An algorithm is presented for identification of premature ventricular cycles (PVCs) by performing a beat-by-beat analysis of the electrocardiogram (ECG). The circular convolution-multiplication relationships for the discrete cosine transform (DCT) similar to that for the discrete Fourier transform (DFT) have been used to decompose a windowed ECG cycle into system and excitatory functions representing action potential and excitation pattern of the heart muscle during cardiac cycle. The energy packing efficiency (EPE) derived from the DCT coefficients characterises the decay rate of the DCT of the system function and is related to bandwidths of resonances in the AR spectrum. EPE evaluated for the DCT of system response is shown to provide a sufficient criterion for the identification of PVCs. The algorithm was able to successfully identify PVCs from the recordings of an MIT-BIH database. Under noisy conditions, the algorithm clearly distinguishes PVC patterns from those of normal beats up to a signal-to-noise ratio (SNR) of 10 dB.