A Glimpse and Contrast on Different Models of Artificial Neuron

Amritpal Kaur

Abstract


Artificial neuron network (ANN) is non linear mapping structures based on the function of human intelligence. They are powerful tools for modeling especially when the underlying data relationship is known.ANN can identify and discover correlated patterns between input data sets and corresponding target value. After training, they can be used to predict the outcome of new self-regulating input data. There are different models of artificial neural networks-The McCulloch-Pitts Model of Neuron, the ADALINE Model and Perceptron Model which are discussed in this paper.


Keywords


ANN, Adaline, Mc-Culloch pitts, Perceptron.

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References


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