Matrix decomposition

Matrix decomposition is a mathematical process that breaks down a complex matrix into simpler, more manageable parts, called matrices, which when combined, recreate the original. Think of it like dissecting a big puzzle into smaller pieces that are easier to analyze or manipulate. This technique is useful for solving systems of equations, optimizing data, or understanding structures in fields like engineering or computer science. Common types include LU, QR, and Singular Value Decomposition (SVD), each serving specific purposes in simplifying calculations and revealing underlying patterns within the data.