3 090 total contributions since 2011

Backgound in Electromagnetic Theory, Plasma Physics and Radar Target Identification using Neural Networks.

PhD Student, Research Assistant and Lecturer at Stanford;

AB, ScB, ScM Student; Research Assistant, Fellow and Professor at Brown;

27 yrs researching Ballistic and Theatre Missile Defense using Neural Networks at MIT Lincoln Laboratory. Retired 2003.

PLEASE DO NOT SEND QUESTIONS AND DATA TO MY EMAIL. HOWEVER, CAN SEND LINKS TO POSTS.

Professional Interests: Neural Netwoks, Spectral Analysis

Answered

Is the "patternnet" a fully connected neural network

Yes. The only difference between my classifiers and regressors is the sigmoid output layer instead of linear. Hope this helps....

Is the "patternnet" a fully connected neural network

Yes. The only difference between my classifiers and regressors is the sigmoid output layer instead of linear. Hope this helps....

ungefär 3 timmar ago | 0

Answered

How to train and test time series data in Neural Network Toolbox

I order to test a net you have to compare the actual output with the desired output. Hope this helps. THANK YOU FOR FORMALLY...

How to train and test time series data in Neural Network Toolbox

I order to test a net you have to compare the actual output with the desired output. Hope this helps. THANK YOU FOR FORMALLY...

3 dagar ago | 0

Answered

Artificial Neural Network implementation and to know the importance of each of the input on output(Response) - wanted help

The way I determine the importance of a single input is 1. Calculate the error using all inputs 2. Loop over inputs ...

Artificial Neural Network implementation and to know the importance of each of the input on output(Response) - wanted help

The way I determine the importance of a single input is 1. Calculate the error using all inputs 2. Loop over inputs ...

3 dagar ago | 0

| accepted

Answered

transfer function purelin equation based on neural network toolbox

Read the documentation help purelin doc purelin Greg

transfer function purelin equation based on neural network toolbox

Read the documentation help purelin doc purelin Greg

12 dagar ago | 0

Answered

How to use a sequenceInputLayer with a regressionLayer (neural networks) ?

The answer is obvious: help regressionlayer doc regressionlayer *Thank you for formally accep...

How to use a sequenceInputLayer with a regressionLayer (neural networks) ?

The answer is obvious: help regressionlayer doc regressionlayer *Thank you for formally accep...

19 dagar ago | 0

Answered

Time Domain Signal for neural network

If you have rpm I don't see why time is important. However, there is no reason you cannot do both and see what difference it ma...

Time Domain Signal for neural network

If you have rpm I don't see why time is important. However, there is no reason you cannot do both and see what difference it ma...

19 dagar ago | 0

| accepted

Answered

Adding hidden layers to a patternnet hurts accuracy?

The global minimum is achievable with a single hidden layer. With more hidden layers you add more local minima; most of which ...

Adding hidden layers to a patternnet hurts accuracy?

The global minimum is achievable with a single hidden layer. With more hidden layers you add more local minima; most of which ...

20 dagar ago | 0

| accepted

Answered

Training neural network - Forward Pass

You are very mixed up. I suggest going to the library and finding a good elementary NN book. Obviously, the appropriate info is...

Training neural network - Forward Pass

You are very mixed up. I suggest going to the library and finding a good elementary NN book. Obviously, the appropriate info is...

20 dagar ago | 0

Answered

Hello, I'm working with artificial neural network.

Three layers are sufficient: input/hidden/output The input layer is NOT a neuron layer. The number of input nodes is the dimens...

Hello, I'm working with artificial neural network.

Three layers are sufficient: input/hidden/output The input layer is NOT a neuron layer. The number of input nodes is the dimens...

22 dagar ago | 0

| accepted

Answered

Why neural network gives negative output ?

How different is the new data (e.g., Mahalanobis distance)? If you know the true outputs, how do the error rates compare? If y...

Why neural network gives negative output ?

How different is the new data (e.g., Mahalanobis distance)? If you know the true outputs, how do the error rates compare? If y...

22 dagar ago | 0

| accepted

Answered

Rsq from NMSE in NN

NMSE = mse(trnopdb-net(trnipdb))/MSE00 i.e., NO TRANSPOSES 2. Rsq = R^2 3. Yes. Use separate calculations fo...

Rsq from NMSE in NN

NMSE = mse(trnopdb-net(trnipdb))/MSE00 i.e., NO TRANSPOSES 2. Rsq = R^2 3. Yes. Use separate calculations fo...

22 dagar ago | 1

| accepted

Answered

HOW DO I SEARCH IN ANSWERS ???

Oh! It only opens up at the top of the page if the page is sufficiently wide. Since I often use large type and 2 pages per scre...

HOW DO I SEARCH IN ANSWERS ???

Oh! It only opens up at the top of the page if the page is sufficiently wide. Since I often use large type and 2 pages per scre...

27 dagar ago | 0

| accepted

Answered

Interpolation using Neural Networks

Plot the data. Look at the plots Are there regions that are seasonal? Separate the data that is relevant to your problem Ca...

Interpolation using Neural Networks

Plot the data. Look at the plots Are there regions that are seasonal? Separate the data that is relevant to your problem Ca...

28 dagar ago | 0

| accepted

Answered

How to plot only few classes for confusion matrix?

Oviously, you have to subsample the original matrices. Greg

How to plot only few classes for confusion matrix?

Oviously, you have to subsample the original matrices. Greg

29 dagar ago | 0

Answered

Open loop Training performance and closed loop training performance are good but multi-step prediction is bad. Reason?

You are not considering information from the autocorrelation fuction. Hope this helps Greg

Open loop Training performance and closed loop training performance are good but multi-step prediction is bad. Reason?

You are not considering information from the autocorrelation fuction. Hope this helps Greg

30 dagar ago | 0

Answered

Formula for two layer FFNN

y1 = b1 + IW1 * x y2 = b2 + LW2 * tanh( y1 ) y3 = b3 + LW3 * tanh( y2 ) = b3 + LW3 * tanh( b2 + LW2 * tanh( b1 + IW1 * x ...

Formula for two layer FFNN

y1 = b1 + IW1 * x y2 = b2 + LW2 * tanh( y1 ) y3 = b3 + LW3 * tanh( y2 ) = b3 + LW3 * tanh( b2 + LW2 * tanh( b1 + IW1 * x ...

ungefär en månad ago | 0

| accepted

Answered

Input and target have different number of sampel

Train and TTrain have to be transposed. Hope this helps. THANK YOU FOR FORMALLY ACCEPTING MY ANSWER Greg

Input and target have different number of sampel

Train and TTrain have to be transposed. Hope this helps. THANK YOU FOR FORMALLY ACCEPTING MY ANSWER Greg

ungefär en månad ago | 0

| accepted

Answered

How to calculate accuracy for neural network algorithms?

I normalize the mean-square-error MSE = mse(error) = mse(output-target) by the minimum MSE obtained when th...

How to calculate accuracy for neural network algorithms?

I normalize the mean-square-error MSE = mse(error) = mse(output-target) by the minimum MSE obtained when th...

ungefär en månad ago | 0

| accepted

Answered

Neural Network input and targets have different of samples

Transpose both matrices. Thank you for formally accepting my answer Greg

Neural Network input and targets have different of samples

Transpose both matrices. Thank you for formally accepting my answer Greg

ungefär en månad ago | 0

| accepted

Answered

How these plots (Performance, Training state, Regression) shows the training performance? How to figure out the training rate from these plots?

Training data plots are useful. However, there is no indication of how good the net will perform on nontraining data (THE TRUE ...

How these plots (Performance, Training state, Regression) shows the training performance? How to figure out the training rate from these plots?

Training data plots are useful. However, there is no indication of how good the net will perform on nontraining data (THE TRUE ...

ungefär en månad ago | 0

Answered

Validation check = 0 for traingdm

What you are worrying about is irrelevant. Your data is so good you don't even need a validation subset.The main purpose of a va...

Validation check = 0 for traingdm

What you are worrying about is irrelevant. Your data is so good you don't even need a validation subset.The main purpose of a va...

ungefär en månad ago | 1

Answered

Expressing equation in terms of sin/cos

If you substitute your solutions into LHS and get the RHS, then it is possible. Greg

Expressing equation in terms of sin/cos

If you substitute your solutions into LHS and get the RHS, then it is possible. Greg

ungefär 2 månader ago | 0

Answered

How to decide window size for a moving average filter?

I'm very surprised that none of the previous responses mentioned 1. Determine characteristic self correlation lengths usi...

How to decide window size for a moving average filter?

I'm very surprised that none of the previous responses mentioned 1. Determine characteristic self correlation lengths usi...

ungefär 2 månader ago | 0

Answered

finding optimal neural network architecture using genetic algorithms

0. The genetic approach is a waste of time. It takes too long. 1.Typically, a single hidden layer is sufficient. 2. Minimize t...

finding optimal neural network architecture using genetic algorithms

0. The genetic approach is a waste of time. It takes too long. 1.Typically, a single hidden layer is sufficient. 2. Minimize t...

ungefär 2 månader ago | 0

Answered

Neuron Network input variables-Missing data

Sorry: You have to predict the missing data as best you can. Greg

Neuron Network input variables-Missing data

Sorry: You have to predict the missing data as best you can. Greg

ungefär 2 månader ago | 0

Answered

Why my network is not giving the desired output

Design(training+validation), test and new data should all have the same summary statistics BEFORE NORMALIZATION. This may requir...

Why my network is not giving the desired output

Design(training+validation), test and new data should all have the same summary statistics BEFORE NORMALIZATION. This may requir...

2 månader ago | 0

| accepted

Answered

How to predict future responses y(t + 1) from the training of a narxnet network with past data of x (t) and y (t)? (NARXNET)

YOU DO NOT HAVE X and Y !!! YOU HAVE X and T where T = Ydesired Hope this helps Thank you for formally accepting m...

How to predict future responses y(t + 1) from the training of a narxnet network with past data of x (t) and y (t)? (NARXNET)

YOU DO NOT HAVE X and Y !!! YOU HAVE X and T where T = Ydesired Hope this helps Thank you for formally accepting m...

2 månader ago | 1

| accepted

Answered

Testing a Backpropagation Neural Network

You are probably OVERTRAINING AN OVERFIT NET OVERFITTING: Using more unknown hidden nodes than number ...

Testing a Backpropagation Neural Network

You are probably OVERTRAINING AN OVERFIT NET OVERFITTING: Using more unknown hidden nodes than number ...

2 månader ago | 0

| accepted

Answered

The performance of hidden neurons

I think I misinterpreted the question. Now I think you mean when I increase the number of hidden nodes from 4 to 5 why do I star...

The performance of hidden neurons

I think I misinterpreted the question. Now I think you mean when I increase the number of hidden nodes from 4 to 5 why do I star...

2 månader ago | 0

Answered

Crossentropy loss function - What is a good performance goal?

These equations are not necessarily precise. For example: data = design + test design = training + validation In partic...

Crossentropy loss function - What is a good performance goal?

These equations are not necessarily precise. For example: data = design + test design = training + validation In partic...

2 månader ago | 0