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Training multilayer feedforward neural networks using dynamic programming
The dynamic programming method is implemented as an alternative supervised training algorithm for designing multilayer feedforward artificial neural networks. The author demonstrates its feasibility and competitiveness by two examples. It helps to set a stage for further research and applications.
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