On the classification of compressed sensed signals

This paper presents a study on the possibilities for the classification of ECG signals acquired based on the theory of compressed sensing (CS). We propose an analysis of the classification results of the ECG signals acquired according to Nyquist theorem as compared to compress sensed signals using two different classifiers, namely nearest neighbor type classifier and a MLP neural network.