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首先,非常感谢《零基础入门深度学习》作者hanbingtao付出的辛苦努力,提供了这么好的教程和代码程序。
误差项沿时间的反向传递 公式(13)明显写错了。 将误差项向前传递到任意k时刻的公式:
原公式是采用从j=k到j=t-1求delta(j),然后把各个delta(j)乘起来,得到delta(k)。这显然是错误的,应当采用循环处理,已知delta(t),用原文中公式(58)求出delta(t-1),反复使用公式(58)直至求出delta(k)。而不是连乘积的形式。
从原文给出的样例代码lstm.py也可以看出这一点,是采用循环处理,逐步沿时间前移,而不是连乘积的算法。
The text was updated successfully, but these errors were encountered:
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首先,非常感谢《零基础入门深度学习》作者hanbingtao付出的辛苦努力,提供了这么好的教程和代码程序。
误差项沿时间的反向传递 公式(13)明显写错了。
δ k T = ∏ j = k t − 1 δ o , j T W o h + δ f , j T W f h + δ i , j T W i h + δ c ~ , j T W c h ( 式 13 )将误差项向前传递到任意k时刻的公式:
原公式是采用从j=k到j=t-1求delta(j),然后把各个delta(j)乘起来,得到delta(k)。这显然是错误的,应当采用循环处理,已知delta(t),用原文中公式(58)求出delta(t-1),反复使用公式(58)直至求出delta(k)。而不是连乘积的形式。
从原文给出的样例代码lstm.py也可以看出这一点,是采用循环处理,逐步沿时间前移,而不是连乘积的算法。
The text was updated successfully, but these errors were encountered: