Neural Lossless Compression of ECG Signals Using Entropy Modeling and Arithmetic Coding

A neural lossless compression of ECG signals that uses entropy modelling and arithmetic coding.

A neural lossless compression of ECG signals that uses entropy modelling and arithmetic coding. It is offered as a reference project: a complete, worked example of how a system like this is designed, built and evaluated, so that a developer can study it, run it and learn from it.

It suits learners who want to work with signals and wireless data: acquiring or simulating signals, filtering and extracting features, and evaluating the results.

The main parts are signal acquisition or simulation, filtering and feature extraction, a processing or learning model, and plots and a clear evaluation. The reference build uses TensorFlow, Python, NumPy, SciPy, and MATLAB, with a clear project structure, setup instructions and sample data so that it can be run and extended.