neural network

The basic architecture of mobile robotic platform with intelligent motion control system and data transmission protection

The requirements for a mobile robotic platform (MRP) with an intelligent traffic control system and data transmission protection are determined. Main requirements are the reduction of dimensions, energy consumption, and cost; remote and intelligent autonomous traffic control; real-time cryptographic data protection; preservation of working capacity in the conditions of action of external factors; adaptation to customer requirements; ability to perform tasks independently in conditions of uncertainty of the external environment.

Design of the system of automated generation of poetry works

 Features of designing a system of automated generation of poetic works, which opens up new opportunities for artistic speech and show business, especially the preparation of poems and songs have been considered. Quite often lyrics without special content become successful due to the lack of complex plots, as well as due to the unobtrusiveness and ease of perception by listeners. Well-known literature sources and available software products that can generate poetic works by combining different methods and algorithms are analyzed.

Development of Mobile Facilities of Neuro-like Cryptographic Encryption and Decryption of Data in Real Time

The requirements are formed, the method is chosen and the main stages of development of mobile means of neuro-like cryptographic encryption and real-time data decryption are considered. It is shown that the development of mobile means of neuro-like cryptographic encryption and decryption of real-time data with high efficiency of equipment is reduced to minimize hardware costs while providing a variety of requirements, characteristics and limitations. The tabular-algorithmic method of calculating the scalar product has been improved.

Construction of an Optimized Multilayer Neural Network Within a Nonlinear Model of Generalized Error

In this paper, we propose a method for optimizing the structure of a multilayer neural network based on minimizing nonlinear generalized error, which is based on the principle of minimum length of description. According to this principle, the generalized error is determined by the error in the description of the model and the error in the approximation of the data by the neural network in the nonlinear approximation.

Simplified Parallel Sorting Discrete-Time Neural Network Model

A model of parallel sorting neural network of discrete-time has been proposed. The model is described by system of difference equations and by step functions. The model is based on simplified neural circuit of discrete-time that identifies maximal/minimal values of input data and is described by difference equation and by step functions. A bound from above on a number of iterations required for reaching convergence of search process to steady state is determined. The model does not need a knowledge of change range of input data.

Establishment of a Facing Recognition System for Video Observation

In the article were researched the principles of building systems for observation and recognition of objects. Also we have given the classification of human faces recognition methods. Authors have analized the features of operetion for the progressive calibration network (PCN) for human face recognition. And finally has been created and tested the developed face recognition algorithm as the realized software system.

Using Neural Networks for Developing a System to Avoid Road Obstacles

The possibility of using a neural network to implement a system of avoidance of obstacles on the road has been investigated. The algorithms based on which such a system can work has been reviewed, also the principle of learning of the neural network has been considered. In order to implement investigation the simulator based on Unity and ML Agents has been developed. Using simulator the efficiency of education and this neural network in different configurations has been investigated.

A Model of Parallel Sorting Neural Network of Discrete-time

A model of parallel sorting neural network of discrete-time is presented. The model is described by a system of differential equations and by step functions. The network has high speed, any finite resolution of input data and it can process unknown input data of finite values located in arbitrary finite range. The network is characterized by moderate computational complexity and complexity of hardware implementation. The results of computer simulation illustrating the efficiency of the network are provided.

A Software Service for the Garbage Type Recognition Based on the Mobile Computing Devices With Graphical Data Input

The article describes problems of determining the type and automatic sorting of household waste using mobile computing devices. All of the required hardware and partially software, required for implementation of this service, are already present in modern smartphones.

Construction of a velocity model of shear wave for complexly structured geological medium using neural network (by example of data of the South Caspian basin

Object. Development of a method for predicting a two-three dimensional velocity model of a medium by using a shear wave. Complexly structured geological medium is studied on the basis of geophysical and geological data using an artificial neural network. Method.  It provides the construction and use of medium models according to geophysical well logging data and other terrestrial geophysical methods. In contrast to existing methods, the proposed method also uses additional data on the medium.