Differrence between feed forward & feed forward back propagation
11 views (last 30 days)
Show older comments
omar belhaj
on 18 Feb 2015
Commented: YERRUPALLI GANESH
on 19 Dec 2020
I used neural netowrk MLP type to pridect solar irradiance, in my code i used fitnet() commands (feed forward)to creat a neural network.But some people use a newff() commands (feed forward back propagation) to creat their neural network. please what's difference between two types?? :
net=fitnet(Nubmer of nodes in haidden layer); --> it's a feed forward ?? true??
net=newff(Nubmer of nodes in haidden layer); ---> it's a feed forward back propagation ??
Help me please wchich one can i choose for my case (prediction problem)???!!! Who appripriate??
Best regards
2 Comments
YERRUPALLI GANESH
on 19 Dec 2020
Difference between levenberg matquardt and feed forward backpropagation algorithm
Accepted Answer
Greg Heath
on 18 Feb 2015
Edited: Greg Heath
on 22 Feb 2015
1. Regardless of how it is trained, the signals in a feedforward network flow in one direction: from input, through successive hidden layers, to the output.
2. Given a trained feedforward network, it is IMPOSSIBLE to tell how it was trained (e.g., genetic, backpropagation or trial and error)
3. A feedforward backpropagation net is a net that just happened to be trained with a backpropagation training algorithm. The backpropagation training algorithm subtracts the training output from the target (desired answer) to obtain the error signal. It then goes BACK to adjust the weights and biases in the input and hidden layers to reduce the error.
4. Current examples of feedforward nets are
a. FITNET for regression and curve-fitting which calls the generic FEEDFORWARDNET
b. PATTERNNET for classification and pattern-recognition which calls the generic FEEDFORWARDNET
c. FEEDFORWARDNET
5. OBSOLETE examples of feedforward nets are
a. NEWFIT for regression and curve-fitting which calls the generic NEWFF
b. NEWPR for classification and pattern-recognition which calls the generic NEWFF
c. NEWFF
6. The default training functions for the above algorithms use backpropagation. However, the designer can train the nets any way they want.
7. The Neural Network Toolbox does not offer a genetic algorithm (GA). However, there are posts to the NEWSGROUP and ANSWERS regarding training with a GA
SEARCH WORDS NEWSGROUP HITS ANSWERS HITS
NEURAL GA 69 39
NEURAL GENETIC 132 56
8. None of the above are recommended for timeseries forecasting. The CURRENT timeseries forecasting algorithms are
a. TIMEDELAYNET: Feedforward net with output that only depends on current and past inputs
b. NARNET: Feedback net with output that only depends on past outputs
c. NARXNET: Feedback net with output that depends on BOTH past outputs as well as current and past inputs
Hope this helps.
Thank you for formally accepting my answer
Greg
P.S. Online documentation for any function can be obtained using the commands help, doc and type. For example
help fitnet
doc fitnet
type fitnet
4 Comments
Greg Heath
on 5 Apr 2015
Edited: Greg Heath
on 5 Apr 2015
Although both FITNET and PATTERNNET call FEEDFORWARDNET, each have different defaults w.r.t. their specific function, i.e., regression/curve-fitting vs classification/pattern-recognition.
So, just use FITNET and PATTERNNET.
More Answers (2)
khan
on 18 Feb 2015
what you said it suggest that the new function have both forward and backward propagation in the same function. Where is the old have only forward pass. You should right click and select help on each of them and you will see.
2 Comments
Greg Heath
on 5 Apr 2015
@Khan
No. the new functions are just revised versions of the old ones. If you use the commands DOC, HELP, and/or TYPE, you will see that NEWFIT, NEWPR and NEWFF are OBSOLETE and as such, will no longer be maintained by MATLAB.
@omar:
For forecasting/predicting the future, use TIMEDELAYNET(only inputs), NARNET(only output feedback) or NARXNET(both inputs and output feedback). Again, use DOC, HELP, and/or TYPE for details.
Greg
Shireen Shah
on 29 May 2018
can you please tell me which command(newff or feedforwardnet) is good choice to be used for channel estimation in OFDM using neural networks?
1 Comment
Greg Heath
on 21 Oct 2018
Use
FITNET for regression
and
PATTERNNET for classification
Both are special cases of FEEDFORWARDNET.
Corresponding NEWFIT, NEWPR and NEWFF are obsolete and have been replaced by the above.
See Also
Categories
Find more on Sequence and Numeric Feature Data Workflows in Help Center and File Exchange
Products
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!