关键词: 随机电报噪声, 隐式马尔可夫模型, 耦合效应, 高斯判断, 自适应模型

Abstract: With the development of integrated circuits, the size of devices decreases, which leads to the increase of traps in MOSFET gate oxide layer. The generated low frequency noise, especially Random Telegraph Noise (RTN), becomes more and more obvious, which challenges the reliability of devices. When there are more than one trap in the device, the coupling effect between traps also has an important influence on the analysis of RTN signals. Therefore, it is particularly urgent to carry out research on RTN signal extraction technology in complex and multi-trap situations. At present, the existing RTN extraction technology consumes a lot of time when processing large amounts of data, and the degree of automation is not high. These problems need to be solved urgently. In this paper, based on the non-Gaussian property of RTN signal, an automatic detection method of RTN signal and an automatic detection method of trap number are proposed, which makes the extraction of RTN signal more accurate and efficient. In addition, this paper also proposes an adaptive model for important parameters in the iterative process, and realizes the iterative acceleration of most RTN signal extraction. Finally, the method is used to extract parameters of the measured RTN signal, and the influence of coupling effect on the parameters is analyzed.

Key words: random telegraph noise, hidden Markov model, coupling effect, Gaussian judgment, adaptive model