<p>I have been searching for more than one week which learning methods were used in Neurogrid.</p>

<p>But I only found descriptions of its architecture (chips, circuits, analog and/or digital components, performance results), everything but no clue on how it updates the weights. </p>

<p>In my opinion, I think that it cannot be gradient descent (with back-propagation), as the topology of the neurons in a chip, for example in the neurocore of Neurogrid, is a mesh or grid. </p>

<p>Do you know where I could find this kind of information?</p>

<p><a href="https://i.sstatic.net/TdpST.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/TdpST.png" alt="One neurocore of Neurogrid"></a></p>

CC BY-SA 4.0
2019-06-27T18:10:21.650Z
Hey thanks a lot for answering, could you please give me these names or articles ? I looked for those for hours and hours without any result.
lolodino77
<machine-learning><neuromorphic-engineering>
Where could I find information on the learning methods used in Neurogrid?
lolodino77
# Where could I find information on the learning methods used in Neurogrid?

(Asked by: username_0 on 2019-06-27)

I have been searching for more than one week which learning methods were used in Neurogrid.

But I only found descriptions of its architecture (chips, circuits, analog and/or digital components, performance results), everything but no clue on how it updates the weights.

In my opinion, I think that it cannot be gradient descent (with back-propagation), as the topology of the neurons in a chip, for example in the neurocore of Neurogrid, is a mesh or grid.

Do you know where I could find this kind of information?

[![One neurocore of Neurogrid](https://i.sstatic.net/TdpST.png)](https://i.sstatic.net/TdpST.png)

**Tags:** machine-learning, neuromorphic-engineering

> **Comments:**
> **username_0**: Hey thanks a lot for answering, could you please give me these names or articles ? I looked for those for hours and hours without any result.  

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## 0 answers

