Abstract: A method of analyzing and correcting a complex dynamic waveform, such as a radar wave or communication wave. The method comprises dividing a complex waveform into its real and imaginary components, then separately analyzing each such waveform in a dedicated neural to determine respective real and imaginary loss functions as the difference between the actual characteristics and desired characteristics of the mean squared error and at least one of frequency-domain power, time-domain envelope, and frequency-domain phase. The real waveform and imaginary waveform are independently corrected, then recombined into a single corrected complex waveform. These differences are fed into a neural network to improve prediction correction to bring the actual waveform closer to a benchmark waveform. The method of the present invention displays increased accuracy over the prior art without increased computing time or sacrificing notch depth.

Abstract: A method of analyzing and correcting a complex dynamic waveform, such as a radar wave or communication wave. The method comprises developing a loss function as the difference the actual characteristics and desired characteristics of the mean squared error and at least one of frequency-domain power, time-domain envelope, and frequency-domain phase. These differences are fed into a neural network to improve prediction correction to bring the actual waveform closer to a benchmark waveform. The method of the present invention displays increased accuracy over the prior art without increased computing time or sacrificing notch depth.