Abstract
A neural network is a data encoding and decoding system made up of a large number of simple processing components that are highly coupled and arranged in a pattern inspired by the cerebral cortex section of the brain. As a result, neural networks can be utilized to tackle issues that traditional computers cannot. Neural networks have emerged as a promising area for research, development, and application to a wide range of real-world circumstances. Indeed, neural networks have qualities and capacities that no other technology has. Artificial neural networks (ANNs) are functional replicas of biological neurons with the purpose of building usable computers for real-world problems. The use of these ANNs has grown substantially in recent years, driven by both theoretical and practical implementations in a variety of fields. A basic theory of ANN is presented, as well as promising topics for research and future trends.