纳米器件的散粒噪声检测方法研究

Study on shot noise detection method in nano devices

针对纳米器件散粒噪声信号去噪方法的不足,利用散粒噪声信号在不同状态下的方差特性,提出了一种改进的经验模态分解算法(EMD)。该算法根据信号固有模态函数(IMFs)方差最大值与对应层数的关系自适应地选择需要处理的IMF层数,并与传统平均算法相结合提取了散粒噪声信号。实验结果表明:在不同程度(≥-3.92 d B)低频噪声环境下,与传统的EMD硬性去噪等方法比较可知,其信噪比提高了5.4 d B^7.0 d B,均方误差降低了36%以上,该方法有效地去除了低频噪声,提高了散粒噪声检测的有效性。

To deal with the shortcomings of denoising methods for nano devices shot noise, this paper studies the variance characteristics of shot noise signal in different states and proposes an improved algorithm for empirical mode decomposition（ EMD）. The al-gorithm can adaptively select the IMF layer which need to be processed, according to the relationship between the maximum variance of IMFs with the corresponding layers. At the same time, it is integrated with the classical average algorithm, then the shot noise signal is separated from the noise effectively. The results show that under different degrees（ ≥- 3. 92 d B） low- frequence noise environment, with traditional rigid EMD de- noising method comparison, it improves the signal to noise ratio 5. 4 d B ~ 7. 0 d B, the mean square error is reduced by more than 36 %, this method effectively removes low- frequency noise, and increases the effective-ness of the shot noise detection.