This study's object is adaptive compression of general-form binary sequences based on binary binomial numbers. The task addressed is to enable high compression speed of binary information based on binomial numbers under the condition of uncertainty in the characteristics of the binary sequences being compressed. One of the factors that reduce the efficiency of binomial compression is uncontrolled transitions of the number of unit combinations to the region of inefficient use, the worst compression ratios. In this regard, the work applies an adaptive approach to binomial compression, based on the choice of an encoding technique depending on the number of units of the processed sequence. This approach yields the following result: a several-fold reduction in the amount of time spent processing binary combinations that are not compressible. Consequently, this leads to an increase in the average speed of binomial compression with a small, up to three to five percent, decrease in the compression ratio. The adaptive compression process model includes the stages of comparing the calculated numbers of binary units with the compression conditions and selecting the coding technique based on binary binomial numbers. If the current value of the number of units goes beyond the compression conditions, the calculation of the number of units is stopped, and the processed sequence remains unchanged. This eliminates unnecessary time costs when the compression ratio becomes less than unity. In practice, the adaptive approach to compression based on binary binomial numbers is effective in the case when the binary sequences being compressed have uncertain characteristics, and their preliminary evaluation is impossible or difficult
Kulyk et al. (Fri,) studied this question.