FU Qiang, WANG Pengjun, TONG Nan, WANG Mingbo, ZHONG Caiming. Integrated Polarity Optimization of MPRM Circuits Based on Improved Multi-objective Particle Swarm Optimization[J]. Chinese Journal of Electronics, 2020, 29(5): 833-840. doi: 10.1049/cje.2020.07.005
Citation: FU Qiang, WANG Pengjun, TONG Nan, WANG Mingbo, ZHONG Caiming. Integrated Polarity Optimization of MPRM Circuits Based on Improved Multi-objective Particle Swarm Optimization[J]. Chinese Journal of Electronics, 2020, 29(5): 833-840. doi: 10.1049/cje.2020.07.005

Integrated Polarity Optimization of MPRM Circuits Based on Improved Multi-objective Particle Swarm Optimization

doi: 10.1049/cje.2020.07.005
Funds:  This work is supported by the National Natural Science Foundation of China (No.61874078, No.61875098), and the K. C. Wong Magna Fund in Ningbo University.
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  • Corresponding author: WANG Pengjun (corresponding author) was born in 1966. He received the Ph.D. degree in electronic engineering from East China University of Chemical Technology. He is now a professor of Wenzhou University, a senior member of Chinese Institute of Electronics, senior member of Chinese Computer Federation, member of Electronic Circuits and Systems Professional Committee of Chinese Institute of Electronics. His research interests include multi-valued logic circuits and low power integrated circuit design theory. (Email:wangpengjun@wzu.edu.cn)
  • Received Date: 2018-10-17
  • Rev Recd Date: 2020-06-24
  • Publish Date: 2020-09-10
  • Aiming at the multi-objective polarity design of Mixed-polarity Reed-Muller (MPRM) circuit, such as small area and low power consumption, an integrated polarity optimization scheme based on improved Multi-objective particle swarm optimization (MOPSO) is proposed. In the Improved MOPSO (IMOPSO) algorithm, particles in the external archive can be actively evolved through self-learning operations to find better circuit polarity. The particles in the population achieve selflearning fractals by comparing the differences between their own states and individuals in external archive to enhance the evolutionary level of the population. A multiobjective decision model of area and power consumption is established according to the characteristics of MPRM circuit. The tabular technique and the IMPOPO algorithm are combined to obtain the Pareto optimal polarity set of the MPRM circuit for area and power consumption. The MCNC Benchmark circuit is used to test the performance of the algorithm. The results verify the effectiveness of the proposed algorithm.
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  • C. Monreiro, Y. Takahashi, and T. Sekine, "Low-power secure S-box circuit using charge-sharing symmetric adiabatic logic for advanced encryption standard hardware design", IET Circuits Devices & Systems, Vol.9, No.5, pp.362-369, 2015.
    A. Das and S. N. Pradhan, "Shared Reed-Muller decision diagram based thermal-aware AND-XOR decomposition of logic circuits", VLSI Design, Vol.2016, No.1, pp.1-14, 2016.
    C. Carvalho and V. G. L. Neumann, "The next-tominimal weights of binary projective Reed-Muller codes", IEEE Transactions on Information Theory, Vol.62, No.11, pp.6300-6303, 2016.
    Z. He, L. Xiao, L. Zhang, et al., "EMA-FPRMs:An efficient minimization algorithm for fixed polarity ReedMuller expressions", International Conference on FieldProgrammable Technology, IEEE, pp.253-256, 2017.
    Q. W. ZHANG, P. J. WANG, J. HU, et al., "Cube-based synthesis of ESOPs for large functions", Chinese Journal of Electronics, Vol.27, No.3, pp.527-534, 2018.
    L. Y. Wang, Y. S. Xia, and X. X. Chen, "Two-level MPRM functions optimization based on majority cubes", Journal of Electronics & Information Technology, Vol.34, No.4, pp.986-991, 2012.
    D. L. Bu and J. H. Jiang, "Dual logic based polarity conversion and optimization of mixed polarity RM circuits", Acta Electronica Sinica, Vol.43, No.1, pp.79-85, 2015.
    Q. FU, P. J. WANG, N. TONG, et al., "Multi-constrained polarity optimization of large-scale FPRM circuits based on multi-objective discrete particle swarm optimization", Journal of Electronics & Information Technology, Vol.39, No.3, pp.717-723, 2017.
    D. L. Bu, J. H. Jiang and W. L. Luo, "Two-phase GA based area and SER trade-off algorithm for MPRM circuits", Journal of Computer-Aided Design & Computer Graphics, Vol.29, No.10, pp.1924-1934, 2017.
    A. D. Falehi and A. Mosallanejad, "Neoteric HANFISCSSSC based on MOPSO technique aimed at oscillation suppression of interconnected multi-source power systems", IET Generation Transmission & Distribution, Vol.10, No.7, pp.1728-1740, 2016.
    Y. Zhang, D. Gong and J. Cheng, "Multi-objective particle swarm optimization approach for cost-based feature selection in classification", IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol.14, No.1, pp.64-75, 2017.
    N. Delgarm, B. Sajadi, F. Kowsary, et al., "Multi-objective optimization of the building energy performance:A simulationbased approach by means of particle swarm optimization (PSO)", Applied Energy, Vol.170, No.5, pp.293-303, 2016.
    Z. D. Jiang, Z. H. Wang and P. J. Wang, "Delay-area trade-off MPRM circuits based on hybrid discrete particle swarm optimization", Journal of Semiconductors, Vol.34, No.6, DOI:10.1088/1674-4926/34/6/065007, 2013.
    E. Hrynkiewicz and S. Ko?odziński, "An Ashenhurst disjoint and non-disjoint decomposition of logic functions in ReedMuller spectral domain", Proc. of the Mixed Design of Integrated Circuits and System, IEEE, Warsaw, pp.200-204, 2010.
    K. Roy and S. C. Prasad, Low-Power CMOS VLSI Circuit Design, John Wiley & Sons, Inc, 2000.
    L. A. Pereira, S. Haffner, G. Nicol, et al., "Multi-objective optimization of five-phase induction machines based on NSGA-II", IEEE Transactions on Industrial Electronics, Vol.64, No.12, pp.9844-9853, 2017.
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