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We discuss key problems of self-organization theory, synergetics, and the prospects of its development for the next decades. We show that the future of this interdisciplinary approach probably is defined by the development of new network paradigm. We consider statements of several fundamental scientific and principle technological problems and concrete results giving rise to these conclusions.

The work outlines the key ideas of Kurdyumov S.P., an outstanding specialist in applied mathematics, self-organization theory, transdisciplinary research. It considers the development of his scientific ideas in the last decade and formulates a set of open problems in synergetics which will probably stimulate the development of this approach. The article is an engaged version of the report made at Xth Kurdyumov readings held in Tver State University in 2015.

A problem of finding of an invariant measure of irreducible discrete-time Markov chain with a finite state space is considered. There is a unique invariant measure for such Markov chain that can be multiplied by an arbitrary constant. A representation of a Markov chain by a directed graph is considered. Each state is represented by a vertex, and each conditional transition probability is represented by a directed edge. It is proved that an invariant measure for each state is a sum of $n^{n−2}$ non-negative summands, where $n$ is a cardinality of state space. Each summand is a product of $n − 1$ conditional transition probabilities and is represented by an opposite directed tree that includes all vertices. The root represents the considered state. The edges are directed to the root. This result leads to methods of analyses and calculation of an invariant measure that is based on a graph theory.

The paper concerns the study of the Rice statistical distribution’s peculiarities which cause the possibility of its efficient application in solving the tasks of high precision phase measuring in optics. The strict mathematical proof of the Rician distribution’s stable character is provided in the example of the differential signal consideration, namely: it has been proved that the sum or the difference of two Rician signals also obey the Rice distribution. Besides, the formulas have been obtained for the parameters of the resulting summand or differential signal’s Rice distribution. Based upon the proved stable character of the Rice distribution a new original technique of the high precision measuring of the two quasi-harmonic signals’ phase shift has been elaborated in the paper. This technique is grounded in the statistical analysis of the measured sampled data for the amplitudes of the both signals and for the amplitude of the third signal which is equal to the difference of the two signals to be compared in phase. The sought-for phase shift of two quasi-harmonic signals is being calculated from the geometrical considerations as an angle of a triangle which sides are equal to the three indicated signals’ amplitude values having been reconstructed against the noise background. Thereby, the proposed technique of measuring the phase shift using the differential signal analysis, is based upon the amplitude measurements only, what significantly decreases the demands to the equipment and simplifies the technique implementation in practice. The paper provides both the strict mathematical substantiation of a new phase shift measuring technique and the results of its numerical testing. The elaborated method of high precision phase measurements may be efficiently applied for solving a wide circle of tasks in various areas of science and technology, in particular — at distance measuring, in communication systems, in navigation, etc.

Computer-aided assembly planning for complex products is an important engineering and scientific problem. The assembly sequence and content of assembly operations largely depend on the mechanical structure and geometric properties of a product. An overview of geometric modeling methods that are used in modern computer-aided design systems is provided. Modeling geometric obstacles in assembly using collision detection, motion planning, and virtual reality is very computationally intensive. Combinatorial methods provide only weak necessary conditions for geometric reasoning. The important problem of minimizing the number of geometric tests during the synthesis of assembly operations and processes is considered. A formalization of this problem is based on a hypergraph model of the mechanical structure of the product. This model provides a correct mathematical description of coherent and sequential assembly operations. The key concept of the geometric situation is introduced. This is a configuration of product parts that requires analysis for freedom from obstacles and this analysis gives interpretable results. A mathematical description of geometric heredity during the assembly of complex products is proposed. Two axioms of heredity allow us to extend the results of testing one geometric situation to many other situations. The problem of minimizing the number of geometric tests is posed as a non-antagonistic game between decision maker and nature, in which it is required to color the vertices of an ordered set in two colors. The vertices represent geometric situations, and the color is a metaphor for the result of a collision-free test. The decision maker’s move is to select an uncolored vertex; nature’s answer is its color. The game requires you to color an ordered set in a minimum number of moves by decision maker. The project situation in which the decision maker makes a decision under risk conditions is discussed. A method for calculating the probabilities of coloring the vertices of an ordered set is proposed. The basic pure strategies of rational behavior in this game are described. An original synthetic criterion for making rational decisions under risk conditions has been developed. Two heuristics are proposed that can be used to color ordered sets of high cardinality and complex structure.

Currently, journal papers contain numerous examples of the use of heavy-tailed distributions for applied research on various complex systems. Models of extreme data are usually limited to a small set of distribution shapes that in this field of applied research historically been used. It is possible to increase the composition of the set of probability distributions shapes through comparing the measures of the distribution shapes and choosing the most suitable implementations. The example of a beta distribution of the second kind shown that the lack of definability of the moments of heavy-tailed implementations of the beta family of distributions limits the applicability of the existing classical methods of moments for studying the distributions shapes when are characterized heavy tails. For this reason, the development of new methods for comparing distributions based on quantile shape measures free from the restrictions on the shape parameters remains relevant study the possibility of constructing a space of quantile measures of shapes for comparing distributions with heavy tails. The operation purpose consists in computer research of creation possibility of space of the quantile’s measures for the comparing of distributions property with heavy tails. On the basis of computer simulation there the distributions implementations in measures space of shapes were been shown. Mapping distributions in space only of the parametrical measures of shapes has shown that the imposition of regions for heavy tails distribution made impossible compare the shape of distributions belonging to different type in the space of quantile measures of skewness and kurtosis. It is well known that shape information measures such as entropy and entropy uncertainty interval contain additional information about the shape measure of heavy-tailed distributions. In this paper, a quantile entropy coefficient is proposed as an additional independent measure of shape, which is based on the ratio of entropy and quantile uncertainty intervals. Also estimates of quantile entropy coefficients are obtained for a number of well-known heavy-tailed distributions. The possibility of comparing the distributions shapes with realizations of the beta distribution of the second kind is illustrated by the example of the lognormal distribution and the Pareto distribution. Due to mapping the position of stable distributions in the three-dimensional space of quantile measures of shapes estimate made it possible the shape parameters to of the beta distribution of the second kind, for which shape is closest to the Lévy shape. From the paper material it follows that the display of distributions in the three-dimensional space of quantile measures of the forms of skewness, kurtosis and entropy coefficient significantly expands the possibility of comparing the forms for distributions with heavy tails.

Method which allows to obtain explicit form of the solution as a part of power series of the argument step is developed. Formalization of characteristics of the algorithm analogous to operations of a computer is performed. The operation of transfer from one rank to another leads to a probability scheme of the algorithm that averages unknown intermediate steps in higher ranks of the series. The stochastic characteristics of the method are studied and illustrated. Examples of solving nonlinear equations and systems of nonlinear differential equations are presented.

The problem of formation of a material, which has the coefficients of attenuations and scattering close or coinciding with the same coefficients for some other predetermined material was considered. A computer processing of values of these coefficients for a big set of various materials has been carried out and their dependence on radiation energy value was studied. The conclusion was drawn about probability of successful solution of the problem in many cases and difficulties, which may occur were pointed out. A set of computer calculations carried out for some specific materials is provided.

The paper provides a solution of a task of calculating the parameters of a Rician distributed signal on the basis of the maximum likelihood principle in limiting cases of large and small values of the signal-tonoise ratio. The analytical formulas are obtained for the solution of the maximum likelihood equations’ system for the required signal and noise parameters for both the one-parameter approximation, when only one parameter is being calculated on the assumption that the second one is known a-priori, and for the two-parameter task, when both parameters are a-priori unknown. The direct calculation of required signal and noise parameters by formulas allows escaping the necessity of time resource consuming numerical solving the nonlinear equations’ s system and thus optimizing the duration of computer processing of signals and images. There are presented the results of computer simulation of a task confirming the theoretical conclusions. The task is meaningful for the purposes of Rician data processing, in particular, magnetic-resonance visualization.