hallo
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I'll be happy to receive your comments on the following questions:
What is leaning in neural networks ?
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For the follow chart :
|--------------| |--------------|
| presynaptic | |---------| | postsynaptic |
| |------->| synapse |-------------->| |
| cell | |---------| | cell |
|--------------| g(t)=A*t*exp(-t/tau) |--------------|
action potential action potential
at frequency f1 at frequency f2
- Does a general learning means that the synaptic weight (A) changes ?
- Does leaning mean also changing the synaptic time constant ?
- Does f2 is a function of f1 and the synaptic parameters (A , tau) ?
- What is the relation (magnitude) between f1 and f2 to the
synaptic time constant ?
- To me as Electrical and Computer Engineering it seems the most
natural way to model synaptic connection as a convolution between
the presynaptic voltage and the synaptic conductance in order to
receive the postsynaptic current, but the usual model is
i_synapse=g(t)*[v(t)-v_synapse] ?
Any comments and references will be helpful.
Sincerely yours
Pinchas Tandeitnik.
Department of Electrical and Computer Engineering,
Ben-Gurion University of the Negev,
P.O.Box 653, Beer-Sheva 84105, ISRAEL.
email: pini at bguee.bgu.ac.il
