AI & Signal Processing (EC-802 (A)) - Important Questions

Define Artificial Intelligence and describe its real-world applications.

Differentiate between Artificial Intelligence, Machine Learning, and Deep Learning.

Define knowledge in AI and explain its importance.

Describe the key components, advantages, and limitations of knowledge-based systems.

Explain forward chaining and backward chaining in expert systems, with examples and advantages and disadvantages.

Explain the different types of Machine Learning (supervised, unsupervised, and reinforcement learning) and their differences, including the relation of Machine Learning to Artificial Intelligence.

What are the challenges in generalization and overfitting?

What is a decision tree, how does it support learning, and how does the ID3 algorithm construct decision trees?

What is overfitting in decision trees and how can it be prevented?

Explain inductive learning in detail with a suitable example. Discuss its role in learning from observations.

Compute the eight-point DFT circular convolution for the following sequences. x2(n) = sin 3 pi n / 8

What is the difference between upsampling and downsampling?

What are the challenges in changing the sampling rate of a signal?

Explain what polyphase decomposition is, how it works, and how FIR filters are used in it.