Modelling the XOR/XNOR Boolean functions complexity using neural network

P. W.C. Prasad; A. K. Singh; Azam Beg; Ali Assi

doi:10.1109/ICECS.2006.379732

Modelling the XOR/XNOR Boolean functions complexity using neural network

P. W.C. Prasad, A. K. Singh, Azam Beg, Ali Assi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Citations (Scopus)

Abstract

This paper propose a model for the complexity of Boolean functions with only XOR/XNOR min-terms using back propagation neural networks (BPNNs) applied to Binary Decision Diagrams (BDDs). The developed BPNN model (BPNNM) is obtained through the training process of experimental data using Brain Maker software package. The outcome of this model is a unique matrix for the complexity estimation over a set of BDDs derived from randomly generated Boolean expressions with a given number of variables and XOR/XNOR min-terms. The comparison results of the experimental and back propagation neural networks mode (BPNNM) underline the efficiency of this approach, which is capable of providing some useful clues about the complexity of the final circuit implementation.

Original language	English
Title of host publication	ICECS 2006 - 13th IEEE International Conference on Electronics, Circuits and Systems
Pages	1348-1351
Number of pages	4
DOIs	https://doi.org/10.1109/ICECS.2006.379732
Publication status	Published - Dec 1 2006
Event	ICECS 2006 - 13th IEEE International Conference on Electronics, Circuits and Systems - Nice, France Duration: Dec 10 2006 → Dec 13 2006

Publication series

Name	Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems

Other

Other	ICECS 2006 - 13th IEEE International Conference on Electronics, Circuits and Systems
Country/Territory	France
City	Nice
Period	12/10/06 → 12/13/06

ASJC Scopus subject areas

Engineering(all)

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10.1109/ICECS.2006.379732

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Prasad, P. W. C., Singh, A. K., Beg, A., & Assi, A. (2006). Modelling the XOR/XNOR Boolean functions complexity using neural network. In ICECS 2006 - 13th IEEE International Conference on Electronics, Circuits and Systems (pp. 1348-1351). Article 4263625 (Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems). https://doi.org/10.1109/ICECS.2006.379732

Modelling the XOR/XNOR Boolean functions complexity using neural network. / Prasad, P. W.C.; Singh, A. K.; Beg, Azam et al.
ICECS 2006 - 13th IEEE International Conference on Electronics, Circuits and Systems. 2006. p. 1348-1351 4263625 (Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Prasad, PWC, Singh, AK, Beg, A & Assi, A 2006, Modelling the XOR/XNOR Boolean functions complexity using neural network. in ICECS 2006 - 13th IEEE International Conference on Electronics, Circuits and Systems., 4263625, Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems, pp. 1348-1351, ICECS 2006 - 13th IEEE International Conference on Electronics, Circuits and Systems, Nice, France, 12/10/06. https://doi.org/10.1109/ICECS.2006.379732

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Modelling the XOR/XNOR Boolean functions complexity using neural network

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