THE METHOD OF FILTRATION OF RANDOM CONSTANT COMPONENT FROM INPUT SIGNAL WITH WELL-DEFINED SIGNAL/NOISE RATIO
The aim of the study is to develop the method of filtration of the informative signal from primary transducers of physical magnitudes, such as MEMS, from input signal under prior uncertainty conditions. The missing of full and reliable information about the form of the informative signal and noise, belonging to the same frequency range, stipulate certain difficulty in the work with such signals. This stipulates the actuality of the method, which will be able to archive the above mentioned target. The method can be interesting particularly in all fields of the present-day devices, operating with sensors, prediction of the exact values of which is cannot be achieved. In order to solve the above mentioned task it seems to be appropriate to use the theory of splashes of random processes and on the base of existing solutions form the new approach as a hypothesis of presence the link between mode of duration of positive splash and the period of following the values in input signal, which has minimum value of correlation score. This method gives the ability of consideration of the input signal as the realization of the random process, which can be described with the help of known distribution law and to formulate boundary conditions for achieving the universality. The present work shows that the maximum efficiency of the method is achieved on certain value of the signal-noise ratio. The universality of method is determined by the need of operation with parameters of input signal, which can be given with the help of standard measuring equipment. The implemented investigation shows that the presented method has the maximum efficiency of 10% during the filtration of the informative signal from the random constant component with the 0.88 value of signal/noise ratio.