Picture of scraped petri dish

Scrape below the surface of Strathprints...

Explore world class Open Access research by researchers at the University of Strathclyde, a leading technological university.

Explore

Multi-classify hybrid multilayered perceptron (HMLP) network for pattern recognition applications

Bin Hashim, Fakroul Ridzuan and Soraghan, John and Petropoulakis, Lykourgos (2012) Multi-classify hybrid multilayered perceptron (HMLP) network for pattern recognition applications. IFIP Advances in Information and Communication Technology, 381. pp. 19-27. ISSN 1868-4238

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

This paper introduces a Hybrid Multilayered Perceptron (HMLP) based classifier known as the Multi-Classify HMLP network (MCHMLP). This network is shown to be able to enhance the performance accuracy when compared to the conventional HMLP network. The Multi-Classify HMLP network architecture is trained using a Modified Recursive Prediction Error (MRPE). This study uses three benchmark datasets in order to measure the capability of the network. The results show that the proposed Multi-Classify HMLP network provides a significant improvement over the conventional HMLP network for pattern recognition applications.