exponents

6.2.3 Correlation Dimension

6.2.4 Entropy

6.2.5 Nonlinear Diagnostics

6.3 Evaluation Metrics

6.4 Empirical Nonlinear Filtering

6.4.1 Nonlinear Noise Reduction

6.4.2 State Space Independent Component Analysis

6.4.3 Comparison of NNR and ICA

6.5 Model-Based Filtering

6.5.1 Nonlinear Model Parameter Estimation

6.5.2 State Space Model-Based Filtering