Artificial Neural Network

Each processing element in an artificial neural net is analogous to a biological neuron

  • – An element accepts a certain number of input values (dendrites) and produces a single output value (axon) of either 0 or 1
  • – Associated with each input value is a numeric weight (synapse)
  • – The effective weight of the element is the sum of the weights multiplied by their respective input values v1 * w1 + v2 * w2 + v3 * w3
  • – Each element has a numeric threshold value
  • – If the effective weight exceeds the threshold, the unit produces an output value of 1
  • – If it does not exceed the threshold, it produces an output value of 0
  • – The process of adjusting the weights and threshold values in a neural net is called training
  • – A neural net can presumably be trained to produce whatever results are required
  • – But think about the complexity of this! Train a computer to recognize any cat in a picture, based on training run with several pictures.

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