Detection of randomness in sparse data set of three...

Details Detection of randomness in sparse data set of three... Detection of randomness in sparse data set of three...

2005-12-27

2005-12-27

Wachsman, Hal (Department: 2857)

Data processing: measuring, calibrating, or testing

Measurement system

Statistical measurement

C702S181000, C702S189000

Reexamination Certificate

active

06980926

ABSTRACT:
A two-stage method is provided for automatically characterizing the spatial arrangement among data points of a three-dimensional time series distribution in a data processing system wherein the classification of this time series distribution is required. The invention utilizes two-stage method Cartesian grids to determine (1) the number of cubes in the grids containing at least one input data point of the time series distribution; (2) the expected number of cubes which would contain at least one data point in a statistically determined random distribution in these grids; and (3) an upper and lower probability of false alarm above and below this expected value utilizing a second discrete probability relationship in order to analyze the randomness characteristic of the input time series distribution.

REFERENCES:
patent: 5956702 (1999-09-01), Matsuoka et al.
patent: 6397234 (2002-05-01), O'Brien et al.
patent: 6466516 (2002-10-01), O'Brien et al.
patent: 6597634 (2003-07-01), O'Brien et al.

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