Artificial Neuron Learning Technique in Soft Computing: A Review
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Abstract
This paper is based upon the learning of artificial
neurons with respect to supervised and unsupervised
learning algorithms. To maintain the strength of neurons,
we must update the weights such that neurons can reach up
to threshold value for spiking. Neural Network can update
by examples given to the system. There are three types of
learning:- Supervised Learning, Unsupervised Learning
and Reinforcement Learning. All the learning methods
having a neural network pattern differ in solving the inputs
according to the application.
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