<p>I'm a graduate student in the Electrical Engineering Program currently working on my thesis and I have to figure out how to train synaptic weights in an Artificial Neural Network either analogously or digitally.</p>

<p>Can anyone suggest some base papers that I can read to get started on this and how I can proceed. Would really appreciate it. Thanks!</p>

CC BY-SA 4.0
2018-07-09T21:46:42.413Z
I don't think this question is really on-topic for psych & neuroscience (but others may disagree with me) - Cross Validated might be better but they will probably prefer a more specific question rather than a broad reference request. I'd start by reading papers in your field that use ANNs and read the papers they cite for their methods.
Bryan Krause
CC BY-SA 4.0
2018-07-10T01:07:02.693Z
I don't know if this will help, but it is where I've started in the past: See Andrew Ng's *Machine Learning* https://www.youtube.com/watch?v=qeHZOdmJvFU&list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW To get familiar with the algorithms for training machine learning see the Python package Scikit-Learn: http://scikit-learn.org/stable/index.html These are general resources and you may be well beyond this already.
Frank Hubeny
CC BY-SA 4.0
2018-07-10T08:53:03.723Z
@BryanKrause would Bioinformatics be an alternative?
AliceD
CC BY-SA 4.0
2018-07-10T14:01:43.627Z
No bioinformatics would not.
Bryan Krause
CC BY-SA 4.0
2018-07-12T01:03:50.270Z
What do you mean by "analogously or digitally"? Like, analogue neuromorphic hardware?
Seanny123
<neural-network>
Training adjustments of synaptic Weights
Adi
# Training adjustments of synaptic Weights

(Asked by: username_0 on 2018-07-09)

I'm a graduate student in the Electrical Engineering Program currently working on my thesis and I have to figure out how to train synaptic weights in an Artificial Neural Network either analogously or digitally.

Can anyone suggest some base papers that I can read to get started on this and how I can proceed. Would really appreciate it. Thanks!

**Tags:** neural-network

> **Comments:**
> **username_1**: I don't think this question is really on-topic for psych & neuroscience (but others may disagree with me) - Cross Validated might be better but they will probably prefer a more specific question rather than a broad reference request. I'd start by reading papers in your field that use ANNs and read the papers they cite for their methods.  
> **username_2**: I don't know if this will help, but it is where I've started in the past: See Andrew Ng's *Machine Learning* https://www.youtube.com/watch?v=qeHZOdmJvFU&list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW To get familiar with the algorithms for training machine learning see the Python package Scikit-Learn: http://scikit-learn.org/stable/index.html These are general resources and you may be well beyond this already.  
> **username_3**: @BryanKrause would Bioinformatics be an alternative?  
> **username_1**: No bioinformatics would not.  
> **username_4**: What do you mean by "analogously or digitally"? Like, analogue neuromorphic hardware?  

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