1 research outputs found
Sequential blind source extraction for quasi-periodic signals with time-varying period
A novel second-order-statistics-based sequential
blind extraction algorithm for blind extraction of quasi-periodic
signals, with time-varying period, is introduced in this paper.
Source extraction is performed by sequentially converging to a
solution that effectively diagonalizes autocorrelation matrices at
lags corresponding to the time-varying period, which thereby explicitly
exploits a key statistical nonstationary characteristic of the
desired source. The algorithm is shown to have fast convergence
and yields significant improvement in signal-to-interference ratio
as compared to when the algorithm assumes a fixed period. The
algorithm is further evaluated on the problem of separation of a
heart sound signal from real-world lung sound recordings. Separation
results confirm the utility of the introduced approach, and
listening tests are employed to further corroborate the results