<p><a href="https://arxiv.org/pdf/1410.1141.pdf" rel="nofollow noreferrer">Here</a> is a paper with the mathematical definition of each term:</p>

<blockquote>
  <p>Let N<sub>t,n,σ,L</sub> be all target functions that can be implemented using a
  neural network of depth t, size n, activation function σ, and when we
  restrict the input weights of each neuron to be |w|<sub>1</sub> + |b| ≤ L.</p>
</blockquote>

CC BY-SA 4.0
2019-11-13T09:08:20.203Z
Does "size $n$" mean that the network has $n$ input nodes?
J. Doe
CC BY-SA 4.0
2019-11-13T09:13:08.057Z
Check the introduction: "The depth of the network is the number of layers and the size of the network is the total number of neurons."
serali
CC BY-SA 4.0
2019-11-13T08:34:51.033Z
2019-11-13T08:34:51.033Z
serali
<p>A neural network can apparently be denoted as <span class="math-container">$N_{t,n,\sigma,L}$</span>. What do these subscripts  <span class="math-container">$t, n, \sigma$</span> and <span class="math-container">$L$</span> mean? Could you link me to a paper, article or webpage with an explanation for this? </p>

<neural-networks><math><definitions><notation>
What do the subscripts mean in $N_{t,n,\sigma,L}$?
J. Doe
# What do the subscripts mean in $N_{t,n,\sigma,L}$?

(Asked by: username_0 on 2019-11-13)

A neural network can apparently be denoted as $N\_{t,n,\sigma,L}$. What do these subscripts $t, n, \sigma$ and $L$ mean? Could you link me to a paper, article or webpage with an explanation for this?

**Tags:** neural-networks, math, definitions, notation


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## 1 answers

### Answer by username_1 on 2019-11-13. Score: 4 | Accepted answer

[Here](https://arxiv.org/pdf/1410.1141.pdf) is a paper with the mathematical definition of each term:

> Let Nt,n,σ,L be all target functions that can be implemented using a
> neural network of depth t, size n, activation function σ, and when we
> restrict the input weights of each neuron to be |w|1 + |b| ≤ L.

> **Comments:**
> **username_0**: Does "size $n$" mean that the network has $n$ input nodes?  
> **username_1**: Check the introduction: "The depth of the network is the number of layers and the size of the network is the total number of neurons."  

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