3,112 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

NTSTOOL - How to get predicted values of "the future"?

The known time series is analyzed to yield a time-series model that uses past and present values to predict future values. The ...

NTSTOOL - How to get predicted values of "the future"?

The known time series is analyzed to yield a time-series model that uses past and present values to predict future values. The ...

4 days ago | 0

Answered

Timedelaynet output calculation principle

You did not include tHe 2 biases. Hope this helps. Greg THANK YOU FOR FORMALLY ACCEPTING MY ANSWER

Timedelaynet output calculation principle

You did not include tHe 2 biases. Hope this helps. Greg THANK YOU FOR FORMALLY ACCEPTING MY ANSWER

12 days ago | 0

Answered

Understand number of weights of Neural Network

It is possible. In general, however, you don't have the slightest idea what choice would be significantly better than random. ...

Understand number of weights of Neural Network

It is possible. In general, however, you don't have the slightest idea what choice would be significantly better than random. ...

29 days ago | 0

Answered

Using pca for features selections

PCA (Principal Coordinate Analysis) is a very useful method for regression (it ranks linear combinations of the original variabl...

Using pca for features selections

PCA (Principal Coordinate Analysis) is a very useful method for regression (it ranks linear combinations of the original variabl...

29 days ago | 0

Answered

How do we decide the number of hiddenlayers in a PatternNet?

patternnet(10) indicates ONE HIDDEN LAYER WITH TEN NODES It is important to be mindful of the number of layers and nodes. The ...

How do we decide the number of hiddenlayers in a PatternNet?

patternnet(10) indicates ONE HIDDEN LAYER WITH TEN NODES It is important to be mindful of the number of layers and nodes. The ...

2 months ago | 0

| accepted

Answered

Why sets Matlab automatically the activation functions for a neural network like this?

The simplest useful approximation is is a series of blocks with different heights and widths. The simplest useful DIFFERENTIAB...

Why sets Matlab automatically the activation functions for a neural network like this?

The simplest useful approximation is is a series of blocks with different heights and widths. The simplest useful DIFFERENTIAB...

2 months ago | 0

Answered

Artificial Neural Networks Hidden Layers

Number of input and output nodes is determined by the data. Number of hidden layers and nodes is determined by the program auth...

Artificial Neural Networks Hidden Layers

Number of input and output nodes is determined by the data. Number of hidden layers and nodes is determined by the program auth...

2 months ago | 0

| accepted

Answered

Neural Network Classification Results

The original class sizes are unequal. Hope this helps THANK YOU FOR FORMALLY ACEEPTING MY ANSWER Greg

Neural Network Classification Results

The original class sizes are unequal. Hope this helps THANK YOU FOR FORMALLY ACEEPTING MY ANSWER Greg

2 months ago | 0

Answered

Please help with narnext error Subscripted assignment dimension mismatch.????

x5=data_inputs(5,1:17); x6=data_inputs(6,1:17); x7=data_inputs(6,1:17); x8=data_inputs(7,1:17); x9=data_inputs(9,1:17); Hop...

Please help with narnext error Subscripted assignment dimension mismatch.????

x5=data_inputs(5,1:17); x6=data_inputs(6,1:17); x7=data_inputs(6,1:17); x8=data_inputs(7,1:17); x9=data_inputs(9,1:17); Hop...

2 months ago | 0

Answered

Hyperparameter tuning of neural network

One hidden layer is always sufficient. However, sometimes 1. Knowledge of the physical or mathematical process may lead to a ...

Hyperparameter tuning of neural network

One hidden layer is always sufficient. However, sometimes 1. Knowledge of the physical or mathematical process may lead to a ...

2 months ago | 1

Answered

Different results in training a CNN with Matlab 2018a and Matlab 2019a

You are making the task difficult by going backwards. Start with a single hidden node and add nodes one at a time. Hope this...

Different results in training a CNN with Matlab 2018a and Matlab 2019a

You are making the task difficult by going backwards. Start with a single hidden node and add nodes one at a time. Hope this...

2 months ago | 0

Question

NEURAL NETWORK DATA SET EXAMPLES

For demonstration of old AND new concepts and ideas, PLEASE use the sample NN data sets provided by MATLAB help nndatas...

2 months ago | 0 answers | 0

Answered

cross validation in neural network using K-fold

%i am using neural network for classification but i need to use instead of holdout option , K-fold. ==> FALSE!. You mean y...

cross validation in neural network using K-fold

%i am using neural network for classification but i need to use instead of holdout option , K-fold. ==> FALSE!. You mean y...

2 months ago | 0

Answered

Can the number of Predictors be different for Train and Test data?

Of course not. The ultimate purpose of training is to create a model that works well on non-training data. Thank you for form...

Can the number of Predictors be different for Train and Test data?

Of course not. The ultimate purpose of training is to create a model that works well on non-training data. Thank you for form...

2 months ago | 0

Answered

How to check the robustness of the Neural network model?

If you are going to test with white noise, include white noise in your design (i.e., training + validation) Then, given a fixed...

How to check the robustness of the Neural network model?

If you are going to test with white noise, include white noise in your design (i.e., training + validation) Then, given a fixed...

2 months ago | 0

| accepted

Answered

NARX with Complex Values Input

Decades ago I learned (the hard way) to forget about trying to use complex computations for NNs. However, if you insist, let us...

NARX with Complex Values Input

Decades ago I learned (the hard way) to forget about trying to use complex computations for NNs. However, if you insist, let us...

3 months ago | 1

Answered

Why sets Matlab automatically the activation functions for a neural network like this?

That is a standard configuation for a neural net. It's operation is explained in every elementary text. Thank you for formally...

Why sets Matlab automatically the activation functions for a neural network like this?

That is a standard configuation for a neural net. It's operation is explained in every elementary text. Thank you for formally...

3 months ago | 0

Answered

I get a "Performance function replaced with squared error performance" warning when trying to set 'crossentropy' as the performance function.

If you insist on using CROSSENTROPY, try PATTERNNET. Hope this helps. Thank you for formally accepting my answer Greg

I get a "Performance function replaced with squared error performance" warning when trying to set 'crossentropy' as the performance function.

If you insist on using CROSSENTROPY, try PATTERNNET. Hope this helps. Thank you for formally accepting my answer Greg

3 months ago | 0

Answered

How to plot Network performance?

You have lost training information, So the only thing left is output vs input. Hope this helps. Thank you for formally ac...

How to plot Network performance?

You have lost training information, So the only thing left is output vs input. Hope this helps. Thank you for formally ac...

3 months ago | 0

Answered

Elman Neural Network (ENN)

size(P_TRAIN) = [ 1296 1728] size(T_TRAIN) = [ 432 1728] Hope this helps. *Thank you for formally accepting my answer* ...

Elman Neural Network (ENN)

size(P_TRAIN) = [ 1296 1728] size(T_TRAIN) = [ 432 1728] Hope this helps. *Thank you for formally accepting my answer* ...

3 months ago | 0

Answered

NARX re-training in closed loop

Using 100 feedback delays makes no sense. Only use feedback delays that are within the correlation length of the function. See...

NARX re-training in closed loop

Using 100 feedback delays makes no sense. Only use feedback delays that are within the correlation length of the function. See...

4 months ago | 1

Answered

Can CNN train separately instead of learning everything at one time?

I try to have the order of inputs as random and uncorrelated as possible. Otherwise the probability of extensive learning/unlear...

Can CNN train separately instead of learning everything at one time?

I try to have the order of inputs as random and uncorrelated as possible. Otherwise the probability of extensive learning/unlear...

4 months ago | 0

Answered

In evaluating a neural net, should NMSE be based only on test subset of data?

For serious work I calulate FOUR values of NMSE: 1.70% Training 2.15% Validation 3.15% Test 4.100% All for 10 (typically...

In evaluating a neural net, should NMSE be based only on test subset of data?

For serious work I calulate FOUR values of NMSE: 1.70% Training 2.15% Validation 3.15% Test 4.100% All for 10 (typically...

4 months ago | 0

| accepted

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....

5 months ago | 0

| accepted

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...

5 months 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 ...

5 months 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

5 months 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...

6 months 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...

6 months 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 ...

6 months ago | 0

| accepted