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Focus On Significant Aspects Of The Intersection Of AI And Optical Communication

Focus On Significant Aspects Of The Intersection Of AI And Optical Communication

Experts in early machine learning and deep learning algorithms understand the contribution of deep learning to optical communications. You may not have a specialization in the DL algorithms and data types. You can explore the multiple DL-enabled solutions to optical communication and make a good decision to efficiently use the convolution neural network and recurrent neural network for image recognition and sequential data analysis. A good data-driven channel modeling approach is a good alternative to the usual blockchain-based modeling method. It enhances the end-to-end learning performance. You can understand the synergy between AI algorithms and optical technology and make an informed decision to use modern AI technologies along with optical technology.

Deep reinforcement learning algorithms

Deep reinforcement learning is successfully applied to perform the best self-configuration and is known for its adaptive allocation for optical networks. A generative adversarial network is used for data augmentation for expanding the training dataset from the experimental data. The best algorithms from the machine learning communities are used in different aspects like digital signal processing, signal detection and analysis, optical performance monitoring, network automation, proactive fault management, and optical sensing. Deep learning addresses large-scale and complex problems as adaptable, robust, and efficient solutions. Modern AI revolutionizes optical network management and gives exceptional benefits to all users.

Properly integrate the AI to the optical communication system

AI algorithmsBeginners in the optical communication sector wish to explore and use artificial intelligence and its associated technologies. They are ready to properly integrating AI to enhance optical communication infrastructure and efficiently use the infrastructure. Deep learning is used in optical communication to promote the development of artificial intelligence. It is used in both physical and network layers. You can consider these modern deep learning techniques and their role in the optical communication sector.

You will be keen and happy to use the best resources and technologies to improve your optical communication system within the budget.