【摘要】 针对心磁信号工频及背景噪声干扰问题,提出了广义S变换奇异值分解(singular value decomposition,SVD)滤波方法.在离散S变换基础上,导出了广义矩阵S变换和逆变换公式.通过对采样信号进行广义S变换,调节时频分辨率,利用SVD分解方法确定有效心磁信号区域,实现自适应时频滤波.实验结果表明,该方法能有效滤除工频及背景噪声干扰,且在较少奇异值个数情况下可获得更好的滤波性能.更多还原

【Abstract】 In order to solve the problem of power line noise and environmental magnetic noise to magnetocardiogram, a filtering method based on singular value decomposition (SVD) and generalized S transform is proposed. On the basis of discrete condition, S transform and its inverse transform in matrix form are derived. The signal is first preprocessed using generalized S transform in order to get better time-frequency resolution, then the time-frequency domain is decomposed by SVD, and the valid time-frequency region is determined. Therefore, the adaptive filtering can be realized. Numerical simulation studies indicate that the method presented can achieve better performance than other methods with less singular values. Illustrative examples verify the effectiveness of the proposed method.更多还原