8.b] Define Activation Function. Explain different types of activation functions.
Answer:
Activation Function:
Activation functions are mathematical functions associated with each neuron in the neural network that map input signals to output signals. It decides whether to fire a neuron or not based on the input signals the neuron receives. These functions normalize the output value of each neuron either between 0 and 1 or between -1 and +1. Typical activation functions can be linear or non-linear.
Linear functions are useful when the input values can be classified into any one of the two groups and are generally used in binary perceptrons. Non-linear functions, on the other hand, are continuous functions that map the input in the range of (O, I) or (—1, I), etc. These functions are useful in learning high-dimensional data or complex data such as audio, video and images.
Different types of activation functions:
