Agilent Technologies, Inc.

Keysight Technologies, Inc.

John Francis McLaughlin

Joseph Michael Gorin

Jochen Rivoir

George Stennis Moore

Matthew Johnson

Peter J Cain

Moray Denham Rumney

David H Molinari

Robert Locascio

In an exemplary embodiment of the disclosure, a signal analyzer includes at least one noise reduction system in the form of an adaptive noise reduction system. The adaptive noise reduction system executes an adaptive noise floor extension (NFE) procedure that includes determining a predicted standard deviation of a response by the signal analyzer to intrinsic noise in the signal analyzer when various signal processing parameters desired by a user are applied to an input signal. The predicted standard deviation is then used in the signal analyzer to select and apply various noise subtraction values upon the input signal before displaying of a signal spectrum of the input signal upon a display of the signal analyzer. The adaptive NFE procedure is directed at reducing or eliminating various ambiguities and/or errors in the displayed signal spectrum.

Adaptive noise reduction in a signal analyzer

Using component-level test data to reduce system test. By modeling a system, sensitivity analysis reveals critical components and parameters of those components required to meet system performance parameters. Critical components are tested for these parameters, and these measurements associated with the components. Systems may be assembled which are modeled to meet the system performance parameters based on the model and the measured parameters. Systems may be assembled and calibration coefficients derived and applied from the model and the measured parameters.

Using component-level calibration data to reduce system-level test

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Santa Rosa, CA, United States of America

John Francis McLaughlin