Hi,
How can i concatinate 20 , 4D signals
I1 = rand(32,32,1,13) ;
I2 = rand(40,32,1,13) ;
...
I20 = rand(47,32,1,13) ;
Catq1=cat(4,I1,I2);
The above give me error? What can i do?

 Réponse acceptée

Ridwan Alam
Ridwan Alam le 12 Déc 2019
Modifié(e) : Ridwan Alam le 12 Déc 2019

0 votes

You want to concatenate on the dim which is not same for both, right?
Catq1 = cat(1,I1,I2);
% OR
Catq1 = [I1;I2];

4 commentaires

ARN
ARN le 13 Déc 2019
Modifié(e) : ARN le 13 Déc 2019
Can you tell me if i am on the right track? So i am extracting data from lets video and i get 3-D data (512 points, 4 channels, 320 timeseries) for 200+ cycles and likewise i am getting for next 20 files.
what i am trying to do is concatinate all the timeseries which will become 320*200*20 and each time-sample i have 520 points on all 4 channels.
ldm= length(data);
[Ns, Nch, Rs] = size(data(1).FL.TimeSignals);
a=zeros(ldm,Ns,Nch,Rs);
for i=1: ldm
a(i,:,:,:)=data(i).FL.TimeSignals, Ns, Nch, Rs;
end
I1=a(:,:,1,:);
a size will be (200, 512,4, 320 ). Now same procedure for all 20 videos and then concatinate it like you proposed?
Ridwan Alam
Ridwan Alam le 13 Déc 2019
well .. without looking at the 'data', it's a bit of a guess .. but looks fine to me, except a few questions. the rehsape() inside the loop is not really doing anything, right? because all data(i).FL.TimeSignals have size [Ns, Nch, Rs]. Now, what are you trying to do with this line: I1=a(:,:,1,:); this will make I1 of size [ldm,Ns,Rs].
ARN
ARN le 13 Déc 2019
No, reshape is not there.. i wrote it wrong. Thanks for the reply
Ridwan Alam
Ridwan Alam le 13 Déc 2019
Sure. Glad to help!

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Bartlomiej Mroczek
Bartlomiej Mroczek le 26 Mar 2023

0 votes

And how to provide the CNN: predict DL block to the ready machine.
1. I have data built in 4D format, my CNN machine only use this format for learning and prediction in matlab.
2. I have built a model in SIMULINK but there is a problem with entering data to the Predict block, error message:
Available formats are double non-complex matrix, a structure with or without time, or a structure with MATLAB timeseries as leaf nodes. All formats require the data to be finite (not Inf or NaN).
How to solve it?

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