Information Technology and Pragmatic Analysis

Similarity method has been in science for several centuries. The basis of the study is closely connected with mathematical linguistics. This approach has allowed obtaining new results in the analytical geometry, which, in turn, is used in different applications in information technology. The results are described briefly. Binary relations in linguistics and geometry are compared with the position of system analysis. The modified hypothesis of space as a binary structure is put forward on the basis of singular linear transformations. The hypothesis of the human sensory system is given shortly. Architecture computing appliance for solving this class of problems is proposed. The modified method is also applied in pattern recognition. The presence of symmetry in natural languages is shown briefly

The method of high accuracy calculation of robot trajectory for the complex curves

The geometric model accuracy is crucial for product design. More complex surfaces are represented by the approximation methods. On the contrary, the approximation methods reduce the design quality. A new alternative calculation method is proposed. The new method can calculate both conical sections and more complex curves. The researcher is able to get an analytical solution and not a sequence of points with the destruction of the object semantics. The new method is based on permutation and other symmetries and should have an origin in the internal properties of the space. The classical method consists of finding transformation parameters for symmetrical conic profiles, however a new procedure for parameters of linear transformations determination was acquired by another method. The main steps of the new method are theoretically presented in the paper. Since a double result is obtained in most stages, the new calculation method is easy to verify. Geometric modeling in the AutoCAD environment is shown briefly. The new calculation method can be used for most complex curves and linear transformations. Theoretical and practical researches are required additionally

Convolutional neural networks training for autonomous robotics

The article discusses methods for accelerating the operation of convolutional neural networks for autonomous robotics learning. The analysis of the theoretical possibility of modifying the neural network learning mechanism is carried out. Classic semiotic analysis and the theory of neural networks is proposed to union. An assumption is made about the possibility of using the symmetry mechanism to accelerate the training of convolutional neural networks. A multilayer neural network to represent how space is an attempt has been made. The conclusion was based on the laws on the plane obtained earlier. The derivation of formulas turned out to be impossible due to the problems of modern mathematics. A new approach is proposed, which involves combining the gradient descent algorithm and the stochastic completion of convolutional filters by the principles of symmetries. The identified algorithms allow increasing the learning rate from 5% to 15%, depending on the problem that the neural network solves