Heart sounds classification plays an important role in cardiovascular disease detection. Currently, deep learning methods for heart sound with heavy parameters consumption cannot be deployed environments limited memory and computational budgets. Besides, de-noising of signals (HSSs) can affect accuracy classification, because erroneous removal meaningful components may lead to distortion. In th...