Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a fast and accurate statistical static timing analysis method that supports sked non-Gaussian process parameter variations. First,  propose modeling of non-Gaussian sources of variation using a Skew-Normal random variable which can represent a large class of non-Gaussian distributions such as Log-Normal and Poisson. Second,  present a linear gate delay model in terms of this Skew-Normal as ll as Gaussian parameters. Third,  approximate arrival times as sked random variables in an effort to simply capture the shape of the arrival times without loss of accuracy. A proposed linear encoding of sked arrival times enables computing the exact analytical expression for the MAX of arrival times as ll as for their first three moments which can be evaluated in an efficient manner. Overall, calculation of the MAX operation is done efficiently (i.e., comparable to the fastest-known Gaussian linear approximation of Clark) with high accuracy and restriction-free for a realistic representation of non-Gaussian process parameters.
['Lin Xie', 'Azadeh Davoodi']
I am writing a research paper on a idea Fast and Accurate Statistical Static Timing Analysis with Skewed Process Parameter Variation
[{"from": "human", "value": "I am writing a research paper on a idea Fast and Accurate Statistical Static Timing Analysis with Skewed Process Parameter Variation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a fast and accurate statistical static timing analysis method that supports sked non-Gaussian process parameter variations. First,  propose modeling of non-Gaussian sources of variation using a Skew-Normal random variable which can represent a large class of non-Gaussian distributions such as Log-Normal and Poisson. Second,  present a linear gate delay model in terms of this Skew-Normal as ll as Gaussian parameters. Third,  approximate arrival times as sked random variables in an effort to simply capture the shape of the arrival times without loss of accuracy. A proposed linear encoding of sked arrival times enables computing the exact analytical expression for the MAX of arrival times as ll as for their first three moments which can be evaluated in an efficient manner. Overall, calculation of the MAX operation is done efficiently (i.e., comparable to the fastest-known Gaussian linear approximation of Clark) with high accuracy and restriction-free for a realistic representation of non-Gaussian process parameters."}]