The analog analysis was repeated several times without any change. The 

 original data will be re-submitted for numerical analysis. At this 

 time, there is no explanation for the anomaly. Since the other five 

 comparisons are good, there is probably little cause for concern. 



It is reasonable to conclude that a SEADAC analysis is equivalent 

 to a numerical analysis, made in an analogous way. It has been shown 

 that different filter bandwidths, time constants, and scanning times 

 affect the resultant spectrum. Consequently, the original data could 

 have produced spectra that might look somewhat different from those in 

 Figure 6, if the analysis constants were changed. The same, however, 

 applies to the numerical analysis constants and equivalent results 

 will only be obtained under analogous conditions. The SEADAC analyzer 

 is therefore considered to produce good estimates of the spectral 

 density function of a random signal. 



PRESENTATION OF RESULTS 



1. LABELING OF COORDINATE AXES 



To derive meaning from the spectral density representation, it 

 is necessary to label the coordinate axes; this assigns quantitative 

 value to the graph. Certain basic information is required: 



1. Frequency multiplication factor. 



2. SEADAC calibration. 



3. Effective filter bandwidth. 



4. Instrument calibration. 



The first step is to convert the frequency scale, which is given 



18 



