berito / cv_exercise_1

computer vision exercise 1

Octave Algorithm Implementations

This repository contains various algorithm implementations in Octave, focusing on fundamental concepts such as matrix operations, numerical methods, sorting algorithms, search algorithms, recursion, string manipulation, and probability and statistics.

Table of Contents

• Matrix Operations
• Numerical Methods
• Sorting Algorithms
• Search Algorithms
• Recursion
• String Manipulation
• Probability and Statistics
• Getting Started
• Usage
• Contributing
• License

Matrix Operations

• matrix_multiplication.m: Implements a function that multiplies two matrices using a basic algorithm (not relying on built-in functions).

Numerical Methods

• bisection_method.m: Implements a function that approximates the roots of a function using the bisection method.

Sorting Algorithms

• bubble_sort.m: Implements bubble sort.
• merge_sort.m: Implements merge sort.
• quicksort.m: Implements quicksort.

Search Algorithms

• binary_search.m: Implements a function that performs binary search on a sorted array.

Recursion

• factorial_recursive.m: Implements a function that computes factorial using recursion.

String Manipulation

• is_palindrome.m: Implements a function that checks if a given string is a palindrome.

Probability and Statistics

• statistics.m: Implements functions to calculate the mean, median, and mode of a given dataset.

Getting Started

Prerequisites

Ensure you have Octave installed on your system. You can download and install Octave from GNU Octave.

Installation

Clone the repository to your local machine using the following command:

git clone https://github.com/berito/cv_exercise_1.git
cd cv_lab_exercise_1
octave main.m