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Error Back Propagation Algorithm Matlab Code

Implementation Of Backpropagation Neural Networks With Matlab
Back Propagation Neural Network Matlab Tutorial
Matlab Programs For Neural Networks

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Implementation Of Backpropagation Neural Networks With Matlab

answers Reputation: 1 Vote1 how to implement back propagation algorithm in matlab? Asked by Sansri Basu Sansri Basu (view profile) 10 questions 0 answers 0 accepted answers Reputation: 1 on 4 Apr 2014 Latest activity Answered by Abdullah Abdullah (view profile) 0 questions 1 answer 0 accepted answers Reputation: 0 on 2 Dec 2014 Accepted Answer by Niklas backpropagation matlab code download Nylén Niklas Nylén (view profile) 2 questions 70 answers 35 accepted answers Reputation: 150 615 views (last 30 days) 615 views (last 30 days) please help me with the matlab code for the back propagation algorithm 0 Comments Show all comments Tags No tags are associated with this question. Products No products are associated with this question. Related Content 2 Answers Niklas Nylén (view profile) 2 questions 70 answers 35 accepted answers Reputation: 150 Vote0 Link Direct link to this answer: https://www.mathworks.com/matlabcentral/answers/124441#answer_132098 Answer by Niklas Nylén Niklas Nylén (view profile) 2 questions 70 answers 35 accepted answers Reputation: 150 on 4 Apr 2014 Accepted answer
Googled 'Back propagation algorithm matlab' and this was the first result: http://anoopacademia.wordpress.com/2013/09/29/back-propagation-algorithm-using-matlab/comment-page-1/ 2 Comments Show all comments Sansri Basu Sansri Basu (view profile) 10 questions 0 answers 0 accepted answers Reputation: 1 on 4 Apr 2014 Direct link to this comment: https://www.mathworks.com/matlabcentral/answers/124441#comment_206077 the code shows error in line 7 as: 'Input argument "Input" is undefined.' Niklas Nylén Niklas Nylén (view profile) 2 questions 70 answers 35

Back Propagation Neural Network Matlab Tutorial

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Ask Answer Browse More Contributors Recent Activity Flagged Content Flagged as Spam Help Trial software Ashikur (view profile) 11 questions 5 answers 2 accepted answers Reputation: 8 Vote0 Back https://www.mathworks.com/matlabcentral/answers/124441-how-to-implement-back-propagation-algorithm-in-matlab propagation algorithm of Neural Network : XOR training Asked by Ashikur Ashikur (view profile) 11 questions 5 answers 2 accepted answers Reputation: 8 on 22 Jan 2012 Latest activity Answered by Sohel Ahammed Sohel Ahammed (view profile) 3 questions 1 answer 0 accepted answers Reputation: 0 on 4 Jul 2015 Accepted Answer by Greg Heath Greg Heath (view profile) 13 https://www.mathworks.com/matlabcentral/answers/26773-back-propagation-algorithm-of-neural-network-xor-training questions 2,398 answers 1,728 accepted answers Reputation: 4,702 486 views (last 30 days) 486 views (last 30 days) c=0;wih = .1*ones(nh,ni+1);who = .1*ones(no,nh+1); while(c<3000) c=c+1; for i = 1:length(x(1,:)) for j = 1:nh netj(j) = wih(j,1:end-1)*double(x(:,i))+wih(j,end)*1; outj(j) = 1./(1+exp(-1*netj(j))); end% hidden to output layer for k = 1:no netk(k) = who(k,1:end-1)*outj'+who(k,end)*1; outk(k) = 1./(1+exp(-1*netk(k))); delk(k) = outk(k)*(1-outk(k))*(t(k,i)-outk(k)); end% back proagation for j = 1:nh s=0; for k = 1:no s = s+who(k,j)*delk(k); end delj(j) = outj(j)*(1-outj(j))*s; s=0; end for k = 1:no for l = 1:nh who(k,l)=who(k,l)+.5*delk(k)*outj(l); end who(k,l+1)=who(k,l+1)+1*delk(k)*1; end for j = 1:nh for ii = 1:ni wih(j,ii)=wih(j,ii)+.5*delj(j)*double(x(ii,i)); end wih(j,ii+1)=wih(j,ii+1)+1*delj(j)*1; end endend// The code above, I have written it to implement back propagation neural network, x is input , t is desired output, ni , nh, no number of input, hidden and output layer neuron. I am testing this for different functions like AND, OR, it works fine for these. But XOR is not working.// Training x = [0 0 1 1; 0 1 0 1] // Training t = [0 1 1 0]// who -> we

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here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about Stack Overflow the company Business Learn more about hiring developers or posting ads with us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 4.7 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up Back propagation algorithm: error computation up vote 1 down vote favorite 1 I am currently writing a back propagation script. I am unsure how to go about updating my weight values. Here is an image just to make things simple. My question: How is the error calculated and applied? I do know that k1 and k2 produce error values. I know that k1 and k2 produce individual error values (target - output). I do not however know if these are to be used. Am I supposed to use the mean value of both error values and then apply that single error value to all of the weights? Or am I supposed to: update weight Wk1j1 and Wk1j2 with the error value of k1 update weight Wk2j1 and Wk2j2 with the error value of k2 update weight Wj1i1 and Wj1i2 with the error value of j1 update weight Wj2i1 and Wj2i2 with the error value of j2 Before you start shooting, I understand that I must use sigmoids function etc. THIS IS NOT THE QUESTION. It always states that I have to calculate the error value for the outputs, this is where I am confused. and then get the net error value by: ((error_k1^2) + (error_k2^2) + (error_j1^2) + (error_j2^2)) / 2 From Wiki: As the image states this is true for each of the output nodes, in my image example k1 and k2. The wiki. The two rows under the image is delta Wh and delta Wi. Which error value am I supposed to use (this is basically my question, which error value am I supposed to calculate the new weight with) Answer: http://www4.rgu.ac.uk/files/chapter3%20-%20bp.pdf page 3(notad as 18) #4 matlab artificial-intelligence backpropagation share|improve this

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