<p>In deep learning, most of the applications are from text and images. Both text and images can be converted into a tensor of real numbers.</p>
<p>Other than both mentioned above, there may be some other real-world data used by Deep learning algorithms. Any algorithm in general takes tensor as input and gives tensor as output. As far as I know, tensors always consist of real numbers.</p>
<p>I want to know whether there are any practical applications that deal with the tensors containing non-real numbers. <em>Is there any such possibility</em>?</p>

CC BY-SA 4.0
2021-11-19T16:30:54.097Z
What about a Fourier transform of a time series?
Dave
CC BY-SA 4.0
2021-11-29T03:36:41.897Z
@Dave I will check once.
hanugm
<deep-learning><datasets><applications><tensor>
Do any practical deep learning algorithms deal with tensors containing non-real entries?
hanugm
# Do any practical deep learning algorithms deal with tensors containing non-real entries?

(Asked by: username_0 on 2021-11-19)

In deep learning, most of the applications are from text and images. Both text and images can be converted into a tensor of real numbers.

Other than both mentioned above, there may be some other real-world data used by Deep learning algorithms. Any algorithm in general takes tensor as input and gives tensor as output. As far as I know, tensors always consist of real numbers.

I want to know whether there are any practical applications that deal with the tensors containing non-real numbers. *Is there any such possibility*?

**Tags:** deep-learning, datasets, applications, tensor

> **Comments:**
> **username_1**: What about a Fourier transform of a time series?  
> **username_0**: @username_1 I will check once.  

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## 0 answers

