How to build a neural network which is not Fully-connected with NN toolbox?
조회 수: 3 (최근 30일)
이전 댓글 표시
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?
댓글 수: 1
Itay Hanoch
2020년 9월 24일
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?
답변 (1개)
Greg Heath
2018년 4월 13일
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
참고 항목
카테고리
Help Center 및 File Exchange에서 Sequence and Numeric Feature Data Workflows에 대해 자세히 알아보기
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!