In the context of the anisotropic control theory vanishing the system α-anisotropic norm corresponds with H2-theory, while its going to infinity, with H∞-theory. Meanwhile, this definition considerably involves just the magnitude of α, the random vector anisotropy (the mean random vectors sequence anisotropy) that characterizes the uncertainty degree. Thus, proper selection the random vector anisotropy magnitude to determine the system α-anisotropic norm is of importance. Accordingly, the paper presents an approach to constructing a normalization procedure of the anisotropy magnitude as a mapping of the positive semiaxis in the unit interval.

The paper is devoted to the investigation of a k-out-of-n system under full repair scenario after its failure. This regime implies the restoration of all failed components for some random time. As a result, the system runs like a new one. A repairable system is one that is repaired not only after a component failure (partial repair), but also after the failure of the entire system (full repair). It is supposed that these repair times have both arbitrary and different distributions, while the components’ lifetime is exponentially distributed. In some previous works, time-dependent reliability characteristics have been obtained with the theory of decomposable semi-regenerative processes [1] and method of characteristics [2] in the same assumptions about life and repair time distributions. Markovization method in particular method of supplementary variables [3] has been applied for some special cases of parameters k and n for calculation of the stationary characteristics. In the current paper, the closed-form representations for the steady state system reliability characteristics for arbitrary k and n under similar assumptions about life and repair time distributions are presented. The obtained expressions are demonstrated in terms of Laplace transform of components’ partial repair time. The results are validated on an example of a 3-out-of-6 system by substituting the exponential distribution of repair time. In addition, the probabilistic characteristics of this system in the case of rare failures, as well as some numerical example to show their insensitivity are considered.

The paper verifies the hypothesis of time-dependent dynamics of steady-state visual evoked potentials during a short series of stimulations (15 s) simulating work with brain-computer interfaces. Using deep machine learning of a neural network with direct propagation and known methods of machine classification, the frequency characteristics of the visual evoked potentials of electroencephalography during the work with brain-computer interfaces are analyzed. It is shown that the temporal dynamics of steady-state visual evoked potentials even for such a short period of time can sufficiently change the parameters. It can potentially serve as an obstacle for work with this type of brain-computer interfaces for a number of users. The described approach allows us to confirm the hypothesis that over time the brain shows signs of fatigue, consisting in changes in the frequency-time characteristics of the registered signal. Thus, the human brain shows signs of fatigue during sessions of steady-state visual evoked potentials.

The rationality constraint condition is formulated, which states that when solving control, computing and communication problems (C3) together, real-time requirements may not make it possible to find the optimal solution (control action), forcing the use of almost optimal solutions (the best found with the existing restrictions on the search procedure). This condition connects and demonstrates the unity and deep interconnection of such concepts common in management and optimization as: necessary diversity, limited rationality, analytical complexity, heuristics, records in real-time optimization. In relation to the problem of institutional management of organizational and technical systems, a number of examples of solving problems of minimizing error or complexity, as well as searching for: critical bandwidth of the communication channel, critical computing rate and the maximum number of controlled subsystems are given.

In the present paper we analyze data obtained in experiments of resource allocation games with two mechanisms: the Yang-Hajek’s mechanism (YH) and mechanism based on the alternating direction method of multipliers (ADMM). Previous research has shown that there is some correlation between consensus achievement and share of certain types of behavior. This paper considers behavior models based on best response and Pareto improvement. The aim of the research was to investigate individuals’ behavior variation on mechanism change. A behavior based on Pareto improvement is demonstrated by players in both mechanisms slightly more often than only in one mechanism. At the same time, more players demonstrate behavior based on best response in either YH or in ADMM than in both mechanisms. Players had an opportunity to subjectively rank mechanisms; dependence between players behavior and subjective ranking is also studied. It is possible that players give higher rank to the mechanism where they behave according to the best-response and Pareto improvement models more often. There can be inverse relationship between the ranking of YH mechanism and the share of Pareto improvement behavior.