Feature Extraction in Signals using Wavelets

MATLAB code and associated files for Feature Extraction using Wavelets - Part 2
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Updated 16 Mar 2017

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Decompose real-world signals into time-varying frequency components using wavelet transform in MATLAB®, and extract relevant features for further processing.
Use the Discrete Wavelet Transform in MATLAB® to extract spectral features from real-world signals. The goal of this demo is to demonstrate how you can use wavelet transform to extract R waves from an EKG signal to enhance peak detection and compute heart rate. Refer to Feature Detection Using Wavelets - Part 1 for more information about how wavelet transform can be used to identify spectral features.

Cite As

Kirthi Devleker (2024). Feature Extraction in Signals using Wavelets (https://www.mathworks.com/matlabcentral/fileexchange/61569-feature-extraction-in-signals-using-wavelets), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016b
Compatible with any release
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Version Published Release Notes
1.0.0.0

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