- For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solution
2006/03/23 by David L. Donoho · 4 citations
Computer Science · Engineering · Mathematics · #Algorithm #Applied mathematics #Banach space #Coefficient matrix #Combinatorics #Compressed sensing #Discrete mathematics #Eigenvalues and eigenvectors #Mathematics #Matrix Theory and Algorithms #Norm (philosophy) #Random Matrices and Applications #Random matrix #Sparse and Compressive Sensing Techniques #Statistics #Underdetermined system #Wishart distribution
- The generalised inverse
1978/06/01 by Menila James · 1 citation
Computer Science · Mathematics · Chemistry · #Matrix Theory and Algorithms #Inverse #Matrix (chemical analysis) #Mathematics #Coefficient matrix #Constant (computer programming) #System of linear equations #Pure mathematics #Applied mathematics #Mathematical analysis #Physics #Computer science #Geometry #Chemistry #Eigenvalues and eigenvectors #Chromatography
- The matrix sign function and computations in systems
1976/01/01 by Eugene D. Denman, Alex N. Beavers · 4 citations
Computer Science · Mathematics · #Algebraic Riccati equation #Algebraic equation #Applied mathematics #Coefficient matrix #Differential equation #Eigendecomposition of a matrix #Eigenvalues and eigenvectors #Function (biology) #Generalized eigenvector #Lyapunov equation #Lyapunov function #Mathematical analysis #Mathematics #Matrix (chemical analysis) #Matrix Theory and Algorithms #Matrix decomposition #Matrix differential equation #Matrix function #Nonnegative matrix #Numerical methods for differential equations #Riccati equation #Sign (mathematics) #Sign function #Square matrix #State-transition matrix #Symmetric matrix