Properties Of Asymptotic Notations
Asymptotic Notations
Algorithmic Complexity
Big-O Notation
Big-Theta Notation
Big-Omega Notation
Small O
Small w
Analyzing Algorithm Efficiency
Time Complexity in Algorithms
Space Complexity in Algorithms
Algorithm Analysis
Complexity Classes
Asymptotic Notations Explained
Efficient Algorithms
Best Practices in Algorithm Design
Comparing Algorithmic Efficiency
Mastering Big-O
Algorithm Performance Metrics
Computer Science Notations
Understanding Asymptotic Growth
Algorithmic Analysis Techniques
Practical Applications of Asymptotic Notations
Recurrence relations
methods of solving recurrence relations
solving recurrence relations
methods of recurrence relations
substituition method
master theorem
recurrence tree method
Breif Review Of graphs
graphs
Sets and disjoint sets
union
find
collapsed find
weighted union
#ipu #mait #asymptotic #asymptotes #asymptote #asymptoticnotations
Design and Analysis Of Algorithms (DAA)
All units Covered
Unit 1, Unit 2, Unit 3, Unit 4
Best suitable for IPU Students and IPU Syllabus
GGSIPU
MAIT
MSIT
BVCOE
BPIT
GNIOT
GTBIT
ADGITM
HMRITM
SAITM
...
TOPICS COVERED
UNIT‐I
Asymptotic notations for time and space complexity, Methods for solving Recurrence relations, Brief Review of Graphs, Sets and disjoint sets, union, sorting and searching algorithms and their analysis in terms of space and time complexity.
Divide and Conquer: General method, binary search, merge sort, Quick sort, selection sort, Strassen’s matrix multiplication algorithms and analysis of algorithms for these problems.
UNIT‐II
Greedy Method: General method, knapsack problem, Huffman Codes, job sequencing with deadlines, minimum spanning trees, single souce paths and analysis of these problems.
Back Tracking: General method, 8 queen’s problem, graph colouring, Hamiltonian cycles, and analysis of these problems.
UNIT‐III
Dynamic Programming: Ingredients of Dynamic Programming. Matrix Chain Multiplication, Longest common subsequence and optimal binary search trees problems, 0‐1 knapsack problem, Traveling salesperson problem, Floyd Warshall algorithm.
Branch and Bound: Method, O/I knapsack and traveling salesperson problem
UNIT ‐ IV
String Matching: The naïve String Matching algorithm, The Rabin‐Karp Algorithm, String Matching with finite automata, The Knuth‐Morris Pratt algorithm.
Computational Complexity: Basic Concepts, Polynomial vs Non‐Polynomial Complexity, NP‐ hard & NP‐ complete classes. Approximation Algorithms
Flow and Sorting Network: Ford‐ Fulkerson method, Maximum bipartite matching, Sorting Networks, Comparison network, Zero‐ one principle, Bitonic sorting network, merging network
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