A Framework for Multiprocessor Neural Networks Systems

Mohamad, Mumtazimah (2012) A Framework for Multiprocessor Neural Networks Systems. In: International Conference on ICT Convergence (ICTC), 15-17 September 2012, South Korea.

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Abstract

Abstract—Artificial neural networks (ANN) are able to simplify classification tasks and have been steadily improving both in accuracy and efficiency. However, there are several issues that need to be addressed when constructing an ANN for handling different scales of data, especially those with a low accuracy score. Parallelism is considered as a practical solution to solve a large workload. However, a comprehensive understanding is needed to generate a scalable neural network that is able to achieve the optimal training time for a large network. Therefore, this paper proposes several strategies, including neural ensemble techniques and parallel architecture, for distributing data to several network processor structures to reduce the time required for recognition tasks without compromising the achieved accuracy. The initial results indicate that the proposed strategies are able to improve the speed up performance for large scale neural networks while maintaining an acceptable accuracy.

Item Type: Conference or Workshop Item (Speech)
Keywords: Artificial neural networks, back propagation,ensemble, multiprocessor,parallel
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Institute: Faculty of Informatics & Computing
Depositing User: Dr Mumtazimah Mohamad
Date Deposited: 11 May 2014 06:51
Last Modified: 23 Apr 2015 03:10
URI: http://erep.unisza.edu.my/id/eprint/497

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