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How to do Single step ahead prediction of Lorenz chaotic time series using Feed Forward Backpropogation Neural Network.
d = 1 x = f(:,1:N-d); t = f(:,1+d:N); rng(0) H =10 % default net = fitnet(H); net.divideFcn = 'dividetrain'; .....

12 years ago | 1

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fft: significant peak in 0 Hz component
One of the basic assumptions is that that your data is a finite window sample of an infinitely periodic function. Very often the...

12 years ago | 1

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I created a neural network flow algorithm. I trained the data sets. An error that is" out of memory" is thrown for the image i loaded and trained. I would like to know a solution to overcome this problem.
The classical approach is to use image feature extraction to reduce the dimensionality of the input. There should be many posts ...

12 years ago | 1

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Answered
Actually I want to identify a system represented by linear equation using a neural network. I want to use gradient descent as my update rule.
What, exactly, do you mean by "identify" ? No problem if you have the NN Toolbox: Just use [] for number of hidden units. ...

12 years ago | 1

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Answered
Out-Sample normalization problem
Regardless of what you use in the model, I always standardize pre-modelling using zscore or mapstd to identify outliers for rem...

12 years ago | 1

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how to extract features from a satellite image will all feature matrices having same size?
Since each pixel has a different classification, the rxc image is columninzed and transposed to an Nx1 row. input = image(:)...

12 years ago | 1

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Reuse dimensionality reduction after designing model
I am unfamiliar with Neighborhood components analysis. PCA maximizes variance in the input space without regard to outputs. I...

12 years ago | 0

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How should i select inputs and outputs for a power load forecasting problem by back propagation method in neural networks?
select outputs by want you want predicted select inputs by using data that will help predict the outputs. Greg

12 years ago | 0

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How do I start coding for neural network time series?
You need continuation symbols after xlsread xlsread... Hope this helps. Greg

12 years ago | 0

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How to set target vector (with large data set) for neural network?
Regardless of data values, use MAPSTD or ZSCORE and training data to normalize inputs. For c classes, the target matrix shoul...

12 years ago | 0

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how to generate codebook for vector quantization using RBF neural network?
Use the functions lookfor, help, doc and type: >> lookfor lvq nnd14lv1 - NND4LV1 LVQ1 demonstration. ...

12 years ago | 0

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Answered
Reuse dimensionality reduction after designing model
PCA does not take into account the output variance. Therefore, it is suboptimal for classification. Use PLS instead. Whate...

12 years ago | 1

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When I am my training a elman neural network it is working only with 5 or lower no. of hidden layers, as I tried to increase no of layers its giving only 50% accuracy which means network is not trained proparly. what could probably go wraong?
It is VERY rare to have to use more than one hidden layer. MATLAB's version of ELMAN uses a poorer approximation of timeseries n...

12 years ago | 2

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Standalone doesn't recognize all functions?
It seems that net is not recognized. Explicitly introduce it in the call of the function. Hope this helps. *Thank you f...

12 years ago | 0

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Choosing training algorithm and performance function for neural network
Use patternnet for classification. help patternnet doc patternnet Search on greg patternnet Practice on a MATL...

12 years ago | 0

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For my project work I have used Elman neural network, with Resilient back propagation algorithm, Nguyen widrow algorithm for generating initial layer values. I observed lot difference between outputs in different trials
Search for one of my design examples greg net rng(0) greg net rng(4151941) greg net rng(default) As Walter has m...

12 years ago | 1

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How can I fix minmum mse requirement for neural network training mannually rather using default requirement?
[ I N ] = size(x) [ O N ] = size(t) % Reference MSEs (From Naïve Constant Output Model y00 = mean(ttrn,2)) Ntrn =...

12 years ago | 1

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How can I predict future temperature data lets say (20 days) without coding from historical data? (multi-step prediction)
Use the autocorrelation function to help determine which feedback lags are significant. For example, search using greg nncor...

12 years ago | 0

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Answered
how to get best test error/accuracy with neural networks pattern recognition ?
Obvious: 1. plot(x,t,'.') to estimate how much training data is really needed to adequately characterize the classes AND to i...

12 years ago | 0

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Neural Network - Multi Step Ahead Prediction
When the loop is closed, the net should be retrained with the original data and initial weights the same as the final weights of...

12 years ago | 1

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neural network training terminated prematurely
1. y2 ~= y1 because of network training. 2. In a repeat y3~= y1 and y4~=y2 because newff net creation creates random initial ...

12 years ago | 0

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How to do Single step ahead prediction of Lorenz chaotic time series using Feed Forward Backpropogation Neural Network.
help narnet doc narnet For practice help nndatasets Also search the NEWSGROUP and ANSWERS using greg narnet...

12 years ago | 0

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How should i select inputs and outputs for a power load forecasting problem by back propagation method in neural networks?
Your choice of inputs and outputs are chosen by YOUR needs. Your choice of neural network and initial choice of network parame...

12 years ago | 0

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Answered
How to get better test error/accuracy with neural networks?
1. Is there evidence that Hopt could be more than 10? i = 1:2:19 2. Since your data set is huge, why not use tic and toc to t...

12 years ago | 0

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How to train a neural network using multiple bmp images as input using the nntool
Target columns should be columns of the 36-dimensional unit matrix eye(36). help ind2ved help vec2ind *Thank you for fo...

12 years ago | 0

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Answered
How to get better test error/accuracy with neural networks?
0. I-H-O = 94-5-1 node topology; N =20,000 creation data pairs 1. Ntrneq = 0.7*N*O = 14,000 training equations but only ...

12 years ago | 0

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Reverse Engineering traingd in ANN?
type traingd % Initialize startTime = clock; original_net = net; [perf,vperf,tperf,gWB,gradient] = nntraining.perfs...

12 years ago | 0

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Neural Network ToolBox : Proper function to train multilabel data (Backpropogation )
>Which Inbuilt functions are suitable to train multilabel dataset ? using backpropogation ? Multilabel is just classificatio...

12 years ago | 0

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Answered
how to train a bottleneck neural network with code
1. What Toolbox is makebottle in? >> help makebottle makebottle not found. 2. The traditional definition of a bottlenec...

12 years ago | 0

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Answered
training multilabel data with traingdm function of Neural network toolbox
Whoops! I think I misled you. My answer assumed mutually exclusive classes. For non-mutually exclusive classes the targets ca...

12 years ago | 1