- 期刊
Convergence of Split-Complex Backpropagation Algorithm with a Momentum
並列摘要
This paper investigates a split-complex backpropagation algorithm with momentum (SCBPM) for complex-valued neural networks. Convergence results for SCBPM are proved under relaxed conditions and compared with the existing results. Monotonicity of the error function during the training iteration process is also guaranteed. Two numerical examples are given to support the theoretical findings.
延伸閱讀
- Zhao, J., & Zhang, H. (2014). Solving Split Common Fixed-Point Problem of Firmly Quasi-Nonexpansive Mappings without Prior Knowledge of Operators Norms. Abstract and Applied Analysis, 2014(), 430-438-552. https://doi.org/10.1155/2014/389689
- HILTON, P., & PEDERSEN, J. (1987). ON THE COMPLEMENTARY FACTOR IN A NEW CONGRUENCE ALGORITHM. International Journal of Mathematics and Mathematical Sciences, 1987(), 113-123. https://doi.org/10.1155/S0161171287000140
- Li, H. J., Liou, Y. C., Li, C. L., Noor, M. A., & Yao, Y. H. (2012). An Implicit Algorithm for Maximal Monotone Operators and Pseudocontractive Mappings. Abstract and Applied Analysis, 2012(), 1402-1414-393. https://doi.org/10.1155/2012/517460
- Chen, C. Y. (1993). A Multi-level Backpropagation Network for Pattern Recognition Systems [master's thesis, Yuan Ze University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0009-0112200611360486
- Hamdi, A., Noor, M. A., & Mukheimer, A. A. (2012). Convergence of a Proximal Point Algorithm for Solving Minimization Problems. Journal of Applied Mathematics, 2012(), 529-541-035. https://doi.org/10.1155/2012/142862