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- W2034695945 abstract "A recently proposed method (the delta method ) of estimating aircraft parameters from e ight data using feed forward neural networks is applied for the extraction of lateral-directional parameters from simulated as well as real-e ightdatainthefrequencydomain.To applythedeltamethodinthefrequency domain,thetime-domain e ight data are frequency transformed using a base-two fast Fourier transform algorithm. The frequency-transformed motion and control variables and the force and moment coefe cients are split into the real and imaginary parts. The network is trained using the training input ‐output pairs of either the real part or the imaginary part of all of thevariables involved. The delta method for the frequency-domain application ise rst validated on simulated e ight data(withandwithoutmeasurementnoise )forthelateral-directionaldynamicsand thenappliedtoreal-e ightdata. Implementation details of the method in the frequency domain and the results obtained thereby are presented. Relative advantages and potential applications of the frequency-domain approach for the delta method are also pointed out." @default.
- W2034695945 created "2016-06-24" @default.
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- W2034695945 date "2001-05-01" @default.
- W2034695945 modified "2023-10-17" @default.
- W2034695945 title "Frequency-Domain Estimation of Parameters from Flight Data Using Neural Networks" @default.
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- W2034695945 doi "https://doi.org/10.2514/2.4742" @default.
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