Match the columns.

Match List - I with List – II.

List - I	List - II
A.	The activation function	I.	is called the delta rule.
B.	The learning method of perceptron	II.	is one of the key components of the perceptron as in the most common neural network architecture.
C.	Areas of application of artificial neural network include	III.	is always boolean like a switch.
D.	The output of the perceptron	IV.	system identification and control.

Choose the correct answer from the options given below:

Correct option is C

Activation Function: Introduces non-linearity, often binary (boolean) in early perceptrons.
Delta Rule: A learning rule used in updating weights in neural networks.
Applications: Includes control systems, pattern recognition, etc.
Perceptron Output: Key in determining the perceptron's decision-making capability.
Information Booster:
1. Perceptron: The simplest form of a neural network used in linear binary classification.
2. Delta Rule: Used in gradient descent to minimize error.
Additional Knowledge:
· Modern Activations: Include ReLU, softmax for more complex tasks.
· Perceptron Limitations: Limited to linearly separable problems.