How to get the function 'convolution1dLayer' ?

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I haev been working on the 1D CNN. But in matlab if i try to use the function 'convolution1dLayer'. Im getting a response as,
>> layer = convolution1dLayer(11,96)
Unrecognized function or variable 'convolution1dLayer'.
Did you mean:
>> layer = convolution2dLayer(11,96)
  5 Comments
Badavath Purnesh Singh
Badavath Purnesh Singh on 10 Nov 2021
Yes, I have installed the R2021b by uninstalling the previous version. Is there an any other way to change the MATLAB verison without unintalling the previous version ?
KSSV
KSSV on 10 Nov 2021
You can install in another path and use both the versions.

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Answers (2)

Nabil Ajali
Nabil Ajali on 25 Jan 2022
There are any solution?
  7 Comments
Steven Lord
Steven Lord on 27 Jan 2022
You said "I have the R2021b version upgraded" but the path you showed indicate you're using release R2021a: "C:\Program Files\MATLAB\R2021a". You must use release R2021b or later to be able to use convolution1dLayer.
Nabil Ajali
Nabil Ajali on 31 Jan 2022
Oh, Maybe I was wrong thinking that I updated. I will confirm this.
Thank you very much!

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yanqi liu
yanqi liu on 26 Jan 2022
yes,sir,may be use 2D to replace 1D,such as
imageInputLayer([1024 1 1])
ans =
ImageInputLayer with properties: Name: '' InputSize: [1024 1 1] Hyperparameters DataAugmentation: 'none' Normalization: 'zerocenter' NormalizationDimension: 'auto' Mean: []
convolution2dLayer([100 1],3,'Stride',1)
ans =
Convolution2DLayer with properties: Name: '' Hyperparameters FilterSize: [100 1] NumChannels: 'auto' NumFilters: 3 Stride: [1 1] DilationFactor: [1 1] PaddingMode: 'manual' PaddingSize: [0 0 0 0] PaddingValue: 0 Learnable Parameters Weights: [] Bias: [] Show all properties
  2 Comments
Nabil Ajali
Nabil Ajali on 26 Jan 2022
Thanks yanqui liu, the problem is my data.
I have 1D vectors and i want to make a CNN with a BiLSTM, so i must use de convolution1DLayer.
yanqi liu
yanqi liu on 27 Jan 2022
yes,sir,may be use sequenceInputLayer to get model,such as
layers = [ ...
sequenceInputLayer(numFeatures)
lstmLayer(100,'OutputMode','sequence')
dropoutLayer(0.3)
lstmLayer(50,'OutputMode','sequence')
dropoutLayer(0.2)
fullyConnectedLayer(numClasses)
softmaxLayer
classificationLayer];

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