Unit 5 | DSTL Notes |Discrete Structure and Theory of Logic Notes | Aktu Notes


Unit 5 | DSTL Notes |Discrete Structure and Theory of Logic Notes | Aktu Notes

Unit 5 | DSTL Notes |Discrete Structure and Theory of Logic Notes | Aktu Notes

Graphs

- A collection of vertices (or nodes) and edges that connect pairs of vertices.

- Terminology:
  - Vertex: A point in the graph.
  - Edge: A line connecting two vertices.
  - Degree of a Vertex: The number of edges connected to a vertex.
  - Loop: An edge that connects a vertex to itself.
  - Path: A sequence of vertices connected by edges.
  - Cycle: A path that begins and ends at the same vertex.

Representation of Graphs

- Adjacency Matrix: A matrix where each cell indicates if an edge exists between vertex pairs.
- Adjacency List: A list where each vertex stores a list of adjacent vertices.

Multigraphs

- A graph that can have multiple edges between the same pair of vertices.
- Key Characteristics: Allows loops and multiple edges, used in complex network modeling.

Bipartite Graphs

- A graph whose vertices can be divided into two disjoint sets such that edges only connect vertices from different sets.
- Application: Common in matching problems, like job assignments.

Planar Graphs

- A graph that can be drawn on a plane without edges crossing.
- Euler’s Formula: For planar graphs, V - E + F = 2 where V is vertices, E is edges, and F is faces.

Isomorphism and Homeomorphism of Graphs

- Isomorphism: Two graphs are isomorphic if they have identical structure.

- Homeomorphism: Graphs are homeomorphic if they can be transformed into each other by adding or removing vertices of degree 2.

Euler and Hamiltonian Paths

- Euler Path: A path that visits every edge exactly once.
- Hamiltonian Path: A path that visits every vertex exactly once.

Graph Coloring

- Assigning colors to vertices so that no two adjacent vertices have the same color.
- Applications: Scheduling, register allocation in compilers.

Combinatorics

- The branch of mathematics dealing with counting, arrangement, and combination of objects.
- Applications: Used in computer science for algorithm analysis, probability, and optimization.

Counting Techniques

- Fundamental Principle of Counting: If one event has m outcomes and a second event has n outcomes, the total is m x n.
- Permutations: Arrangements of objects in a specific order.
  - Formula:  P ( n , r ) = n ! / ( n r ) !
- Combinations: Selection of objects without considering the order.
  - Formula:  n C r = n ! / r ! ( n r ) !

Pigeonhole Principle

- If  n items are put into m containers, and n > m , at least one container must contain more than one item.
- Applications: Used in problems involving repetition, such as ensuring duplicate items in subsets.

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