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update version

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tonaerospace
2023-05-31 00:19:30 +07:00
parent ddb58d2fbd
commit 08297ccd00
4 changed files with 58 additions and 43 deletions
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14
src/types.jl
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@@ -346,7 +346,7 @@ Base.@kwdef mutable struct lifNeuron <: computeNeuron
delta::Float64 = 1.0 # δ, discreate timestep size in millisecond
refractoryDuration::Int64 = 3 # neuron's refratory period in millisecond
refractoryCounter::Int64 = 0
tau_m::Float64 = 50.0 # τ_m, membrane time constant in millisecond
tau_m::Float64 = 100.0 # τ_m, membrane time constant in millisecond
eta::Float64 = 0.01 # η, learning rate
wRecChange::Array{Float64} = Float64[] # Δw_rec, cumulated wRec change
recSignal::Float64 = 0.0 # incoming recurrent signal
@@ -440,7 +440,7 @@ Base.@kwdef mutable struct alifNeuron <: computeNeuron
phi::Float64 = 0.0 # ϕ, psuedo derivative
refractoryDuration::Int64 = 3 # neuron's refractory period in millisecond
refractoryCounter::Int64 = 0
tau_m::Float64 = 50.0 # τ_m, membrane time constant in millisecond
tau_m::Float64 = 100.0 # τ_m, membrane time constant in millisecond
wRecChange::Array{Float64} = Float64[] # Δw_rec, cumulated wRec change
recSignal::Float64 = 0.0 # incoming recurrent signal
alpha_v_t::Float64 = 0.0 # alpha * v_t
@@ -453,7 +453,7 @@ Base.@kwdef mutable struct alifNeuron <: computeNeuron
firingRateError::Float64 = 0.0 # local neuron error w.r.t. firing regularization
firingRate::Float64 = 0.0 # running average of firing rate, Hz
tau_a::Float64 = 50.0 # τ_a, adaption time constant in millisecond
tau_a::Float64 = 100.0 # τ_a, adaption time constant in millisecond
beta::Float64 = 0.15 # β, constant, value from paper
rho::Float64 = 0.0 # ρ, threshold adaptation decay factor
a::Float64 = 0.0 # threshold adaptation
@@ -544,7 +544,7 @@ Base.@kwdef mutable struct linearNeuron <: outputNeuron
delta::Float64 = 1.0 # δ, discreate timestep size in millisecond
refractoryDuration::Int64 = 3 # neuron's refratory period in millisecond
refractoryCounter::Int64 = 0
tau_out::Float64 = 25.0 # τ_out, membrane time constant in millisecond
tau_out::Float64 = 50.0 # τ_out, membrane time constant in millisecond
eta::Float64 = 0.01 # η, learning rate
wRecChange::Array{Float64} = Float64[] # Δw_rec, cumulated wRec change
recSignal::Float64 = 0.0 # incoming recurrent signal
@@ -637,7 +637,7 @@ function init_neuron!(id::Int64, n::lifNeuron, n_params::Dict, kfnParams::Dict)
n.synapticStrength = rand(-5:0.01:-4, length(n.subscriptionList))
n.epsilonRec = zeros(length(n.subscriptionList))
n.wRec = rand(-0.2:0.01:0.2, length(n.subscriptionList))
n.wRec = randn(length(n.subscriptionList))
n.wRecChange = zeros(length(n.subscriptionList))
n.alpha = calculate_α(n)
n.z_i_t_commulative = zeros(length(n.subscriptionList))
@@ -657,7 +657,7 @@ function init_neuron!(id::Int64, n::alifNeuron, n_params::Dict,
n.synapticStrength = rand(-5:0.01:-4, length(n.subscriptionList))
n.epsilonRec = zeros(length(n.subscriptionList))
n.wRec = rand(-0.2:0.01:0.2, length(n.subscriptionList))
n.wRec = randn(length(n.subscriptionList))
n.wRecChange = zeros(length(n.subscriptionList))
# the more time has passed from the last time neuron was activated, the more
@@ -680,7 +680,7 @@ function init_neuron!(id::Int64, n::linearNeuron, n_params::Dict, kfnParams::Dic
n.synapticStrength = rand(-5:0.01:-4, length(n.subscriptionList))
n.epsilonRec = zeros(length(n.subscriptionList))
n.wRec = rand(-0.2:0.01:0.2, length(n.subscriptionList))
n.wRec = randn(length(n.subscriptionList))
n.wRecChange = zeros(length(n.subscriptionList))
n.alpha = calculate_k(n)
n.z_i_t_commulative = zeros(length(n.subscriptionList))