Friday, 1 November 2024
Digital Logic and Computer Design Assignment - 3
Sunday, 29 September 2024
Pattern Recognition and Computer Vision - ASSIGNMENT 1
Pattern Recognition and Computer Vision - ASSIGNMENT 1
Date -- 30 September 2024
BATCH- ECE-AIML
SUBMISSION DATE - 14 October 2024
- Explain the difference between supervised and unsupervised learning in pattern recognition.
- What is the role of clustering in pattern recognition?
- Discuss the advantages and limitations of using Decision Trees for pattern recognition.
- Explain the concept of feature selection and its importance in pattern recognition.
- Analyze the performance of different clustering algorithms (e.g., K-means, Hierarchical) on a gene expression dataset.
- Prove that Naive Bayes classifiers are optimal when features are independent.
- Explain the concept of maximum-margin hyperplane in SVMs.
- Derive the SVM decision boundary equation.
- Describe the role of bias terms in Feed Forward Networks.
- Explain the difference between Fisher Discriminant Analysis and Principal Component Analysis.
- What is the role of regularization in polynomial curve fitting?
Thursday, 12 September 2024
Digital Logic and Computer Design - 2 (2025)
Digital Logic and Computer Design
Assignment - 2
SUBJECT CODE-- ECC 207
BATCH- IT 123SUBMISSION DATE - 20 September 2025
(a) ALU (b) PAL (c) PLA
7. Compare RAM and ROM along with their types.
8. Obtain the minimal expression using Quine- McCluskey method-
F(A,B,C,D) = Sigma m(1,5,6,12,13,14)+d(2,4)
Tuesday, 27 August 2024
DLCD Assignment-1 2025
ASSIGNMENT 1
SUBJECT CODE-- ECC 207
BATCH- IT-123SUBMISSION DATE - 27 AUGUST 2025
Q.1
Expand [A(A’+B)(A’+B+C’)] to maxterms and minterms .
Q.2
Find the reduced expression for the following using K-maps:
a)
F = A’B’+A’B+AB’
b)
F = A’B’+AB+A’B
c)
F = (A+B)(A+B’)(A’+B’)
d) F = A’B’C’+A’BC’+ABC’ +AB’C
e)
F = (A+B+C)(A’+B+C’)(A’+B’+C’)(A+B’+C’) (A’+B’+C)
f) F = AB’+AC’+ABC+AB’
g)
F(A,B,C) = ∑m(0,4,5,7)
h)
F(A,B,C) = ∑m(0,1,3,5,7)
i) F(A,B,C,D) = ∑m(0,1,2,3,5,7,8,9,10,12,13)
j)
F(A,B,C,D,E) = ∑m(0,2,3,10,11,12,13,16,17,18,19,20,21,26,27)
k)
F(A,BC,D) = ∑m(0,2,6,10,11,12,13) + d(3,4,5,14,15)
l) F(A,B,C,D) = ∑m(0,1,3,4,5,7,10,13,14,15)
m)
F(A,B,C,D) = ∑m(0,2,3,6,7,8,10,11,12,15)
n)
F(A,B,C,D) = ∑m(0,1,3,4,5,6,7,13,15)
o) F(A,B,C,D) = ∏M(6,7,8,9). d(10,11,12,13,14,15)
p)
F(A,B,C,D) = ∏M(1,5,6,7,11,12,13,15)
q)
F(A,BC,D) = ∑m(1,5,6,12,13,14) + d(2,4)
Sunday, 10 March 2024
DIGITAL IMAGE PROESSING - ASSIGNMENT 1
DIGITAL IMAGE PROESSING - ASSIGNMENT 1
Date -- 11 March 2024
BATCH- ECE-MLDA, AIML
SUBMISSION DATE - 20 March 2024
- Compute the Euclidean Distance (D1), City-block Distance (D2) and Chessboard distance (D3) for points p and q, where p and q be (5, 2) and (1, 5) respectively. Give answer in the form (D1, D2, D3).
- What do you mean by convolution? Explain all the properties of convolution.
- Describe the fundamental steps in image processing?
- Write the expression to find the number of bits to store a digital image? Find the number of bits required to store a 256 X 256 image with 32 gray levels.
- Explain CMY model.
- Write a note on Match Band Effect.
- Differentiate photopic and scotopic vision?
- Explain linear versus non linear operations.