THE PROSPECT OF CREATION OF A CYCLIC CONTINUAL-QUANTUM CHI-SQUARED MACHINE FOR CHECKING STATISTICAL HYPETHESES ON SMALL TEST SAMPLES OF BIOETRIC AND OTHER TYPES OF DATA
Background. The article considers preconditions for reducing sized of test samples of the Pearson’s chi-squared test from 600 examples to 20 examples provided preservation of its capacity. The problem’s topicality is caused by the fact that during learning and testing of personality biometric identification means it is not possible to use ;arge volumes of learning and testing samples. Materials and methods. The study formalizes the conditions, at which the chi-squared test on small samples becomes a discerete distribution of values from a continuous distribution of values. For the normal and uniform law of values distribution the authors use histograms with uniform intervals having a precise binding of central intervals of a histogram to mathematical expectation, calculated on a test sample. Results. It is offered to amplify the chi-squared test capacity 22 times by smoothing histograms with a digital filter with a slipping window of 9 readouts. The forecast is that the next chi-squared test capacity amplifier should be designed in the form of a cyclic continual-quantum converter that repeatedly solves the problem for smaller sub-samples. The article assesses an additional amplification of the chi-squared test capacity by revealing and studying discrete conditions of its distribution (an output discerte spectrum of the chi-squared conversion). Conclusions. It is shown that in 16 experiments the chi-squared test, synchronized by mathematical expectation and built on histograms with 6 uniform intervals, has a discrete spectrum of value probability consisting of 116 significant lines. The occurrence probability of each line depends on the input value distribution law. Recording of the discrete prectrum of chi-squared distribution can make it possible to improve the chi-squared test capacity by one or two orders.