DLCD Assignment 3 year (2025)

 

Digital Logic and Computer Design

Assignment - 3

SUBJECT CODE-- ECC 207

BATCH- IT 123

SUBMISSION DATE - 7 November 2025

1 Explain cache with set associative and direct mapping. Assume your own example and explain.

2 Explain types of interrupts with an example for each. Explain interrupt cycle with the help of flowchart.

3 Show internal configuration of DMA controller.

4 Explain Computer Organization with respect to computer configuration for micro program, symbolic program and binary microprogram.

5 What is an assembly language? Explain basic computer instruction formats.

6 Define DMA.  Explain its need. Explain DMA transfer in detail with the help of suitable example.

7 Differentiate between hardwired control and microprogram control and explain organization of microprogrammed control unit with neat diagram.

PRCV Assignment 3

                   Subject Name: Pattern Recognition and Computer Vision

Subject Code: ML-411T                 Semester: 7^th

 

Assignment No. 3

 Submission Date - 7 November 2025, Friday

Bloom’s Taxonomy Levels:  1. Remember  2. Understand  3. Apply  4. Analyze  5. Evaluate 6. Create

 

Q. No.	Question	BTL level	CO
1.	What are the two approaches for blind image restoration? Explain in detail.	1	3
2.	Which is the most frequent method to overcome the difficulty of formulating the spatial relocation of pixels?	1	3
3.	Explain additivity property in Linear Operator? A.      How is the degradation process modeled? B.     Explain homogeneity property in Linear Operator?	2	3
4.	Explain the inverse filtering with suitable examples.	1	3
5	Give the relation for degradation model for continuous function? a. Define circulant matrix? b. What is the concept of an algebraic approach?	2	3
6.	What is image degradation and restoration? Explain them with examples.	3	3
7.	Write the properties of Singular value Decomposition (SVD)?	4	3
8.	What are the three methods of estimating the degradation function?	1	3

PRCV Assignment 2

 

Subject Name: Pattern Recognition and Computer Vision

             

Subject Code: ML-411T                 Semester: 7^th

Assignment No. 2

Submission Date - 7 November 2025, Friday

Bloom’s Taxonomy Levels:  1. Remember  2. Understand  3. Apply  4. Analyze  5. Evaluate 6. Create

Q. No.	Question	BTL level	CO
1.	What do you mean by fuzzy decision making? Also discuss the fuzzy classification using suitable examples.	1	2
2.	What do you understand by supervised learning and unsupervised learning? Explain. Discuss any unsupervised learning algorithm with some examples.	2	1
3.	Briefly explain segmentation and grouping.	1	2
4.	Explain Gaussian Mixture Models. If for any two elements A<B given that P(A)=1/3, P(B)=1/5 and P(AUB)=11/30, then find: P(A/B).	1	1
5	Explain chi-square test.	1	1
6.	Explain evaluation of classifiers. Give probability distribution of a random variable.	3	2
7.	Explain why the maximum likelihood estimation is not working with uniformly distributed training sets.	2	2
8.	Show that in the likelihood the sample mean is equal to the mean of samples.	1	1