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中文摘要：
为克服BP神经网络模型及其学习算法中的固有缺陷，构造了第二类Chebyshev前向神经网络模型，提出该神经网络模型权值直接确定法和结构自适应确定法．理论分析及仿真实验均表明，该系统弥补了BP神经网络的某些固有缺陷．相比同构型BP神经网络，其计算速度和工作精度均有大幅提高．
英文摘要：
To remedy the weaknesses of back propagation（BP） neural network model and its learning algorithm, a weights-di- rect-determination and structure-adaptive-determination method of feed-forward neural network activated with the 2nd -class Chebyshev orthogonal polynomials was developed. Theoretical analysis and simulation results both show that the proposed sys- tem can remedy the weaknesses of BP neural network model and its learning algorithm, and the calculation speed and working precision improve a lot comparing with the same structured BP neural network.
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