Open Access

ARTICLE

Optical Neural Networks: Analysis and Prospects for 5G Applications

Doaa Sami Khafaga¹, Zongming Lv², Imran Khan^3,4, Shebnam M. Sefat⁵, Amel Ali Alhussan^1,*

1 Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P. O. Box 84428, Riyadh, 11671, Saudi Arabia
2 School of Information and Finance, Xuancheng Vocational & Technical College, Xuancheng, 242000, China
3 Department of Electrical Engineering, University of Engineering and Technology, P. O. Box 814, Peshawar, Pakistan
4 Islamic University Centre for Scientific Research, The Islamic University, Najaf, Iraq
5 Department of Computer Science, Independent University, Dhaka, 1208, Bangladesh

* Corresponding Author: Amel Ali Alhussan. Email:

(This article belongs to the Special Issue: Optimization for Artificial Intelligence Application)

Computers, Materials & Continua 2023, 77(3), 3723-3740. https://doi.org/10.32604/cmc.2023.039956

Received 26 February 2023; Accepted 01 July 2023; Issue published 26 December 2023

Abstract

With the capacities of self-learning, acquainted capacities, high-speed looking for ideal arrangements, solid nonlinear fitting, and mapping self-assertively complex nonlinear relations, neural systems have made incredible advances and accomplished broad application over the final half-century. As one of the foremost conspicuous methods for fake insights, neural systems are growing toward high computational speed and moo control utilization. Due to the inborn impediments of electronic gadgets, it may be troublesome for electronic-implemented neural systems to make the strides these two exhibitions encourage. Optical neural systems can combine optoelectronic procedures and neural organization models to provide ways to break the bottleneck. This paper outlines optical neural networks of feedforward repetitive and spiking models to give a clearer picture of history, wildernesses, and future optical neural systems. The framework demonstrates neural systems in optic communication with the serial and parallel setup. The graphene-based laser structure for fiber optic communication is discussed. The comparison of different balance plans for photonic neural systems is made within the setting of hereditary calculation and molecule swarm optimization. In expansion, the execution comparison of routine photonic neural, time-domain with and without extending commotion is additionally expounded. The challenges and future patterns of optical neural systems on the growing scale and applications of in situ preparing nonlinear computing will hence be uncovered.

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Keywords

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