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The heart sound signal, as a kind of weak biological signal under the background of strong noise, is easily subject to interference from noise of various sources. De-noising of heart sound signals, therefore, forms the primary basis for achieving non-invasive diagnosis of coronary heart disease. The paper proposes the five-level wavelet decomposition method for heart sound signals using Daubechies 6 wavelet (db6), which has yielded satisfactory results. A bi-spectrum estimation of the de-noised heart sound signals is performed based on the ARMA model, with appropriately and meticulously selected parameters. Experiments conducted on a total of 36 subjects, one half having healthy hearts and the other half afflicted with coronary heart disease, indicate that the db6-based decomposition method is capable of satisfactorily differentiating normal heart sound signals from abnormal ones.