Method and apparatus for detecting signal features
AssigneeRohde & Schwarz GmbH & Co. KG
InventorsAndrew Schaefer, Baris Guezelarslan, Benjamin Fischbach
Life of this patent
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Abstract
A measurement apparatus comprising an acquisition memory adapted to store data sections of at least one acquired measurement signal; a processor adapted to calculate a measurement parameter vector, v, for each data section of the acquired measurement signal; and a trained autoencoder neural network adapted to process the measurement parameter vectors, v, applied as input data to the trained autoencoder neural network to provide at a middle layer of said autoencoder neural network an encoded vector, h, with characteristic signal features of the acquired measurement signal.
Claims17
A method for detecting signal features of a measurement signal comprising the steps of:
- providing at least two separate data sections of at least one measurement signal;
- determining a measurement parameter vector, v, for each provided data section of the measurement signal;
- and
- processing the measurement parameter vectors, v, as input data by a trained autoencoder neural network to detect signal features of said measurement signal.
A measurement apparatus comprising:
- an acquisition memory adapted to store data sections of at least one acquired measurement signal;
- a processor adapted to calculate a measurement parameter vector, v, for each data section of the acquired measurement signal;
- and
- a trained autoencoder neural network adapted to process the measurement parameter vectors, v, applied as input data to the trained autoencoder neural network to provide at a middle layer of said autoencoder neural network an encoded vector, h, with characteristic signal features of the acquired measurement signal.
A computer-implemented method for signal feature detection within at least one measurement signal,
- wherein measurement parameter vectors, v, representing separate data sections of the measurement signal are processed by a trained autoencoder neural network to detect automatically characteristic signal features of the measurement signal displayed on a display of a user interface.
A computer-implemented software tool for signal feature detection in one or more measurement signals by processing separate data sections of each measurement signal to calculate associated measurement parameter vectors, v, applied as input data to a trained autoencoder neural network to extract characteristic signal features of the measurement signals.
Dependencies are inferred from the claim text.