Abstract
A class of neural dynamics, called Zhang dynamics (ZD), has been proposed to solve online various time-varying problems. In this paper, different Z-type (Zhang type) models based on different Zhang functions (ZFs) are proposed, investigated and simulated for solving the time-varying inverse square root (or in short, TVISR) problem. Then, for the same problem-solving task, different G-type (gradient type) models based on different energy functions (EFs) are developed and investigated as well. Moreover, the convergence analyses of Z-type and G-type models are studied in-depth for the completeness of this paper. Besides, for possible circuit and/or computer realization, Matlab Simulink modeling of Z-type and G-type models is illustrated. Through illustrative examples, the efficacy and superiority of the proposed Z-type and G-type models for TVISR problem solving are verified and substantiated.
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Acknowledgments
This work is supported by National Natural Science Foundation of China under grants 61075121 and 60935001, the 2012 Scholarship Award for Excellent Doctoral Student granted by Ministry of Education of China under grant 3191004, and also the Specialized Research Fund for the Doctoral Program of Institutions of Higher Education of China with project number 20100171110045. Besides, the authors would like to thank the editors and anonymous reviewers for their time and effort spent in handling the paper, as well as for providing the constructive comments for improving the presentation and quality of this paper.
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Communicated by C. Alippi, D. Zhao and D. Liu.
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Zhang, Y., Li, Z., Guo, D. et al. Z-type and G-type models for time-varying inverse square root (TVISR) solving. Soft Comput 17, 2021–2032 (2013). https://doi.org/10.1007/s00500-013-1124-5
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DOI: https://doi.org/10.1007/s00500-013-1124-5