## 3 Results and Discussion
### The Mechanism of the Formation of the Multiscan Video Signal on the Basis of Its Impulse Response
The SSPs make it possible to estimate the width of the rectangular signal of an action, localize it in space and determine its amplitude by the smeared response of the path of the signal reception and transmission. The SSPs are functionals, the values of which depend on the parameters of the transformation of measurement signals acting in reception and transmission systems. Such transformations are the weighing and summing of signals, the transformation of bias and scaling of signals, and convolutions of signals with the impulse responses of the linear units of the system of signal reception and transmission. The SSPs are integral characteristics of signals and are constructed based on the moments of a different order [29; 30]. The moments are described by the following expressions:  
\[W_{k}=\int t^{k}f(t)dt \tag{17}\]  
where integration is performed over the entire interval of the signal observation (finite or infinite; in the first case, \(f(t)\) is assumed to be equal to zero beyond the interval). In [31], five SSPs of a video signal are determined: mass (\(M\)), centroid (\(C\)), dissipation (\(D\)), extent (\(E\)) and brightness (\(Y\)). The SSPs are computed using one-dimensional moments \(W_{0}\), \(W_{1}\), and \(W_{2}\) by the following expressions:  
\[M=W_{0} \tag{18}\]  
\[C=W_{1}/M=W_{1}/W_{0} \tag{19}\]  
\[D=W_{2}/M-C^{2}=W_{2}/W_{0}-(W_{1}/W_{0})^{2} \tag{20}\]\[E=2\sqrt{3D}=2\sqrt{3\left(W_{2}/W_{0}-\left(W_{1}/W_{0}\right)^{2}\right)} \tag{21}\] \[Y=\frac{M}{E}=\frac{W_{0}}{2\sqrt{3\left(W_{2}/W_{0}-\left(W_{1}/W_{0} \right)^{2}\right)}} \tag{22}\]  
In the above expressions, the second variant is only a function of the moments, and the first variant is a recurrent scheme of computations, in which each subsequent parameter is expressed in terms of the former ones. The SSPs' interpretation is as follows:  
* the signal mass is an integral over the entire signal observation interval (in this case, it is necessary to take into account that the mass function is unipolar); the physical analogue of the signal mass is the total mass of a linear object with a certain specified mass distribution over its length, which is described by the density of its redistribution _f(t)_;
* the signal centroid corresponds to the \"centre of gravity\" of the indicated linear object;
* the signal dissipation characterizes the degree of the dispersion of the masses around the \"centre of gravity\" of the indicated linear object; the smaller the dissipation value is, the larger the part of masses around the \"centre of gravity\" is localized; and vice versa, the larger the dissipation value is, the more dispersal character of the mass distribution is. When mass, centroid, and dissipation are suitable for the description of signals with a random distribution of amplitudes over their entire length, it makes sense to compute the extent and brightness for rectangular signals which are light zone profiles on the multiscan (Figure 4a). In the case of specified limitations for the measurement signal shape, the extent corresponds to the width of the rectangular signal (light zone width) and brightness to its amplitude (light zone illumination). Of all the SSPs, the most interesting is dissipation due to its property to take into account the value of the smearing-out of a video pulse when it passes through the path of reception and transmission in the MOD with the impulse response \(h(\hat{t}-\hat{x})\) (Figure 5). In this case, the output signal dissipation \(v(\hat{t})\) is:  
\[D\big{[}v(\hat{t})\big{]}=D\big{[}f(\hat{x})\big{]}+D\big{[}h(\hat{t}-\hat{x}) \big{]} \tag{23}\]  
Let us summarize the case described in Figure 5 and expression (23) when the video pulse \(f(\hat{x})\) passes through the sequence of linear units with the impulse responses \(h(\hat{t}-\hat{x}_{i})\) (Figure 7).