Figure 8 plots the weighted principal components identified for the angle-dependent component of the horn radiativity. Each component is weighted by its corresponding singular value, thus visually indicating its importance. Also plotted using the same line type are the zero-lines for each principal component. Note in particular that the first (largest) principal component is entirely positive.

Figure 9 shows the complete horn impulse-response model ( diag ), overlaid with the original raw data . We see that both the fixed base-leakage and the angle-dependent horn-output response are closely followed by the fitted model.

Figure 10 shows the estimated impulse response of the base-leakage component , and Fig.11 shows the modeled angle-dependent horn-output components delayed out to their natural arrival times.

Figure 12 shows the average power response of the horn outputs. Also overlaid in that figure is the average response smoothed according to Bark frequency resolution [16]. This equalizer then becomes in Fig.. The filters and in Fig. are obtained by dividing the Bark-smoothed frequency-response at each angle by and designing a low-order recursive filter to provide that equalization dynamically as a function of horn angle. The impulse-response arrival times determine where in the delay lines the filter-outputs are to be summed in Fig..

Figure 13 shows a spectrogram view of the angle-dependent amplitude responses of the horn with (Bark-smoothed curve in Fig.12) divided out. This angle-dependent, differential equalization is used to design the filters and in Fig.. Note that below 12 Barks or so, the angle-dependence is primarily to decrease amplitude as the horn points away from the listener, with high frequencies decreasing somewhat faster with angle than low frequencies.

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