ECG Signal Processing with Soft/Hard Threshold Filtering, FIR and IIR Filtering

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Resource Overview

Comprehensive ECG signal processing toolkit featuring soft/hard threshold denoising, FIR/IIR filtering, and spatial correlation filtering. Includes MATLAB/Python implementation examples for biomedical signal analysis. Available for download with complete documentation.

Detailed Documentation

ECG signal processing employs multiple advanced techniques including soft/hard threshold filtering for wavelet-based denoising, FIR (Finite Impulse Response) filtering using windowing methods for linear phase characteristics, IIR (Infinite Impulse Response) filtering with Butterworth/Chebyshev designs for efficient frequency response, and spatial correlation filtering for multi-lead signal analysis. These methods enable robust feature extraction and noise reduction in electrocardiogram signals through implementable algorithms like wavelet thresholding (using wavedec/wrcoef functions) and filter design (fir1/butter functions). For detailed technical specifications, code examples, or download resources, please contact our technical support team.

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