Delay estimation by FFT
Markus Nentwig presents a practical FFT-based algorithm to estimate and correct integer and fractional sample delays between two signals, returning a scaled, aligned replica and delay estimate. The method combines coarse cross-correlation with a phase-slope linear regression on weighted spectra to achieve subsample timing accuracy. The article also discusses accuracy limits, phase-unwrapping pitfalls, and how to use the error-vector spectrum to reveal distortion in lab measurements.
Generating Partially Correlated Random Variables
Designing signals to match a target covariance is simpler than it sounds. This post shows how to build partially correlated complex signals by hand for the two-signal case, then generalizes to N signals using the Cholesky decomposition. Short MATLAB examples demonstrate the two-line implementation and the article highlights numerical caveats when a covariance is only positive semidefinite.
A Markov View of the Phase Vocoder Part 2
This post builds a Markov-chain transition graph to guide phase vocoder time-frequency decisions, using spectral correlation data from a Bach violin sonata. It shows how FFT size and the time-stretch factor alpha change bin-to-bin correlations, proposes an inverse-square plus log-boundary probability model for transitions, and demonstrates practical limits and implementation choices with accompanying MATLAB code.
