Basics of Artificial Neural Network

Basics of Artificial Neural Network

Pravesh Kumar Bachaliya, Nikhil, Subodhini Gupta

Sam Global University, Bhopal, Madhya Pradesh, India

Praveshbachhliya7@gmail.com

Nikhildangi7869@gmail.com

subodhinig@gmail.com

ABSTRACT

The information processing model, an Artificial Neural Network (ANN), was motivated by how biological nerve systems, like the brain, handle information. The innovative structure of the information processing system is the main component of this paradigm. It comprises several intricately linked processing components (neurons) that work together to address particular issues. ANNs learn by imitation, just like humans do. An ANN is set up for a specific case of use, such as data classification or pattern recognition, by a process of learning. In biological systems, learning entails modifying the connections between neurons called synapses. This also applies to ANNs. This essay provides a summary of artificial neural ANN training, operation, and network. Additionally, it explains the application.

Keywords: ANN (Artificial Neural Network), Pattern Recognition, Neurons, Supervised training, Unsupervised Training