A new gradient descent algorithm for unconstrained optimization problem is proposed.
提出了一种新的无约束优化下降算法.
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Gradient descent algorithm using momentum BP network training.
采用动量梯度下降算法训练BP网络.
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In this paper, a class of new descent algorithm is proposed to solve unconstrained optimization problems.
研究给出了一类新的求解无约束优化问题的下降算法.
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Usually, the steepest descent algorithm is used to find the minimum of LOO upper - bound.
通过最速下降法求LOO上界的极小点来确定核参数是一种新的核参数选择方法.
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Finally, all of the parameters of the T - S model are determined accurately with gradient descent algorithm.
最后, 通过梯度下降方法,精确确定T -S 模糊模型的所有参数.
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