Neuro

#Funcoes de ativacao representada por φ(υ)

##Funcao de limiar ou delta de dirac
φ₁(υ) = υ >= 0 ? 1 : 0
#Funcao linar por partes
φ₂(υ) = υ ≥ 0.5 ? 1 : (υ ≤ -0.5 ? 0 : υ)
#Funcao logistica onde α e o parametro de inclinacao da funcao sigmoide
φ₃(υ, α) = 1./(1 + exp(-α*υ))

gact(x) = x.*(1-x)

function test(iter)
  𝘅 = [0 0 1; 1 1 1; 1 0 1; 0 1 1]
  𝘅ᵀ = transpose(𝘅)
  test = [0, 1, 1, 0]
  weights = 2rand(3, 1) - 1
  for i in 1:iter
    output = φ₃(𝘅 * weights, 1)
    error = test - output
    delta = error.*φ₃(output, 1)
    weights += 𝘅ᵀ * delta
  end
  println(φ₃(𝘅 * weights, 1))
end

test(10000)