use LinearAlgebra.normalize!(vector, 1) to adjust weight after weight merge

This commit is contained in:
2023-05-16 21:01:11 +07:00
parent 70d2521c5e
commit 0ac5a703ea
2 changed files with 12 additions and 7 deletions

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@@ -34,13 +34,8 @@ using .interface
"""
Todo:
[*6] time-based learning method based on new error formula
(use output vt compared to vth instead of late time)
if output neuron not activate when it should, use output neuron's
(vth - vt)*100/vth as error
if output neuron activates when it should NOT, use output neuron's
(vt*100)/vth as error
[7] use LinearAlgebra.normalize!(vector, 1) to adjust weight after weight merge
[9] verify that model can complete learning cycle with no error
[*5] synaptic connection strength concept. use sigmoid, turn connection offline
[8] neuroplasticity() i.e. change connection
@@ -56,6 +51,13 @@ using .interface
"inference"
[DONE] output neuron connect to random multiple compute neurons and overall have
the same structure as lif
[DONE] time-based learning method based on new error formula
(use output vt compared to vth instead of late time)
if output neuron not activate when it should, use output neuron's
(vth - vt)*100/vth as error
if output neuron activates when it should NOT, use output neuron's
(vt*100)/vth as error
[DONE] use LinearAlgebra.normalize!(vector, 1) to adjust weight after weight merge
Change from version: v06_36a
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