The neural network learning vector quantization can be understood as a special case of an artificial neural network, more precisely, a learning-based approach - winner takes all. In this paper, we investigate this algorithm and find that this algorithm is a supervised version of the vector quantization algorithm, which should check which input belongs to the class (to update) and improve it according to the distance and class in question. To give. A common problem with other neural network algorithms is the speed vector learning algorithm, which has twice the speed of synchronous updating, which performs better where we need fast enough. The simulation results show the same problem and it is shown that in MATLAB software the learning vector quantization simulation speed is higher than the self-organized neural network. تفاصيل المقالة

The primary task of systems with real-time signal processing is to identify radars in the operating environment and to classify them based on prior system learning and to perform high-speed, real-time operations, especially where the received signal is an immediate threat such as missiles and requires war systems. Electronics should respond as soon as possible as an alarm. The purpose of this study is to use the results of this research to classify the information extracted by radar interception systems, which is achieved after the input signal selection stage and the correct selection of classification algorithms, and the other is accelerated by the learning vector quantization method. In this paper, we have presented a numerical method called a learning vector quantization, a method for data retrieval. In this method, the neural network algorithms are first organized to generate the required coding, and in the next step the digital vector learning algorithms will be created to retrieve the data. In this article, we will also consider each database benchmark. The implications of the usual implementation of universal command and control practices and their use of conventional restraint methods are a clear indication. تفاصيل المقالة

Network- based warfare is known as the symbolic element of the Age Information War. The network-based approach has been built around information sharing, and this information sharing in the battle is possible through the networking of all elements on the battlefield. A coherent networking force improves the quality of information sharing and, as a result, survival and command speed, improves the efficiency of battlefield elements, saves time and resources, and adds value for combat capability. There are various levels, including the lowest level, that is, an infantry soldier, which ultimately results in an amazing increase in the effectiveness of combat operations. Recent developments in microelectronics, mechanics, and ergonomics, as well as the movement and return, the importance and emphasis from tanks and missiles to soldiers, have examined future soldier projects. Electronic science has led to the integration of small individuals with advanced technology equipment and infantry soldiers with advanced communication, command and control (C3) systems, or communications, command, control, computer and information (C4I). All this was to try to see the infantry soldier as a complete unit instead of a small part of the great force. Each country has its own special soldier project. Considering the importance of the subject, identifying the opportunities and threats facing the Iranian warrior is necessary. In this study, we will study the future soldier project in advanced and sensitive countries and focus on communication and Network- based systems. تفاصيل المقالة