ITERATIVE FAST ORTHOGONAL SEARCH FOR MODELING BY A SUM OF EXPONENTIALS OR SINUSOIDS

Accurate sinusoidal series models of biological time-series data may b e obtained using a modeling algorithm known as fast orthogonal search (FOS). FOS does not require equally spaced data, and can resolve sinus oidal frequencies much more closely spaced than can a discrete Fourier transform. FOS has been less successful at obtaining accurate exponen tial series models. We here consider a modification of FOS in which it eration of the original procedure is used to further reduce the mean-s quared error (m.s.e.) between model and data, approaching a minimum in the m.s.e. Iteration of the FOS procedure greatly improves the accura cy of estimated exponential series models. The application of iterativ e FOS (IFOS) to exponential and sinusoidal series models is described. Finally, the use of FOS and IFOS procedures for finding a single mode l from the results of multiple experiments is described. (C) 1998 Biom edical Engineering Society.