Editing Artificial neuron (section)

==Pseudocode algorithm==
The following is a simple [[pseudocode]] implementation{{Citation needed|date=September 2024}} of a single Threshold Logic Unit (TLU) which takes [[Boolean data type|Boolean]] inputs (true or false), and returns a single Boolean output when activated. An [[object oriented|object-oriented]] model is used. No method of training is defined, since several exist. If a purely functional model were used, the class TLU below would be replaced with a function TLU with input parameters threshold, weights, and inputs that returned a Boolean value.

 '''class''' TLU '''defined as:'''
     '''data member''' threshold ''':''' number
     '''data member''' weights ''': list of''' numbers '''of size''' X
 
     '''function member''' fire(inputs ''': list of''' booleans '''of size''' X) ''':''' boolean '''defined as:'''
         '''variable''' T ''':''' number
         T '''←''' 0
         '''for each''' i '''in''' 1 '''to''' X '''do'''
             '''if''' inputs(i) '''is''' true '''then'''
                 T '''←''' T + weights(i)
             '''end if'''
         '''end for each'''
         '''if''' T > threshold '''then'''
             '''return''' true
         '''else:'''
             '''return''' false
         '''end if'''
     '''end function'''
 '''end class'''