In linear algebra, a **defective matrix** is a square matrix that does not have a complete basis of eigenvectors, and is therefore not diagonalizable. In particular, an *n* × *n* matrix is defective if and only if it does not have *n* linearly independent eigenvectors. A complete basis is formed by augmenting the eigenvectors with generalized eigenvectors, which are necessary for solving defective systems of ordinary differential equations and other problems.

A defective matrix always has fewer than *n* distinct eigenvalues, since distinct eigenvalues always have linearly independent eigenvectors. In particular, a defective matrix has one or more eigenvalues λ with algebraic multiplicity (that is, they are multiple roots of the characteristic polynomial), but fewer than *m* linearly independent eigenvectors associated with λ. However, every eigenvalue with multiplicity *m* always has *m* linearly independent generalized eigenvectors.

A Hermitian matrix (or the special case of a real symmetric matrix) or a unitary matrix is never defective; more generally, a normal matrix (which includes Hermitian and unitary as special cases) is never defective.

Read more about Defective Matrix: Jordan Block, Example

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