16 Jan
2020
16 Jan
'20
11:13 a.m.
Hi!
There is no way to get 100 spike generators without creating them
individually. But as they are pretty efficient with respect to memory
and performance, I also don't see a problem with that.
Other than that, the description of what you want to achieve is far too
vague to give you more detailed advice. Please consider sending a figure
of your planned network topology and/or (pseudo) code that shows what
you want to do. Also have a look at the example networks for NEST, as
those contain a lot of useful design patterns for all kinds of
simulation scenarios:
https://nest-simulator.readthedocs.io/en/latest/examples/index.html
Cheers,
Jochen!
On 07.01.20 16:46, shanka19(a)purdue.edu wrote:
Hello everyone,
Happy New Year! I want to create a simple neural network consisting of a single neuron
connected by multiple inputs (spike generators). I am aware that I can create single spike
generators and then connect them but it becomes infeasible as the size of input grows. Is
there a way to create a network of maybe 100 spike generators connected to a single LIF
Neuron without explicitly creating 100 of them? Once the connections are made is there a
way that the network is updated when the weights are updated. I want the network to get
updated as I update the weights. Now, I update the weights and reset the network to create
it again with new weights. Any help would be appreciated. Thanks in advance!
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--
Dr. Jochen Martin Eppler
Phone: +49(2461)61-96653
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Simulation Laboratory Neuroscience
Jülich Supercomputing Centre
Institute for Advanced Simulation
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