The article explores the utilization of optical communication networks in free space and introduces a novel FSON (Free Space Optical Network) topology designed to establish a stable optical communication environment for transmitting and receiving data between artificial space technologies and terrestrial terminals. The FSON topology incorporates various elements and devices to facilitate efficient communication. To analyze and evaluate the proposed topology, a basic artificial neuron model was constructed, and its performance metrics were examined. The research involved theoretical calculations, primarily focused on assessing the attenuation of optical signals within the transmission medium. This analysis aimed to enable stable communication between terrestrial and space terminals within the network. Incorporating an Artificial Neural Network (ANN) approach, the study employed physical measurements derived from the positions of transmitting and receiving antennas as target values. These data were processed using different training algorithms to create an optimized model, enabling the assessment of optical signal loss concerning varying distances under different scenarios.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Study of FSON Based on a Simple Artificial Neuron Model

  • Mehman Hasanov,
  • Khagani Abdullayev,
  • Sahib Piriev,
  • Nadir Atayev,
  • Turana Rasullu

摘要

The article explores the utilization of optical communication networks in free space and introduces a novel FSON (Free Space Optical Network) topology designed to establish a stable optical communication environment for transmitting and receiving data between artificial space technologies and terrestrial terminals. The FSON topology incorporates various elements and devices to facilitate efficient communication. To analyze and evaluate the proposed topology, a basic artificial neuron model was constructed, and its performance metrics were examined. The research involved theoretical calculations, primarily focused on assessing the attenuation of optical signals within the transmission medium. This analysis aimed to enable stable communication between terrestrial and space terminals within the network. Incorporating an Artificial Neural Network (ANN) approach, the study employed physical measurements derived from the positions of transmitting and receiving antennas as target values. These data were processed using different training algorithms to create an optimized model, enabling the assessment of optical signal loss concerning varying distances under different scenarios.