Computationally efficient algorithms for cyclic spectral analysis
Richard S. Roberts, W. A. Brown, H.H. Loomis · IEEE Signal Processing Magazine · 1991
Two computationally efficient algorithms for digital cyclic spectral analysis, the FFT accumulation method (FAM) and the strip spectral correlation algorithm (SSCA), are developed from a series of modifications on a simple time smoothing algorithm. The signal processing, computational, and structural attributes of time smoothing algorithms are presented with emphasis on the FAM and SSCA. As a vehicle for examining the algorithms the problem of estimating the cyclic cross spectrum of two complex-valued sequences is considered. Simplifications of the resulting expressions to special cases of the cross cyclic spectrum of two complex-valued sequences, such as the cyclic spectrum of a single real-valued sequence, are easily found. Computational and structural simplifications arising from the specialization are described.>