Data processing: measuring – calibrating – or testing – Measurement system – Statistical measurement
Reexamination Certificate
2001-06-27
2004-09-28
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system
Statistical measurement
C375S371000
Reexamination Certificate
active
06799144
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates in general to measurement apparatus; more particularly, to a system and method for analyzing components of a distribution; and more particularly still, to a system and method for analyzing deterministic and random components of signals.
2. Description of Related Art
A commonly encountered problem in processing measurements is to accurately determine the physical processes and key parameters associated with the distribution. In many cases, a distribution may have both deterministic and random components associated with it. It is essential to extract important information on what kind of physical processes are involved in the distribution and how much each process contributes to the measured distribution.
The present available statistical tools do not allow separation of deterministic and random components. Instead such tools determine a mean and sigmna for the entire distribution. The present invention provides a solution to this and other problems, and offers other advantages.
SUMMARY OF THE INVENTION
The present invention discloses a method, apparatus, and article of manufacture for analyzing measurements. The invention provides a method for separating and analyzing the components of a distribution, such as deterministic and random components. The method performs the steps of collecting data from a measurement apparatus, constructing a histogram based on the data such that the histogram defines a distribution, fitting tail regions of the distribution, and calculating the deterministic and random components of the distribution. The tail regions are defined by calculating the first and second order derivative of the histogram. The tail regions are fitted to predefined models and the fitted parameters are determined. The statistical confidence of the fitted parameters is estimated. Although this method may be applied to any distribution, it works particularly well to analyze signal distributions such as jitter signal distributions. The deterministic and random components of jitter can have many uses, including: 1) determining the operation margin for a digital system; 2) calculating and predicting the error probability for a digital system; 3) providing diagnostics for digital system characterization and debug; and 4) providing pass/fail values to production tests.
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Jessen Ross Adam
Li Peng
Petrich Dennis
Wilstrup Jan Brian
Hoff Marc S.
Merchant & Gould P.C.
Miller Craig Steven
Wavecrest Corporation
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