Lectures related to Algorithmic Complexity: Travel Time Analysis

Covers proofs of Big-O using witnesses and rules to analyze algorithm complexity.

Explains Big-O notation for algorithm complexity analysis through polynomial examples and growth rate identification.

Analyzes the growth of functions to understand algorithm complexity and efficiency.

Explains the merge sort algorithm, its correctness, and time complexity compared to other sorting algorithms.