ℓ1 Minimization

L¹ minimization is a mathematical technique used to find the simplest solution among many possibilities, especially when solving systems of equations with limited or noisy data. It works by selecting the solution with the smallest sum of absolute values of its components, promoting sparsity—meaning many entries become zero. This approach is particularly useful in fields like signal processing and machine learning for recovering signals or images from incomplete information, because it encourages solutions that are concise and efficient, capturing the essential features without unnecessary complexity.