How to build a neural network which is not Fully-connected with NN toolbox?
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Hi, I'm using NN toolbox to build my own network. The problem is that it seems that NN toolbox offers only fully-connected network. The image attached can be one example. Is there any way that I can build a neural network with disconnecting some weights?
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/189351/image.png)
1 个评论
Itay Hanoch
2020-9-24
Hi,
I run into the same problem as you,
Trying to find a way to disconnect specific weight in a layer,
Did you you found a way to deal with this problem at the end?
回答(1 个)
Greg Heath
2018-4-13
The best approach is to find, via an exhaustive search within bounds, the minimum number of hidden nodes that will yield your desired result.
I have posted ZILLIONS of examples in both the NEWSGROUP (comp.soft-sys.matlab) and ANSWERS.
For
1. N I-dimensional "I"nputs yielding N O-dimensional "O"utputs
2. Default 0.7/0.15/0.15 data division
3. H hidden units in a default I-H-O node topology
Ntrneq ~ 0.7*N*O % No. of training equations
Nw = (I+1)*H+(H+1)*O % No. of unknown weights
Find the minimum number of hidden units that will guarantee
Ntrneq >= Nw
or
H <= (Ntrneq-O)/(I+O+1)
subject to the following target variance performance constraint on the error
error = target-output
mse(error) <= 0.01*var(target',1)
Hope this helps.
Thank you for formally accepting my answer
Greg
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