Korenberg's "fast Orthogonal Search" Method
Michael Korenberg of Queens University in Kingston, Ontario, developed a method for choosing a sparse set of components from an over-complete set, such as sinusoidal components for spectral analysis, called fast orthogonal search (FOS). Mathematically, FOS uses a slightly modified Cholesky decomposition in a mean-square error reduction (MSER) process, implemented as a sparse matrix inversion. As with the other LSSA methods, FOS avoids the major shortcoming of discrete Fourier analysis, and can achieve highly accurate identifications of embedded periodicities and excels with unequally-spaced data; the fast orthogonal search method has also been applied to other problems such as nonlinear system identification.
Read more about this topic: Least-squares Spectral Analysis
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