State and explain any 3 signal functions in neural networks
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it is a computational nonlinear model based on the neural structure of the brain that is able to learn to perform tasks like classification, prediction, decision-making, visualization, and others just by considering examples.
The input layer contains input neurons that send information to the hidden layer. The hidden layer sends data to the output layer. Every neuron has weighted inputs (synapses), an activation function(defines the output given an input), and one output. Synapses are the adjustable parameters that convert a neural network to a parameterized system.
The input layer contains input neurons that send information to the hidden layer. The hidden layer sends data to the output layer. Every neuron has weighted inputs (synapses), an activation function(defines the output given an input), and one output. Synapses are the adjustable parameters that convert a neural network to a parameterized system.
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