Journal:Informatica
Volume 2, Issue 2 (1991), pp. 221–232
Abstract
The principles of a neural network environmental model are proposed. The principles are universal and can use different neural network architectures. Such a model is self-organizing, it can operate in both regimes with and without a teacher. It codes information about objects, their features, the actions operating in an environment, analyzes concrete situations. There are functions for making an action plan, for action control. The goal of the model is given from an external site. The model has more than sixteen active regimes. The neural network environmental model is fulfilled in software and hardware tools.
Journal:Informatica
Volume 2, Issue 2 (1991), pp. 195–220
Abstract
The observation problem along with the certain independent value plays a great role while carrying out control of dynamic systems in the conditions of uncertainty (Kalman, 1957, Krasovski, 1985, Leondes, 1976). A new approach on connection between the problems of control and observation is presented in (Gabasov, 1991). Developing it, we justify the solution of observation problem in the given paper that arises, at optimization of linear dynamic systems. The paper consists of the two parts. In the part I the linear discrete system is investigated. In the part II the linear dynamic continuous system is considered.
Journal:Informatica
Volume 2, Issue 2 (1991), pp. 171–194
Abstract
The paper deals with the minimization algorithms which enable us to economize the computing time during the coordinated calculation of the values of an objective function on the nodes of a rectangular lattice by storing and using quantities that are common for several nodes. The algorithm of a uniform search with clustering, the variable metric algorithm and the polytope algorithm are modified.
Journal:Informatica
Volume 2, Issue 2 (1991), pp. 155–170
Abstract
This paper is devoted to the construction and investigation of difference schemes for the solution of one-dimensional parabolic problems with non-classical boundary conditions. The stability of schemes and the convergence of a numerical solution is proved in the norms L1 and C.
Journal:Informatica
Volume 2, Issue 1 (1991), pp. 117–134
Abstract
The problem of change point detection when the properties of the random process observed suddenly begin changing slowly is considered. The most probable time moments of changes are investigated. Random processes are described by autoregression equations. The situation is studied when slow changes in the properties of a random process take place according to the linear law. An example of solving the problem is presented, realized by computer.
Journal:Informatica
Volume 2, Issue 1 (1991), pp. 100–116
Abstract
The hierarchical principle of video-information analysis (progressive detalisation) is one from the set of principles which are implemented in the living vision system. The reflection of this principle in the techniques of the representation of a shape of the region, occupied by binary image, allows us to find a solution of two tasks simultaneously: data compression and data structure, which suits for geometric transformations of the image. This report includes operations which are performed on the hierarchical list of rectangles. The latter is built up by using intermediate pyramidal representation.
Journal:Informatica
Volume 2, Issue 1 (1991), pp. 77–99
Abstract
The problem multialternative recognition of non-stationary processes on the basis of dynamic models is investigated in the paper. The algorithms of pointwise and group classifications are compared. Clustering algorithms based on nonlinear mapping of the segments of random processes onto the plain are used to construct the classifiers.
Journal:Informatica
Volume 2, Issue 1 (1991), pp. 66–76
Abstract
The problem of determination of a change point in the properties of autoregressive sequences with unknown distribution is analysed. Two robust algorithms for the estimation of a change point when the distribution is symmetric and asymmetric are presented.