# Ben

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**Content Feed**

Trouble adding input signals in Neural ODE training

Hi, What data do you have for your input signal ? If you can write a function for , e.g. , then the @(t,x,p) odeModel(t,x,p,u)...

5 days ago | 0

How to prepare the training data for neural net with concatenationLayer, which accepts the combination of sequence inputs and normal inputs?

You are right that to use trainNetwork with a network that has multiple inputs you will need to use a datastore. There is docume...

6 days ago | 0

Potential data dimension mismatch in lstm layer with output mode as 'sequence'?

The LSTM and Fully Connected Layer use the same weights and biases for all of the sequence elements. The LSTM works by using it'...

6 days ago | 0

Predict function returns concatenation error for a two-input Deep Neural Network

The "Format" functionLayer is re-labelling the input as "CSSB", and the inputs are "CB", so it's going to make the batch dimensi...

6 days ago | 0

Why doesn't concatLayer in Deep Learning Toolbox concatenate the 'T' dimension?

You can create a layer that concatenates on the T dimension with functionLayer sequenceCatLayer = functionLayer(@(x,y) cat(3,x,...

8 days ago | 0

i need to utilize fully of my GPUs during network training!

To use more of the GPU resource per iteration you can increase the minibatch size. I'll note that the LSTM layer you are adding...

8 days ago | 0

add more options to gruLayer's GateActivationFunction

I would recommend implementing this extended GRU layer as a custom layer following this example: https://www.mathworks.com/help...

9 days ago | 0

Is it possible to apply upper and lower bounds to predictions in an LSTM?

I believe the default LSTM has outputs bounded in (-1,1) due to the activation functions used. In any case you can try using ac...

9 days ago | 0

Hi, how do I fix the error please? i would like to build model with both sequance and image input layers, thanks

Concatenation does not expand over dimensions, for example the following errors: x = rand(1,10); y = rand(1); cat(1,x,y) If ...

9 days ago | 0

Forecasting single variable time series data using LSTM

The XTrain, YTrain, XVal and YVal must all be cell arrays with size (Number of Observations) x 1, and where each entry XTrain{1}...

9 days ago | 0

How to create LSTM network of multiple dimension

It appears your data is in (Batch) x (Sequence) x (Features) format. For trainNetwork you need to represent you sequence data as...

9 days ago | 0

How to apply physics informed neural networks on Matlab toolbox?

I'm not sure if this answers your question but you can take the network from this example, defined in the "Define Deep Learning ...

2 months ago | 2

Data pre-processing function in ANN model

Are you using the Deep Learning Toolbox tools such as DAGNetwork, dlnetwork, trainNetwork and/or custom training loops? In that ...

4 months ago | 0

| accepted

can i implement lstm layer from scratch using matlab in sequence to sequence regression

Sure, I think the best way to do this would be with a custom layer, you can follow this example that implements a modified LSTM ...

4 months ago | 1

Unable to resolve the name 'helper.downloadSCNNLaneDetection'.

I believe you need to do the following 1. clone or download https://github.com/matlab-deep-learning/pretrained-spatial-CNN into...

4 months ago | 0

Problem while usinge UNET

The response size is the size of the target data. I see this error when trying to train a regression network and the network's o...

4 months ago | 0

How to resolve "Unable to determine if experiment is for classification or regression because setup function returned invalid outputs"?

I think the issue is that the 2nd returned output of BayesOptExperiment_setup2 needs to be the layer array or layerGraph object ...

4 months ago | 0

Generate Text with Deep Learning "Invalid training data. Labels must not contain undefined values" ERROR

There are a few issues to fix this: The call to Y = categorical(charactersShifted) needs to include a valueset that includes al...

4 months ago | 1

Training neural network to solve non-linear equation with multiple input

Hi Fahad, You are getting the unconnect layers error for the following reason. When you define fnc=@(x1,x2) (x1 + x2).^2 it is...

5 months ago | 0

Resampling a Data Array for LSTM Training

Hi Patrick, In principle I think you can use Signal Processing resample - however you may want to verify this resample behaves ...

7 months ago | 0

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Physics-informed NN for parameter identification

Hi Dawei, The PINN in that example is assuming the PDE has fixed coefficients. To follow the method of Raissi et al. you can co...

7 months ago | 0

how to Train Network on Image and Feature Data with more then one feature input?

The subtle issue here is that the feature data needs to read out of the datastore as a NumFeatures x 1 vector as documented here...

8 months ago | 1

| accepted

Deep Learning Datastores causing errors with size/length

I think the issue here is just wrangling the datastore-s to read out a BatchSize x 2 cell array, where each cell in the first co...

8 months ago | 0

| accepted

minibatchqueue without shuffling by default

I think you need to use IterationDimension=2 to read out [0, ..., 0.2] in one mini-batch: ads=arrayDatastore(linspace(0,2,1000)...

8 months ago | 0

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Why is the data missing when I use Deep Network Designer for training？Please heip.

I typically see this error when the data was on the GPU but that data has since been lost from the GPU. For example you can rep...

9 months ago | 0

An error when run Unet Model Deep learning

You should set the number of filters on the final convolution layer to match the number of pixel classes for your problem. Tt lo...

9 months ago | 0

| accepted

Is there a way to train a network giving inputs one by one in MATLAB?

One thing that is changing for sure is the parameters for the ADAM optimizer. For example if you look at adamupdate (doc page), ...

9 months ago | 1

| accepted

Error using trainNetwork (line 184) Invalid network. Caused by: Layer 4: The size of the pooling dimension of the padded input data must be larger than or equal to the pool si

The issue is that the 2nd layer convolution1dLayer(3,10) has no padding. Currently its input size is [3, 5723, ?] where 3 is n_f...

9 months ago | 0

| accepted

My simple numerical Deep Learning project will not train. Get "invalid training data" message.

I think the issue here is you need to permute the data to NumFeatures x BatchSize for featureInputLayer when working with trainN...

9 months ago | 0

Size of the input layer is different from the expected input size

You're trying to concatenate the output of "gru_2" with the output of "fc_4". However "gru_2" outputs sequence data, and "fc_4" ...

9 months ago | 1

| accepted