Optimal design of a general type-2 fuzzy classifier for the pulse level and its hardware implementation

. Nowadays, soft computing has been of great help in solving real-world problems and satisfying the needs in our everyday life. We require more than ever the development and implementation of models and techniques that assist in medical issues due to the recent pandemic. The aim of this work is the development and hardware implementation of a general type-2 fuzzy classifier for the pulse levels and the optimization of the general type 2 membership functions parameters using the Ant Lion Optimizer to compare results of type 1 and interval type-2 fuzzy classifiers with the patients of the Framingham database. This study additionally explains the implementation process of the general type-2 fuzzy classifier on the Jetson Nano hardware Development Board and the comparison of execution time with interval type-2, and type-1 fuzzy classifiers. This work offers a novel perspective in that the general type-2 fuzzy classifier can be implemented for embedded applications with excellent performance regarding hardware resources consumption.

Automated summary

This study focuses on the development and application of a general type-2 fuzzy classifier to address medical issues, specifically targeting pulse levels for experimentation and comparison with different types of fuzzy classifiers, offering a new perspective for embedded applications.