Dynamically adjustable linear data discriminator

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364422, 364571, 367 30, 367 47, G01V 140, G01V 124, G06F 1500

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047180277

ABSTRACT:
A method of discriminating between linear and nonlinear regions of measured data is based upon two hypotheses, one of which is a hypothesis that a response is merely a result of inherent randomness and the other of which is a hypothesis that the response is a result of a true nonlinear change greater than a value M. It is also based upon a relative cost between accepting the latter hypothesis when the former is true versus accepting the former hypothesis when the latter is true. A resulting probabilistic criterion (M/2)+(.sigma..sup.2 /M) [1n(P.sub.H0 /P.sub.H1)C] is graphically implemented for deriving offset values which can be used in a specific embodiment to construct tabular values defining linear
onlinear regions from a presumed hypothetical straight line response.

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Sage and Melsa, Estimation Theory with Applications to Communications and Control, .COPYRGT.1971, Chapter 5, sections 5.1-5.5, pp. 116-148.

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