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Talk:Feedforward neural network

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slp

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The last paragraph in Single-layer Perceptron seems irrelevant and out of place since it's solely about Multi-layer Perceptrons. It should be in the next section. --134.100.6.103 (talk) 12:53, 22 July 2013 (UTC)[reply]

overview

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This is a very basic page and I am hoping to update it. Paskari 14:26, 30 November 2006 (UTC)[reply]

Picture

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I recently included the picture, if anyone can make a better one please replace itPaskari 14:26, 30 November 2006 (UTC)[reply]


In the picture descibing the XOR function, shouldn't the output be 0 when x=y=1 ? 132.168.90.105 (talk) 13:40, 3 March 2016 (UTC) Julien Borrel[reply]

It wasn't making sense to me either. It turns out that the threshold being reached ends up with a 0 or 1 value resulting, for example, in 0 or -2 when the -2 weight is applied and never a -4.
I hope my changes to the XOR diagram description are correct and readable.
For the reviewers:
The equal signs within triplets represent threshold of 2 results.:
From input layer on up:
0,0 -> 0,0,0 -> 0+0+0 -> 0
0,1 -> 0,1=0,0 -> 1-0+0 -> 1
1,0 " " "
1,1 -> 1,2=1,0 -> 1-2+1 -> 0 JJones587 (talk) 11:33, 15 May 2023 (UTC)[reply]
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Stanford: What's so cool about feed-forward networks? —Preceding unsigned comment added by 178.128.58.224 (talk) 04:03, 13 January 2011 (UTC)[reply]

ADELINE part

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Currently in the text there is no connection between the ADELINE chapter and the previous chapters, what does ADELINE do for ff-nn? I think the part should be removed or expanded to make that connection. (Background, I'm a MSc level Computer Science student) 82.157.46.201 (talk) 14:11, 17 January 2013 (UTC)[reply]

References

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This really need more citations. Which paper first used the word feedfoward in this context, and which books gave a formal definition (in terms of graph theory?

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