Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Increasing process variation in the nanometer regime motivates the use of statistical static timing analysis tools for timing verification. As device dimensions get smaller, signal integrity effects such as crosstalk noise become more significant. Therefore, it is necessary to accurately model the impact of crosstalk noise on the circuit delay. Process variations cause variability in the crosstalk alignment which leads to the variability in the delay noise. Hover, most of the existing approaches model delay noise as a worst-case deterministic quantity. In this work,  capture the variability of delay noise by first deriving the closed-form expressions of mean and standard deviation of the delay noise distribution. Next,  obtain the correlation information of the delay noise and use it to represent the delay noise distribution in canonical form. Delay noise, in canonical form, can easily be integrated with existing SSTA tools.  show experimental results that verify the accuracy of our approach.
['Ravikishore Gandikota', 'David Blaauw', 'Dennis Sylvester']
I am writing a research paper on a idea Modeling crosstalk in statistical static timing analysis
[{"from": "human", "value": "I am writing a research paper on a idea Modeling crosstalk in statistical static timing analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Increasing process variation in the nanometer regime motivates the use of statistical static timing analysis tools for timing verification. As device dimensions get smaller, signal integrity effects such as crosstalk noise become more significant. Therefore, it is necessary to accurately model the impact of crosstalk noise on the circuit delay. Process variations cause variability in the crosstalk alignment which leads to the variability in the delay noise. Hover, most of the existing approaches model delay noise as a worst-case deterministic quantity. In this work,  capture the variability of delay noise by first deriving the closed-form expressions of mean and standard deviation of the delay noise distribution. Next,  obtain the correlation information of the delay noise and use it to represent the delay noise distribution in canonical form. Delay noise, in canonical form, can easily be integrated with existing SSTA tools.  show experimental results that verify the accuracy of our approach."}]