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.
Tsalaile
Thato
T
Loughborough University, Loughborough LE11 3TU, UK. t.k.tsalaile@lboro.ac.uk
Sameni
Reza
R
Sanei
Saeid
S
Jutten
Christian
C
Chambers
Jonathon
J
D000465:Algorithms; D003198:Computer Simulation; D004562:Electrocardiography; D006347:Heart Sounds; D006801:Humans; D015233:Models, Statistical; D016011:Normal Distribution; D012135:Respiratory Sounds; D012815:Signal Processing, Computer-Assisted