Method and apparatus for analyzing a disribution
AssigneeWavecrest Corporation
InventorsJie Sun, Peng Li, Jan Brian Wilstrup
Life of this patent
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Abstract
A method, apparatus, and article of manufacture for analyzing a measurable distribution having random components and deterministic components. The method includes the steps of collecting data, constructing a probability density function based on the data such that the probability density function is a convolution of deterministic functions and random functions, constructing a probability density function based on a deterministic and random convolution model having three or more parameters wherein at least one of the parameters are unknown, and determining unknown parameters by using a deconvolution process.
Claims93
A method of analyzing a measurable distribution having random components and deterministic components, comprising the steps of:
- (a) collecting data from a data source;
- (b) constructing a probability density function based on the data such that the probability density function defines a distribution, wherein the probability density function is a convolution of deterministic functions and random functions;
- (c) construct a probability density function based on a convolution model having three or more parameters wherein at least one of the parameters are unknown, the convolution model having a deterministic model and a random model;
- (d) determining unknown parameters by using a deconvolution process.
An apparatus for analyzing a distribution having random components and deterministic components, the apparatus comprising:
- (a) a measurement apparatus for collecting data;
- (b) an analyzing unit, operatively connected to the measurement apparatus, for collecting data from the measurement apparatus, for constructing a probability density function based on the data such that the probability density function defines a distribution, wherein the probability density function is a convolution of deterministic functions and random functions;
- construct a probability density function based on a convolution model having three or more parameters wherein at least one of the parameters are unknown, the convolution model having a deterministic model and a random model;
- and determining unknown parameters by using a deconvolution process.
The apparatus of claim 53, wherein at least one deterministic model parameter is known, wherein the analyzing unit determines the random model parameter based on known deterministic model parameters by using a deconvolution process.
An article of manufacture comprising a program storage medium readable by a computer having a memory, the medium tangibly embodying one or more programs of instructions executable by the computer to perform method steps for analyzing a distribution having random components and deterministic components, the method comprising the steps of:
- (a) collecting data from a data source;
- (b) constructing a probability density function based on the data such that the probability density function defines a distribution, wherein the probability density function is a convolution of deterministic functions and random functions;
- (c) construct a probability density function based on a convolution model having three or more parameters wherein at least one of the parameters are unknown, the convolution model having a deterministic model and a random model;
- (d) determining unknown parameters by using a deconvolution process.
Dependencies are inferred from the claim text.