Spectral decomposition is a method in linear algebra that expresses a matrix in terms of its eigenvalues and eigenvectors. This concept allows for the analysis of the properties of matrices, particularly in relation to diagonalization, where a matrix can be represented as a product of its eigenvectors and a diagonal matrix of its eigenvalues. Spectral decomposition is crucial in understanding the structure of matrices, especially symmetric or Hermitian matrices, as it reveals insights into their behavior and applications in various fields.
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