Document Type : Original Article

Author

• aysser Abdulkhaleq abdulrahman

Computer Science, College of Science, University of Sulaimany, Sulaimany, Kurdistan Region, Iraq

Abstract

A neural network is a series of algorithms that endeavors to recognize underlying relationships in a data set through a process that mimics the operations of a human brain. It may be used in many real-life applications such as speech and voice recognition, eCommerce, cybersecurity, etc. The activation function is one of the vital parts of neural networks, which affects the performance of neural network applications. Moreover, the choice of the activation function depends on the type of problem we want to solve. This paper presents a specific neuron activation function based on a property found in physical systems, “proteretic”. This prosperity is applied to the Walsh-based distributed memory. We show that using the proteretic function with the Walsh-based memory enhances the storage performance by making the network converge faster than the other neural network activation functions.

Keywords

• Neural network
• hysteresis
• porteresis
• walsh-based memory
• activation function
• convergence

Main Subjects

• Information technology