An Improved Oscillating-Error Classifier with Branching

TL;DR

This paper introduces an enhanced oscillating-error classifier that incorporates branching to add layers, improving accuracy while maintaining consistency with neural network principles.

Contribution

It presents a novel branching method to extend the oscillating-error classifier, enabling higher accuracy and deeper correction layers.

Findings

Achieves higher classification accuracy.

Maintains consistency with neural network frameworks.

Extends previous oscillating-error techniques.

Abstract

This paper extends the earlier work on an oscillating error correction technique. Specifically, it extends the design to include further corrections, by adding new layers to the classifier through a branching method. This technique is still consistent with earlier work and also neural networks in general. With this extended design, the classifier can now achieve the high levels of accuracy reported previously.